The Focal Ground Glass Continuation Resolved
Radiology. 2020 Jul 7 : 202504.
Review of the Chest CT Differential Diagnosis of Ground-Glass Opacities in the COVID Era
Maansi Parekh, MBBS, DNB, Achala Donuru, MBBS, FRCR, 
Rashmi Balasubramanya, MD, and Sangita Kapur, MBBS, FSCCT
Abstract
Coronavirus disease 2019 (COVID-19), a recently emerged lower respiratory tract illness, has quickly become a pandemic. The purpose of this review is to discuss and differentiate COVID-19 typical imaging findings from other diseases, which can appear similar in the first instance. The typical CT findings of COVID-19 are bilateral and peripheral predominant ground glass opacities. As per the Fleischner Society consensus statement, CT is appropriate in certain scenarios, including patients who are at risk for and/or develop clinical worsening. The probability, that CT findings represent COVID-19, however, depends largely on the pre-test probability of infection, which is in turn defined by community prevalence of infection. When the community prevalence of COVID-19 is low, a large gap exists between positive predictive values of chest CT vs. RT-PCR. This implies that with usage of Chest CT there are a large number of false positive results. Imaging differentiation is important, for management and isolation purposes, and for appropriate disposition of CT false positive patients. We will discuss differential pathology with close imaging resemblance to typical CT imaging features of COVID-19, and, highlight CT features that may help in differentiation from other conditions.
Learning Objectives
After reading the article and taking the test, the reader will be able to:
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■ Identify the multivariate context of appropriate use of imaging in COVID-19 pneumonia,
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■ Specify the limitations of imaging in the diagnosis of COVID-19 pneumonia,
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■ Describe the findings and differentiating features of other lung conditions that can be, frequently mistaken for COVID-19 pneumonia
Accreditation and Designation Statement
The RSNA is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. The RSNA designates this journal-based SA-CME activity for a maximum of 1.0 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Disclosure Statement
The ACCME requires that the RSNA, as an accredited provider of CME, obtain signed disclosure statements from the authors, editors, and reviewers for this activity. For this journal-based CME activity, author disclosures are listed at the end
Introduction
An acute lower respiratory tract infection caused by the novel Coronavirus (nCoV-2019) was first reported in China in December 2019 (1, 2). The clinical spectrum of disease with nCoV-2019 infection (COVID-19) is variable and ranges from an asymptomatic infection, mild upper respiratory tract illness to severe viral pneumonia with respiratory failure and occasionally death (2). While the case fatality ratio has been as high as 15%, the incidence of critical illness has been reported to be 7-26% (3). Patient factors that have been associated with a higher incidence of critical illness and death include male sex, age > 60 years, obesity, diabetes, hypertension, cardiopulmonary comorbidities, higher values of D-dimer and IL-6. (3).
At the time of writing this article, more than 8 million cases and 450,000 deaths worldwide have been reported. The COVID-19 pandemic has resulted in an unprecedented healthcare crisis with immense strain on healthcare resources and disruptions in both routine and emergency health care delivery (4). The lack of adequate diagnostic testing has resulted in suboptimal early detection and containment of this infection, which has contributed to rapid and widespread transmission by undetected individuals with mild or no symptoms (5). The primary diagnostic test, reverse transcriptase-polymerase chain reaction (RT-PCR) assay for COVID-19, has variable sensitivity ranging from 37-71% (5) depending on the rate of viral expression at the time of collection and the site of specimen collection (6). Obstacles to the use of RT-PCR testing include shortage of kits and extended processing period.
Chest CT in COVID-19 pneumonia demonstrates bilateral, peripheral and basal predominant ground glass opacities (GGOs) and/or consolidation in nearly 85% of patients with superimposed irregular lines and interfaces; the imaging findings peak at 9-13 days post-infection (7,8) [Figure 1]. Subsequently, a mixed pattern evolves with crazy paving, architectural distortion and perilobular abnormalities superimposed on GGOs with slow resolution (7) [Figure 1]. Importantly, CT may be normal in an infected patient, particularly early in the disease (8). Atypical Chest CT findings include upper lobe or peribronchovascular distribution of GGOs, cavitation, tree in bud nodules, lymphadenopathy, and pleural thickening (9). Tables 1 and 2 summarize common and uncommon findings of COVID-19 (10-21). It is vitally important to remember that the CT imaging appearance is dependent on when CT is performed during the patient's time course of this disease.
(a,b) COVID 19 pneumonia: A 77-year old male patient presented with low grade fever and shortness of breath since 1 week. Chest CT shows hazy opacities in both lungs predominantly peripheral in distribution (arrows). These are the typical features of the disease that have been reported with COVID-19 infection. (c,d) COVID crazy paving: The patient is a 58 year old male presents with lightheadedness. CXR and CT chest supported viral pneumonia diagnosis. His COVID testing was positive. CT shows crazy paving pattern (arrow). (e,f) COVID consolidation: 86 year old female with past medical history of hypertension, hyperlipidemia and type 2 diabetes presented with generalized weakness and cough. The patient was found to be positive for COVID. The patient passed away 9 days after admission. Chest CT shows widespread alveolar consolidation with typical radiological findings of ARDS.
Table 1:
Common chest CT findings for COVID-19 pneumonia and their original publications
Table 2:
Uncommon CT findings in isolated COVID-19 pneumonia
Patients may also develop cardiac involvement with COVID-19. Risk factors for developing cardiovascular disease include advancing age, impaired immune system, or elevated levels of Angiotensin-converting enzyme 2 (ACE2) and has prognostic implications (22). Studies have reported incidence of myocardial injury with troponin elevation in 7-17% of hospitalized patients and 22-31% of patients admitted to the intensive care unit (8, 9, 23, 24). Cardiac involvement manifests as myocarditis, pericarditis and heart failure, with corresponding imaging findings on chest x-ray, CT and MRI (25, 26, 27). The pathophysiology includes virus infiltration, cardiac stress and inflammation (25, 26). The left ventricular ejection fraction may be preserved or reduced. Acute coronary syndromes have been reported with a proposed mechanism of increased thrombotic activity (25).
The Fleischner consensus statement on the role of chest imaging in COVID-19 is written with a multivariate perspective of disease severity, pre-test probability, risk factors for and/or evidence of disease progression and availability of diagnostic testing (5). As per the consensus statement, CT is appropriate in establishing baseline pulmonary status and identifying underlying cardiopulmonary abnormalities in patients with moderate to severe disease. CT can help triage resources towards patients at risk of disease progression and may identify a cause in case of clinical worsening. CT may also identify an alternate diagnosis (5). CT findings concerning for COVID-19 may be found incidentally in asymptomatic patients in the setting of known community transmission. Aymptomatic carriers of COVID-19 may comprise 17.9-33.3% of infected cases (28, 29). Such patients need to be directed towards RT-PCR testing.
In a resource constrained environment with high community burden of disease and rapid point of care (PoC) testing either unavailable or negative, CT has been used to rapidly triage patients into non COVID-19, possible or most likely COVID-19 (Table 3). Given the presence of CT abnormalities, the probability that the CT findings represent COVID-19 depends largely on the pre-test probability of infection, which is defined by community prevalence of infection and modified by individual factors such as exposure history (5, 30). If the disease prevalence is high, even atypical presentations are likely to represent COVID-19. On the other hand, if the disease prevalence is low, CT findings that are other otherwise quite typical of COVID-19 may be caused by another disease (30). The positive and negative predictive values (PPV and NPV), which are calculated using disease prevalence in the community, are useful to consider in comparison to sensitivity and specificity, which can only be used when the true COVID-19 status is already known. Therefore, CT diagnosis is not used in isolation without acknowledging the prevalence of disease in the community. As expected, the metrics of diagnostic performance for chest CT (PPV, NPV, sensitivity and specificity) are strictly valid only for the study population from which they are obtained (30).
Table 3:
Differential diagnosis of CT ground glass opacities in the COVID-19 era
Kim et al performed a meta-analysis to assess diagnostic performance of CT and RT-PCR (31). For Chest CT the PPV ranged from 1.5% to 30.7% and NPV ranged from 95.4% to 99.8%. For RT-PCR, the PPV ranged from 47.3% to 96.4% and NPV ranged from 96.8% to 99.9%. They report a pooled sensitivity of 94% (95% CI: 91%, 96%; I 2=95%) for Chest CT and 89% (95% CI: 81%, 94%; I 2 =90%) for RT-PCR. The pooled specificity of Chest CT was 35% (95% CI: 26%, 50%). They found that, given the low specificity of CT, a large gap existed between PPV of chest CT vs RT-PCR in low-prevalence areas, specifically if the disease prevalence was less than 10% (31). These results imply that use of Chest CT may result in a large number of false positive results that may lead to further diagnostic testing, greater medical cost and workload and patient anxiety. Patients with suspected COVID-19 on chest CT may be placed in dedicated COVID-19 rule out units and may experience delay in care or intervention. Thus attempts at differentiation of chest CT abnormalities is important for management and isolation of patients with high clinical suspicion as well as for appropriate disposition of patients where disease prevalence or pre-test probability is low.
Given the lack of specificity of chest CT findings for COVID-19, the purpose of this review is to address the range of pulmonary disease processes that can mimic the CT appearance of COVID-19 pneumonia.
INFECTIONS
Bacterial pneumonias:
Bacterial pneumonia is commonly encountered in clinical practice. Pneumonia is the eighth leading cause of death, and the number one cause of death from infectious disease, in the United States. Bacterial pneumonias are classified into three main groups: Community acquired pneumonia (CAP), Aspiration and Nosocomial or hospital acquired pneumonia. Patients typically present with fever, chills, or cough. Chest radiography is the most commonly used imaging tool in pneumonias. CT should be used in unresolved cases or when complications are suspected. The usual pattern of CAP is that of lobar consolidation. The radiographic patterns of Nosocomial pneumonia are very variable, most commonly showing patchy consolidation, and are associated with cavitation and pleural effusion (32) [Figure 2]. Patients typically have a high white cell count unless they are neutropenic or immunocompromised.
(a,b) Bacterial pneumonia: A 64 year old female patient presented with significant shortness of breath. The patient was noted to have bacteremia secondary to pseudomonas. Chest CT shows mixed ground glass opacities and consolidation in the right upper lobe with cavitation (arrows).
In contrast to COVID-19, bacterial pneumonia characteristically produces focal segmental or lobar pulmonary opacities without lower lung predominance. Complications or associated findings such as cavitation, lung abscess, lymphadenopathy, parapneumonic effusions and empyema, when present, are useful imaging differentiating features, as they are not seen in COVID-19 unless the patients are superinfected with bacterial pneumonia (8).
Viral pneumonias
Viruses are the most common causes of respiratory tract infections and are seen more commonly in children, the elderly and the immunocompromised (33, 34). The most common pathogen causing viral pneumonia in both, immunocompetent and immunocompromised, is Influenza virus (33). The clinical signs and symptoms of viral pneumonia are often diverse and depend on host immune status (34). The spectrum of CT findings encountered in various pulmonary viral diseases encompasses four main categories: (a) GGO and consolidation; (b) nodules, micronodules, and tree-in-bud opacities; (c) interlobular septal thickening; and (d) bronchial and/or bronchiolar wall thickening (35) [Figure 3]. Lymphadenopathy and pleural effusions may also be present (36). Some of the viral pneumonias can present with significant ground glass opacity and include Cytomegalovirus (CMV), Adenovirus, Herpes Simplex Virus (HSV), Varicella zoster, Measles, Human meta-pneumovirus (HMPV) and Influenza (33, 37). Percentage area of lung involvement with GGOs with different viruses has been extensively described. GGOs can be seen in 50-75% with Adenovirus, over 75% with CMV and HSV and 10-25% in HMPV and measles (33).
(a,b) CMV pneumonia: 31 year old female with a past medical history of Type 1 Diabetes mellitus complicated by end stage renal disease, s/p kidney/pancreas transplant presents with 2 days of right lower quadrant abdominal pain associated with nausea/vomiting. Upon further work-up, patient was found to have CMV viremia. CT demonstrates diffuse randomly distributed small pulmonary nodules (arrows), many of them are ill-defined and distributed in the secondary pulmonary lobules, and also in the perilymphatic regions.
Out of the 4 patterns of viral disease, described above, the pattern that can be confused with COVID-19 is GGO as the predominant finding. Therefore, in our discussion we will focus on viruses that demonstrate predominantly this CT finding.
The viral infections most often described to have features that resemble COVID-19, include Influenza, CMV, and other coronaviruses (38-41). As for differentiation from Influenza, as per Liu, et al though peripheral GGOs and consolidation are seen in both these entities, round opacities and septal thickening are more common in COVID-19. Conversely, nodules, tree in bud opacities and pleural effusion are more common in Influenza (38).
Li et al, explored differences in CT features of COVID-19 versus other Coronaviridae, severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). They report that GGO, consolidation, septal thickening and air bronchogram sign were similar in COVID-19, SARS and MERS, while, reversed halo sign and pulmonary nodules associated with COVID-19 have not been previously described with SARS and MERS. Lung abnormalities in SARS are more commonly reported to be unifocal (40).
CMV, a cause of severe lung infection in immunocompromised patients, such as those with HIV and organ transplant recipients, can result in widespread GGOs. The clinical context and timing since transplant is best distinguishing feature (33).
HMPV is predominantly seen in stem cell transplant patients and those with hematological malignancies. HPIV occurs in approximately 21% of the intensive care unit patients, and bacterial coinfection is a known association (42). HMPV pneumonia shows multifocal patchy consolidation with GGO on CT. Centrilobular nodules and bronchial wall thickening, seen in 25% are useful differentiating features (43).
Overall, according to Bai et al, compared to non-COVID-19 viral pneumonia, parenchymal opacities in COVID-19 pneumonia were more likely to be peripheral (80% vs. 57%), and have GGO (91% vs. 68%), fine reticular opacity (56% vs. 22%) and vascular thickening (11% vs. 1%). COVID-19 patients were less likely to have central and peripheral distribution (14% vs. 35%), air bronchograms (14% vs. 23%), pleural thickening (15% vs. 33%), pleural effusion (4 vs. 39%) and lymphadenopathy (2.7% vs. 10.2%) (17).
Pneumocystis pneumonia
Pneumocystis jirovecii (PJP) is a common opportunistic infection that causes pneumonia in immunocompromised patients and, rarely, in immunocompetent individuals. It typically occurs with CD4 counts <200 cells/mm (44). The presentation of PJP in a patient with HIV infection is typically subacute, characterized by a slow onset of dry cough and dyspnea. PJP in patients without HIV infection presents as an acute illness associated with severe hypoxia and results in rapid respiratory deterioration and respiratory failure (45). The radiographic findings of PJP are nonspecific, and in as many as a third of infected patients, they may be normal (46).The most common high-resolution CT (HRCT) finding of PJP is diffuse GGO, which is often greater in extent in patients without HIV infection (45). With more advanced disease, crazy paving pattern, consolidation, nodules and cysts can also develop. Lung consolidation is more common in patients without HIV infection (47) [Figure 4].
(a,b) - Pneumocystis carinii pneumonia: 32 yr old male with AIDS and a CD4 of 7 presented with respiratory arrest. CT demonstrates a moderate right pneumothorax (asterisk) and widespread ground glass and air space opacities.
(a,b) - Pneumocystis carinii pneumonia: 32 yr old male with AIDS and a CD4 of 7 presented with respiratory arrest. CT demonstrates a moderate right pneumothorax (asterisk) and widespread ground glass and air space opacities.
Unlike COVID-19, PJP predominantly affects immunosuppressed patients. Although there may be widespread GGO in PJP, in contrast to COVID-19 pneumonia, it is upper lobe predominant. Nodules, cysts, and spontaneous pneumothorax can also develop.
INTERSTITIAL LUNG DISEASES
Nonspecific interstitial pneumonia
Nonspecific interstitial pneumonia (NSIP) is a common interstitial lung disease (ILD) associated with a number of conditions such as connective tissue disorders, i.e., Systemic Sclerosis, Sjögren's syndrome, polymyositis, dermatomyositis and systemic lupus erythematosus (SLE). Additionally it can be related to autoimmune diseases such as rheumatoid arthritis, primary biliary cirrhosis, graft versus host disease or drug induced (48, 49). NSIP typically presents in middle age patients, with a higher predilection in women. The symptoms are non-specific and include chronic dyspnea and cough without sputum production. Pulmonary function tests show a restrictive pattern of decreased lung function and reduced gas exchange capacity. HRCT of the chest demonstrates predominantly basilar perivascular GGOs in the earlier stages of the disease, known as cellular NSIP. As the disease progresses fibrotic changes develop in the form of traction bronchiectasis, volume loss, architectural distortion and subpleural irregular reticular opacity [Figure 5]. A hallmark feature of NSIP on HRCT chest is subpleural sparing, however, it is only seen in a few cases (50). Microcystic honeycombing maybe seen with NSIP, where there are subpleural cystic spaces measuring less than 4 mm.
Nonspecific interstitial pneumonitis: CT shows subpleural interstitial prominence, most predominant in both lower lobes with associated traction bronchiectasis
In comparison to COVID-19, the symptoms of NSIP are insidious in onset. There is known association with connective tissue disorders or other predisposing condition. Subpleural sparing, when present is considered specific for NSIP. Stigmata of fibrosis (traction bronchiectasis, architectural distortion and honeycombing) may be seen. If rapidly developing airspace consolidation or ground glass abnormality is seen in an acutely ill patient with NSIP, one should consider the possibility of an acute exacerbation (51).
Desquamative interstitial pneumonia
Desquamative interstitial pneumonia is a relatively rare ILD seen more commonly in men. It can also be related to marijuana smoke inhalation, infections such as HIV, toxins or occupational exposure such as asbestos (52, 53, and 54). Patients are predominantly middle aged with progressively worsening shortness of breath and chronic cough. Majority of them are smokers. HRCT demonstrates predominantly peripheral and lower lobe GGOs [Figure 6]. Some cases may demonstrate fine linear or reticular opacities, in the peripheral and basal lung zones (55).
(a,b) - Desquamative interstitial pneumonitis: 54 year old male patient with long smoking history presented with declining pulmonary function. CT chest showed irregular linear opacities and small cysts in both lower lobes. Lung biopsy confirmed desquamative interstitial pneumonitis.
(a,b) - Desquamative interstitial pneumonitis: 54 year old male patient with long smoking history presented with declining pulmonary function. CT chest showed irregular linear opacities and small cysts in both lower lobes. Lung biopsy confirmed desquamative interstitial pneumonitis.
The strong association of DIP with smoking is a useful differentiating feature. Small cystic spaces may develop within the areas of GGO, not usually seen with COVID-19 (56).
Organizing pneumonia
Patients with organizing pneumonia (OP) present with a relatively short history of breathlessness. Additionally they have non-productive cough, weight loss, malaise and fever. OP may have unilateral or bilateral lung involvement and has myriad pulmonary manifestations. The most frequent features on HRCT include bilateral, multifocal, patchy consolidations (present in up to 90% of cases) and ground-glass abnormalities (57) [Figure 7]. Less commonly bronchovascular nodules and bronchial wall thickening can be seen. The reverse halo sign also called atoll sign is considered a hallmark feature, however is seen in only 20% of patients (58). A perilobular pattern is seen in over half of the patients. It appears as polygonal mainly subpleural opacities surrounded by aerated lung (59). The lung manifestations of OP that resemble COVID-19 disease include lower lobe, subpleural and peribronchovascular predominant GGOs and opacities with reverse-halo appearance. The former opacities are migratory in 11-24% (60).
(a,b) - Organizing Pneumonia: 43-year-old, Caucasian male with a history of follicular lymphoma, status post chemotherapy. He was admitted for respiratory failure. Lung biopsy yielded organizing pneumonia. He did well on steroids and was discharged.
(a,b) - Organizing Pneumonia: 43-year-old, Caucasian male with a history of follicular lymphoma, status post chemotherapy. He was admitted for respiratory failure. Lung biopsy yielded organizing pneumonia. He did well on steroids and was discharged.
Presence of predisposing conditions can suggest OP. In contrast to COVID-19, pulmonary opacities are often migratory. Perilobular thickening, if present is another helpful differentiating feature. Patients typically respond to steroids.
EXPOSURES
Inhalational
Hypersensitivity pneumonitis
Hypersensitivity pneumonitis (HP) or extrinsic allergic alveolitis (EAA), is also known as bird fanciers disease, farmer's lung and hot tub lung, based on the inciting agent. The disease is divided into acute, subacute and chronic type based on timing since presentation. Each of these stages has their own distinctive appearance on HRCT and patients may present with some degree of overlap between stages (61). In the acute phase patients typically present with fever, cough, dyspnea of short duration and myalgia, while they present with weight loss, fatigue, exertional dyspnea, cough possibly with clear sputum in the chronic stages. There are subtle to more diffuse GGOs in the acute phase, which may mimic pulmonary edema (62). The subacute stage is seen weeks to months after the first exposure to allergen. There are distinct tiny centrilobular pulmonary nodules, measuring less than 6 mm. There may be accompanying GGOs. In the fibrotic stage there is bilateral predominantly perihilar fibrosis with mid zone predominance. The distinct feature of HP is mosaic attenuation of the lungs. This pattern represents geographical areas of high attenuation interspersed with areas of low attenuation due to air trapping (Headcheese sign) [Figure 8]. Rarely, lung cysts may be present, related to small airways disease (63).
(a,b) - Hypersensitivity pneumonitis: 28-year-old female presented with chronic cough associated with shortness of breath dyspnea on exertion. She lives at home where her sister has an African gray parrot. CT shows widespread ground-glass opacities. There is hypoattenuation and hypovascularity of scattered secondary lobules (head cheese sign). Her clinical symptoms worsened and she was diagnosed with hypersensitivity pneumonitis.
(a,b) - Hypersensitivity pneumonitis: 28-year-old female presented with chronic cough associated with shortness of breath dyspnea on exertion. She lives at home where her sister has an African gray parrot. CT shows widespread ground-glass opacities. There is hypoattenuation and hypovascularity of scattered secondary lobules (head cheese sign). Her clinical symptoms worsened and she was diagnosed with hypersensitivity pneumonitis.
Although widespread GGO with HP, can appear similar to COVID-19 pneumonia, other findings such as poorly defined centrilobular GGO, mosaic attenuation, and air trapping on expiratory images can help distinguish the two conditions (Figure 8). In late HP, mid to upper lung zone fibrosis may be present.
Electronic Cigarette or Vaping Product Use Lung Injury (EVALI)
The Center of Disease Control (CDC) identified an outbreak of a respiratory illness in patients with history of vaping in 2019. The entity which is mainly identified in younger patients was named EVALI, given its association with use of e-cigarettes (64). EVALI clinically manifests as an acute viral illness with nearly all patients reporting respiratory symptoms, 75% report also had gastrointestinal symptoms while 85% reported constitutional symptoms (65). It is a diagnosis of exclusion. Most patients improve on supportive treatment, although a small percent succumb to the illness (66). At HRCT, patients demonstrate bilateral and symmetric diffuse hazy ground glass opacities with subpleural sparing without zonal predominance [Figure 9]. Upper lung zone predominant centrilobular nodules may also be present. Later in the disease process there is evidence of organization with architectural distortion and stigmata of fibrosis (64).
(a,b) - E-cigarette or vaping product use associated lung injury: 18 year old male with a history of vaping presented with fever, leukocytosis and pleuritic chest pain. Chest radiograph demonstrates lower lobe predominant air space opacities. CT chest shows multiple perihilar and lower lobe predominant ground glass opacities.
(a,b) - E-cigarette or vaping product use associated lung injury: 18 year old male with a history of vaping presented with fever, leukocytosis and pleuritic chest pain. Chest radiograph demonstrates lower lobe predominant air space opacities. CT chest shows multiple perihilar and lower lobe predominant ground glass opacities.
Most patients report their last episode of vaping the week before symptom onset. In contrast to COVID-19, the GGOs in EVALI are most pronounced centrally with conspicuous subpleural sparing. Any of the lung zones may be involved. Presence of upper lobe predominant centrilobular nodules is another useful differentiating feature.
Drug toxicity
There is a growing list of drugs leading to pulmonary adverse effects with recent addition of immunotherapy related medications to the list. The characteristic feature of drug induced pneumonitis is the onset of symptoms such as dry cough and breathlessness following the use of a new medication. Drug induced pneumonitis usually occurs while the patient is taking the drug rather than after withdrawal. There are varied manifestations, including diffuse GGOs, depending on the inciting drug. The on-line website and mobile app Pneumotox is very useful to help sort out the number of drugs that can be associated with lung pathology (67). We have discussed the imaging appearance and differentiating features of ILD above, which are common drug related findings in the lungs. This section will focus on Immune checkpoint inhibitors as pneumonitis related to these drugs bears close resemblance to COVID-19. Drug-related pneumonitis is observed in 3-6% of patients with non-small cell lung cancer (NSCLC) who are on immunotherapy (68, 69). Four CT patterns have been reported: Cryptogenic organizing pneumonia (COP), NSIP, HP and acute interstitial pneumonia (AIP) [Figure 10].
(a,b) - Drug induced pneumonitis: 61 year old woman with history of stage IIIA non-small cell lung cancer s/p chemoradiation followed by immunotherapy (durvalumab). Her course was complicated by pneumonitis. The patient improved with steroid treatment.
(a,b) - Drug induced pneumonitis: 61 year old woman with history of stage IIIA non-small cell lung cancer s/p chemoradiation followed by immunotherapy (durvalumab). Her course was complicated by pneumonitis. The patient improved with steroid treatment.
Diagnosis of drug-induced lung disease is based on definite temporal relation between drug intake and development of respiratory symptoms or imaging abnormality. The relationship may be difficult to establish when lung disease develops after drug withdrawal. Drug-withdrawal generally results in improvement.
MISCELLANEOUS
Pulmonary edema
Pulmonary edema is the abnormal accumulation of fluid in the extravascular compartments of the lung, and, may be classified as increased hydrostatic pressure edema seen in heart failure, permeability edema with diffuse alveolar damage (DAD) as seen in ARDS, permeability edema without DAD which can be seen with administration of various drugs, and ingestion of toxins, or mixed edema seen in patients with stroke, status epilepticus and subarachnoid hemorrhage (70). Symptoms include acute breathlessness, cough, wheezing, orthopnea and paroxysmal nocturnal dyspnea. Findings of interstitial pulmonary edema are GGO, bronchovascular and interlobular septal thickening (71). Alveolar edema manifests as airspace consolidation in addition to the above findings. Pleural effusions are a frequent accompanying finding in cardiogenic pulmonary edema (72) [Figure 11].
(a,b) - Pulmonary edema: A 67 year old female with cardiac history notable for congestive heart failure, coronary artery disease, aortic stenosis and past myocardial infarction presented with dizziness. CT performed to rule out pulmonary embolism demonstrates bilateral pleural effusions and pulmonary interstitial edema (arrows).
(a,b) - Pulmonary edema: A 67 year old female with cardiac history notable for congestive heart failure, coronary artery disease, aortic stenosis and past myocardial infarction presented with dizziness. CT performed to rule out pulmonary embolism demonstrates bilateral pleural effusions and pulmonary interstitial edema (arrows).
History of an acute cardiac event or of progressive symptoms of heart failure suggests this diagnosis over COVID-19. The distribution of GGO's (usually central or gravity-dependent), lymphadenopathy, and pleural effusions, in hydrostatic pulmonary edema, are useful differentiating features. There may be indicators of cardiac disease on imaging, including coronary artery calcifications, cardiomegaly and evidence of prior coronary intervention.
As previously mentioned, patients may develop pulmonary edema from COVID-19 related cardiac involvement [Figure 12] (73).
(a-c) - COVID with coexisting heart failure: A 69 year old male presented with acute on chronic CHF with ejection fraction of 28%. The patient tested positive for COVID-19. Note patchy peripherally distributed GGO's (arrowheads). The patient also has moderate bilateral pleural effusions (arrows).
(a-c) - COVID with coexisting heart failure: A 69 year old male presented with acute on chronic CHF with ejection fraction of 28%. The patient tested positive for COVID-19. Note patchy peripherally distributed GGO's (arrowheads). The patient also has moderate bilateral pleural effusions (arrows).
(a-c) - COVID with coexisting heart failure: A 69 year old male presented with acute on chronic CHF with ejection fraction of 28%. The patient tested positive for COVID-19. Note patchy peripherally distributed GGO's (arrowheads). The patient also has moderate bilateral pleural effusions (arrows).
Aspiration
Aspiration pneumonia occurs due to an insult from entry of a foreign substance into the respiratory tract which could be solid or liquid. Lung damage is mainly the result of pulmonary infection from aspiration of colonized oropharyngeal secretions. Risk factors include alcohol intoxication, general anesthesia, loss of consciousness, structural abnormalities of the pharynx and esophagus, and neuromuscular disorders (74). Clinical features range from no symptoms to severe distress with respiratory failure. Symptom onset may be acute or sub-acute. Acute chemical pneumonitis is characterized by a sudden onset of dyspnea, hypoxemia, tachycardia, and diffuse wheezes or crackles (75).
Aspiration can lead to the development of lobar or segmental pneumonia, bronchopneumonia, lung abscess, and empyema. In recumbent patients, the posterior segment of the upper lobes and the superior segment of the lower lobes are most commonly involved. Aspiration is more likely to involve bilateral basal segments, middle lobe, and lingula when it occurs while the patient is upright (76). A chest radiograph may be negative early in the course of aspiration pneumonia. Komiya et al described that GGOs, centrilobular nodules, consolidation and atelectasis are frequently noted CT findings with aspiration (77). Chronic aspiration results in bronchiectasis and tree-in-bud opacities (74).
There are similarities in the imaging appearance of aspiration and COVID-19 pneumonia due to involvement of peripheral portions of lungs with mixed density parenchymal opacity. The presence of centrilobular nodules, dependent tree-in-bud nodularity, and, when present, complications such as lung abscess, empyema or visible aspirated material are helpful differentiating features. Additionally, imaging findings of predisposing conditions may be present, e.g., dilated esophagus, neuromuscular disorders and anatomic abnormality, such as tracheo-esophageal fistula and head and neck malignancy (78).
Diffuse alveolar hemorrhage
Diffuse alveolar hemorrhage (DAH) occurs due to passage of blood into the alveoli. It can be seen in coagulation disorders, antiphospholipid antibody syndrome, connective tissue diseases, vasculitides, medications, inhaled toxins, pulmonary hemosiderosis and pulmonary veno-occlusive disorders. Patients with DAH may present with hemoptysis and/or anemia on laboratory testing. A third of patients may not have hemoptysis. BAL is usually required to confirm the diagnosis and rule out other causes for the opacities on imaging. Imaging findings depend upon the chronicity of the process. Initially DAH may present with GGOs. After two to three days intralobular and smooth interlobular septal thickening superimpose on areas of GGOs and may sometimes give rise to a crazy-paving pattern (79) [Figure 13]. In the chronic stages, the GGOs typically recede and there maybe residual centrilobular nodules.
(a, b) Diffuse alveolar hemorrhage: 47 yr old female w recurring hemoptysis. CT demonstrates widespread ground glass opacities in both lungs (arrow).
(a, b) Diffuse alveolar hemorrhage: 47 yr old female w recurring hemoptysis. CT demonstrates widespread ground glass opacities in both lungs (arrow).
There is often history of hemoptysis and a new drop in hemoglobin which favors this diagnosis. DAH is frequently associated with connective tissue disease and renal disease. BAL shows sequentially increasing RBC counts. The GGOs in DAH, unlike COVID-19 do not have a specific pattern, otherwise, imaging findings of DAH are very similar to COVID-19 and differentiation may only be possible based on clinical history, comparison with any available prior imaging, and BAL or viral testing.
Pulmonary alveolar proteinosis
Pulmonary alveolar proteinosis (PAP) is characterized by periodic acid Schiff stain positive material within the alveoli. It maybe idiopathic in origin, related to hematological malignancies, seen in immunosuppressed patients or inhalational lung disease. Typically patients are asymptomatic or present with minimal dyspnea. Their CT chest findings are out of proportion to their clinical symptoms. LDH may be elevated. PAP presents with smooth interlobular septal thickening with GGOs in both lungs giving the characteristic "crazy paving" appearance of the lungs (80) [Figure 14]. Crazy-paving in PAP is widespread with sharply marginated areas of lobular sparing.
(a, b) Pulmonary alveolar proteinosis: 41 year old female who approximately 6 months ago presented with shortness of breath and a dry cough. A CT scan showed extensive crazy paving appearance of the lung parenchyma, ground-glass opacities with septal thickening. The patient underwent bronchoscopy with biopsy. Findings of bronchoscopy were consistent with pulmonary alveolar proteinosis.
(a, b) Pulmonary alveolar proteinosis: 41 year old female who approximately 6 months ago presented with shortness of breath and a dry cough. A CT scan showed extensive crazy paving appearance of the lung parenchyma, ground-glass opacities with septal thickening. The patient underwent bronchoscopy with biopsy. Findings of bronchoscopy were consistent with pulmonary alveolar proteinosis.
Strong association with smoking and patient presention with non-specific symptoms and slow development of exercise intolerance guide towards PAP. Unlike COVID-19, there is no zonal predilection. Patients may recall a history of similar episode in the past and improvement with BAL [Figure 15].
(a,b) COVID mimicking PAP with crazy paving appearance: A 77 year old male was admitted for fever and cough. CT chest axial lung windows demonstrates crazy paving appearance (arrows) mimicking pulmonary alveolar proteinosis. The patient's PCR was positive for COVID-19.
(a,b) COVID mimicking PAP with crazy paving appearance: A 77 year old male was admitted for fever and cough. CT chest axial lung windows demonstrates crazy paving appearance (arrows) mimicking pulmonary alveolar proteinosis. The patient's PCR was positive for COVID-19.
Eosinophilic Pneumonia
Patients often have asthma and slow onset of fever and respiratory symptoms. The imaging appearance of this condition is classically known as 'photographic negative of pulmonary edema' as the opacities are distinctly peripheral (81). The parenchymal abnormality consists of consolidation and GGO with an upper-lung predominance. Crazy-paving may be present.
Indolent clinical presentation is indolent and middle or upper zone predilection and non-segmental involvement are useful differentiating features.
Conclusion
The typical chest CT imaging features of COVID-19 pneumonia have low specificity due to their overlap with a number of other conditions. This review has focused on highlighting these differences with imaging examples. It is important to note that when the prevalence of COVID-19 is high, even atypical imaging features are more likely to be COVID-19. Although definitive diagnosis cannot be made based on CT imaging features alone, the use of a combination of clinical and imaging findings can substantially improve the accuracy of diagnosis.
Footnotes
Abbreviations:
- AIP
- Acute interstitial pneumonia
- COP
- Cryptogenic organizing pneumonia
- GGOs
- Ground glass opacities
- DAH
- Diffuse alveolar hemorrhage
- DIP
- Desquamative interstitial pneumonitis
- HP
- Hypersensitivity Pneumonitis
- NSIP
- Non-Specific Interstitial Pneumonia
- PJP
- Pneumocystis jirovecii Pneumonia
- PAP
- Pulmonary alveolar proteinosis
- WBC
- White Blood Cell Count
- RT-PCR
- Reverse Transcriptase-Polymerase chain reaction
References
1. Song F, Shi N, Shan F, Zhang Z, Shen J, Lu H, Ling Y, Jiang Y, Shi Y. (2020). Emerging 2019 Novel Coronavirus (2019-nCoV) Pneumonia. Radiology, 295(1), 210–217. doi:10.1148/radiol.2020200274. [PMC free article] [PubMed] [Google Scholar]
2. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, Xiang J, Wang Y, Song B, Gu X, Guan L, Wei Y, Li H, Wu X, Xu J, Tu S, Zhang Y, Chen H, Cao B. (2020). Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. The Lancet, 395(10229), 1054–1062. doi:10.1016/S0140-6736(20)30566-3. [PMC free article] [PubMed] [Google Scholar]
3. Cummings M, Baldwin M, Abrams D, Jacobson S, Meyer B, Balough E, Aaron J, Claassen J, Rabbani LR, Hastie J, Hochman B, Salazar-Schicchi J, Yip N, Brodie D, O'Donnell M. Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study. The Lancet, Volume 395, Issue 10239, 2020,1763-1770, 0140-6736. doi:10.1016/S0140-6736(20)31189-2. [PMC free article] [PubMed] [Google Scholar]
5. Rubin GD, Ryerson CJ, Haramati LB, Sverzellati N, Kanne JP, Raoof S, Schluger NW, Volpi A, Yim JJ, Martin IBK., Anderson DJ, Kong C, Altes T, Bush A, Desai SR, Goldin J, Goo JM, Humbert M, Inoue Y, Leung AN. (2020). The Role of Chest Imaging in Patient Management during the COVID-19 Pandemic: A Multinational Consensus Statement from the Fleischner Society. Radiology, 201365. doi:10.1016/j.chest.2020.04.003. [PMC free article] [PubMed] [Google Scholar]
6. Wang W, Xu Y, Gao R, et al.. Detection of SARS-CoV-2 in Different Types of Clinical Specimens. JAMA. 2020 Mar 11;323(18):1843-1844. doi:10.1001/jama.2020.3786. [PMC free article] [PubMed] [Google Scholar]
7. Wang Y, Dong C, Hu Y, Li C, Ren Q, Zhang X, Shi H, Zhou M. (2020). Temporal Changes of CT Findings in 90 Patients with COVID-19 Pneumonia: A Longitudinal Study. Radiology, 200843. doi:10.1148/radiol.2020200843. [PMC free article] [PubMed] [Google Scholar]
8. Kanne JP, Little BP, Chung JH, Elicker BM, Ketai LH. (2020). Essentials for Radiologists on COVID-19: An Update—Radiology Scientific Expert Panel. Radiology, 200527. doi:10.1148/radiol.2020200527. [PMC free article] [PubMed] [Google Scholar]
9. Li X, Zeng W, Li X, Chen H, Shi L, Li X, Xiang H, Cao Y, Chen H, Liu C, Wang J. CT imaging changes of corona virus disease 2019(COVID-19): a multi-center study in Southwest China. J Transl Med 18, 154 (2020). doi:10.1186/s12967-020-02324-w. [PMC free article] [PubMed] [Google Scholar]
10. Wu J, Wu X, Zeng W. et al. (2020). Chest CT findings in patients with corona virus disease 2019 and its relationship with clinical features. Invest Radiol. 2020 May;55(5):257-261. doi:10.1097/RLI.0000000000000670. [PMC free article] [PubMed] [Google Scholar]
11. Zhao W, Zhong Z, Xie X, Yu Q, Liu J. Relation Between Chest CT Findings and Clinical Conditions of Coronavirus Disease (COVID-19) Pneumonia: A Multicenter Study. American Journal of Roentgenology 2020 214:5, 1072-1077. doi:10.2214/AJR.20.22976. [PubMed] [Google Scholar]
12. Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. Coronavirus Disease 2019 (COVID-19): A Systematic Review of Imaging Findings in 919 Patients. American Journal of Roentgenology. 2020 Mar 14;1-7. doi:10.2214/AJR.20.23034. [PubMed] [Google Scholar]
13. Pan F, Ye T, Sun P, Gui S, Liang B, Li L, Zheng D, Wang J, Hesketh RL, Yang L, Zheng C. Time course of lung changes on chest CT during recovery from 2019 novel coronavirus (COVID-19) pneumonia. Radiology 2020. 2020 Jun;295(3):715-721. doi:10.1148/radiol.2020200370. [PMC free article] [PubMed] [Google Scholar]
14. Zhou S, Wang Y, Zhu T, Xia L. CT Features of Coronavirus Disease 2019 (COVID-19) Pneumonia in 62 Patients in Wuhan, China. American Journal of Roentgenology 2020 214:6, 1287-1294. doi:10.2214/AJR.20.22975. [PubMed] [Google Scholar]
15. Han R, Huang L, Jiang H, Dong J, Peng H, Zhang D. Early clinical and CT manifestations of coronavirus disease 2019 (COVID-19) pneumonia. AJR Am J Roentgenol 2020. doi:10.2214/AJR.20.22961 [PubMed] [Google Scholar]
16. Bernheim A, Mei X, Huang M, Yang Y, Fayad ZA, Zhang N, Diao K, Lin B, Zhu X, Li K, Li S, Shan H, Jacobi A, Chung M. Chest CT Findings in Coronavirus Disease-19 (COVID-19): Relationship to Duration of Infection. Radiology. 2020 Feb 20:200463. doi:10.1148/radiol.2020200463. [PMC free article] [PubMed] [Google Scholar]
17. Bai H, Hsieh B, Xiong Z, et al.. Performance of radiologists in differentiating COVID-19 from viral pneumonia on chest CT [published online ahead of print, 2020 Mar 10]. Radiology. 2020;200823. doi:10.1148/radiol.2020200823 [PMC free article] [PubMed]
18. Meng H, Xiong R, He R, et al.. CT imaging and clinical course of asymptomatic cases with COVID-19 pneumonia at admission in Wuhan, China [published online ahead of print, 2020 Apr 12]. J Infect. 2020;81(1):e33-e39. doi:10.1016/j.jinf.2020.04.004 [PMC free article] [PubMed] [Google Scholar]
19. Chen Q, Zheng Z, Zhang C, et al.. Clinical characteristics of 145 patients with corona virus disease 2019 (COVID-19) in Taizhou, Zhejiang, China. Infection. 2020;1-9. doi:10.1007/s15010-020-01432-5 [PMC free article] [PubMed] [Google Scholar]
20. Li Y, Xia L. Coronavirus Disease 2019 (COVID-19): Role of Chest CT in Diagnosis and Management. American Journal of Roentgenology 2020 214:6, 1280-1286. doi:10.2214/AJR.20.22954. [PubMed] [Google Scholar]
21. Chung M, Bernheim A, Mei X, Zhang N, Huang M, Zeng X, Cui J, Xu W, Yang Y, Fayad ZA, Jacobi A, Li K, Li S, Shan H. CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV). Radiology. 2020 Apr;295(1):202-207. doi:10.1148/radiol.2020200230. [PMC free article] [PubMed] [Google Scholar]
22. Clerkin KJ, Fried JA, Raikhelkar J, et al.. COVID-19 and Cardiovascular Disease. Circulation. 2020;141(20):1648-1655. doi:10.1161/CIRCULATIONAHA.120.046941 [PubMed] [Google Scholar]
23. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, et al.. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus–infected pneumonia in Wuhan, China. JAMA. 2020; 323:1061–1069. doi:10.1001/jama.2020.1585 [PMC free article] [PubMed] [Google Scholar]
24. Long B, Brady WJ, Koyfman A, Gottlieb M. Cardiovascular complications in COVID-19 [ published online ahead of print, 2020 Apr 18]. Am J Emerg Med. 2020;S0735-6757(20)30277-1. doi:10.1016/j.ajem.2020.04.048 [Google Scholar]
25. Akbarshakh A, Eduardo M. (2020). COVID-19 and the Heart. Circulation Research, 2020 May 8;126(10):1443-1455. doi:10.1161/CIRCRESAHA.120.317055. [PMC free article] [PubMed] [Google Scholar]
26. Ni W, Yang X, Liu J, Bao J, Li R, Xu Y, Guo W, Hu Y, Gao Z. (2020). Acute Myocardial Injury at Hospital Admission is Associated with All-cause Mortality in COVID-19. J Am Coll Cardiol. 2020 May 8;S0735-1097(20)35225-6. doi:10.1016/j.jacc.2020.05.007. [PMC free article] [PubMed] [Google Scholar]
27. Huang L, Zhao P, Tang D, Zhu T, Han R, Zhan C, Liu W, Zeng H, Tao Q, Xia L. (2020). Cardiac involvement in recovered COVID-19 patients identified by magnetic resonance imaging. JACC. Cardiovascular Imaging, 13 May 2020, doi:10.1016/j.jcmg.2020.05.004 [Google Scholar]
28. Mizumoto K, Kagaya K, Zarebski A, Chowell G. Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020. Euro Surveill 2020;25(10). [PMC free article] [PubMed] [Google Scholar]
29. Nishiura H, Kobayashi T, Suzuki A. et al.. Estimation of the asymptomatic ratio of novel coronavirus infections (COVID-19). Int J Infect Dis 2020 Mar 13 [Epub ahead of print]. [PMC free article] [PubMed] [Google Scholar]
30. Eng J, Bluemke D. Imaging Publications in the COVID-19 Pandemic: Applying New Research Results to Clinical Practice. Radiology. 2020 Apr 23:201724. doi:10.1148/radiol.2020201724. [PMC free article] [PubMed] [Google Scholar]
31. Kim H, Hong H, Yoon SH. (2020). Diagnostic Performance of CT and Reverse Transcriptase-Polymerase Chain Reaction for Coronavirus Disease 2019: A Meta-Analysis. Radiology. 2020 Apr 17;201343. doi:10.1148/radiol.2020201343. [PMC free article] [PubMed] [Google Scholar]
32. Vilar J, Domingo ML, Soto C, Cogollos J. Radiology of bacterial pneumonia. European Journal of Radiology. European Journal of Radiology, 31 Jul 2004, 51(2):102-113. doi:10.1016/j.ejrad.2004.03.010 [PubMed] [Google Scholar]
33. Koo HJ, Lim S, Choe J, Choi SH, Sung H, Do KH. (2018). Radiographic and CT Features of Viral Pneumonia. Radiographics. May-Jun 2018;38(3):719-739. doi:10.1148/rg.2018170048. [PubMed] [Google Scholar]
34. Marcos MA, Esperatti M, Torres A. Viral pneumonia. Current Opinion in Infectious Diseases, 31 Mar 2009, 22(2):143-147. doi:10.1097/qco.0b013e328328cf65. [PubMed] [Google Scholar]
35. Müller NL. Differential diagnosis of chronic diffuse infiltrative lung disease on high-resolution computed tomography. Semin Roentgenol. 1991 Apr;26(2):132-42. doi:10.1016/0037-198x(91)90007-b. [PubMed] [Google Scholar]
36. Franquet T. Imaging of pulmonary viral pneumonia. Radiology. 2011 Jul;260(1):18-39. doi:10.1148/radiol.11092149. [PubMed] [Google Scholar]
37. Miller W, Shah R. Isolated diffuse ground-glass opacity in thoracic CT: causes and clinical presentations. AJR Am J Roentgenol. 2005 Feb;184(2):613-22. doi:10.2214/ajr.184.2.01840613. [PubMed] [Google Scholar]
38. Liu M, Zeng W, Wen Y, Zheng Y, Lv F, Xiao K. COVID-19 pneumonia: CT findings of 122 patients and differentiation from influenza pneumonia [published online ahead of print, 2020 May 12]. Eur Radiol. 2020;1-7. doi:10.1007/s00330-020-06928-0 [PMC free article] [PubMed] [Google Scholar]
39. Yin Z, Kang Z, Yang D, Ding S, Luo H, Xiao E. A Comparison of Clinical and Chest CT Findings in Patients With Influenza A (H1N1) Virus Infection and Coronavirus Disease (COVID-19). AJR Am J Roentgenol. 2020 May 26;1-7. doi:10.2214/AJR.20.23214. [PubMed] [Google Scholar]
40. Hosseiny M, Kooraki S, Gholamrezanezhad A, Reddy S, Myers L. (2020). Radiology Perspective of Coronavirus Disease 2019 (COVID-19): Lessons From Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome. AJR Am J Roentgenol. 2020 May;214(5):1078-1082. doi:10.2214/AJR.20.22969. [PubMed] [Google Scholar]
41. D'Ardes D, Boccatonda A, Schiavone C, Santilli F, Guagnano MT, Bucci M, Cipollone F. A case of coinfection with SARS-COV-2 and cytomegalovirus in the era of COVID-19. EJCRIM 2020;7 doi:10.12890/2020_001652. [PMC free article] [PubMed] [Google Scholar]
42. Choi SH, Hong SB, Ko GB. et al.. Viral infection in patients with severe pneumonia requiring intensive care unit admission. Am J Respir Crit Care Med. 2012 Aug 15;186(4):325-32. doi:10.1164/rccm.201112-2240OC. [PubMed] [Google Scholar]
43. Kim MC, Kim MY, Lee HJ. et al.. CT findings in viral lower respiratory tract infections caused by parainfluenza virus, influenza virus and respiratory syncytial virus. Medicine (Baltimore). 2016 Jun;95(26):e4003. doi:10.1097/MD.0000000000004003. [PMC free article] [PubMed] [Google Scholar]
44. Hidalgo A, Falcó V, Mauleón S, et al.. Accuracy of high-resolution CT in distinguishing between Pneumocystis carinii pneumonia and non-Pneumocystis carinii pneumonia in AIDS patients. Eur Radiol. 2003 May;13(5):1179-84. doi:10.1007/s00330-002-1641-6. [PubMed] [Google Scholar]
45. Hardak E, Brook O, Yigla M. Radiological features of Pneumocystis jirovecii Pneumonia in immunocompromised patients with and without AIDS. Lung. 2010 Apr;188(2):159-63. doi:10.1007/s00408-009-9214-y. [PubMed] [Google Scholar]
46. Kuhlman JE, Kavuru M, Fishman EK, Siegelman SS. Pneumocystis carinii pneumonia: spectrum of parenchymal CT findings. Radiology. 1990;175(3):711-714. doi:10.1148/radiology.175.3.2343118 [PubMed] [Google Scholar]
47. Tasaka S, Tokuda H, Sakai F, Fujii T, Tateda K, Johkoh T, et al.. Comparison of clinical and radiological features of pneumocystis pneumonia between malignancy cases and acquired immunodeficiency syndrome cases: a multicenter study. Intern Med. 2010;49(4):273-81. doi:10.2169/internalmedicine.49.2871. [PubMed] [Google Scholar]
48. Arakawa H, Yamada H, Kurihara Y. et al.. Nonspecific interstitial pneumonia associated with polymyositis and dermatomyositis: serial high-resolution CT findings and functional correlation. Chest. 2003 Apr;123(4):1096-103. doi:10.1378/chest.123.4.1096. [PubMed] [Google Scholar]
49. Poletti V, Romagnoli M, Piciucchi S. et al.. Current status of idiopathic nonspecific interstitial pneumonia. Semin Respir Crit Care Med. 2012 Oct;33(5):440-9. doi:10.1055/s-0032-1325155. [PubMed] [Google Scholar]
50. Silva CI, Müller NL, Lynch DA, Curran-Everett D, Brown KK, Lee KS., Chung MP, Churg A. (2008). Chronic hypersensitivity pneumonitis: differentiation from idiopathic pulmonary fibrosis and nonspecific interstitial pneumonia by using thin-section CT. Radiology. 2008 Jan;246(1):288-97. doi:10.1148/radiol.2453061881. [PubMed] [Google Scholar]
51. Kligerman S, Groshong S, Brown K, Lynch D. Nonspecific Interstitial Pneumonia: Radiologic, Clinical, and Pathologic Considerations. Radiographics. Jan-Feb 2009;29(1):73-87. doi:10.1148/rg.291085096. [PubMed] [Google Scholar]
52. Naidich DP, Srichai MB, Krinsky GA. Computed tomography and magnetic resonance of the thorax. Lippincott Williams & Wilkins. (2007) ISBN:0781757657. [Google Scholar]
53. Freed JA, Miller A, Gordon RE. et al.. Desquamative interstitial pneumonia associated with chrysotile asbestos fibres. Br J Ind Med. 1991 May;48(5):332-7. doi:10.1136/oem.48.5.332. [PMC free article] [PubMed] [Google Scholar]
54. Godbert B, Wissler MP, Vignaud JM. Desquamative interstitial pneumonia: an analytic review with an emphasis on aetiology. Eur Respir Rev. 2013 Jun 1;22(128):117-23. doi:10.1183/09059180.00005812. [PMC free article] [PubMed] [Google Scholar]
55. Hartman TE, Primack SL, Swensen SJ, et al.. Desquamative interstitial pneumonia: thin-section CT findings in 22 patients. Radiology. 1993 Jun;187(3):787-90. doi:10.1148/radiology.187.3.8497631. [PubMed] [Google Scholar]
56. Attili AK, Kazerooni EA, Gross BH, Flaherty KR, Myers JL, Martinez FJ. Smoking-related interstitial lung disease: radiologic-clinical-pathologic correlation. Radiographics. Sep-Oct 2008;28(5):1383-96; discussion 1396-8. doi:10.1148/rg.285075223. [PubMed] [Google Scholar]
57. Jara-Palomares L, Gomez-Izquierdo L, Gonzalez-Vergara D, Rodriguez-Becerra E, Marquez-Martin E, Barrot-Cortés E, Martin-Juan J. (2010). Utility of high-resolution computed tomography and BAL in cryptogenic organizing pneumonia. Respir Med. 2010 Nov;104(11):1706-11. doi:10.1016/j.rmed.2010.06.008. [PubMed] [Google Scholar]
58. Walker CM, Mohammed TL, Chung JH. "Reversed halo sign". J Thorac Imaging. 2011 Aug;26(3):W80. doi:10.1097/RTI.0b013e318224cfbc. [PubMed] [Google Scholar]
59. Ujita M, Renzoni EA, Veeraraghavan S, Wells AU, Hansell DM. Organizing Pneumonia: Perilobular Pattern at Thin-Section CT. Radiology. 2004 Sep;232(3):757-61. doi:10.1148/radiol.2323031059. [PubMed] [Google Scholar]
60. Kligerman SJ, Franks TJ, Galvin JR. From the Radiologic Pathology Archives: Organization and Fibrosis as a Response to Lung Injury in Diffuse Alveolar Damage, Organizing Pneumonia, and Acute Fibrinous and Organizing Pneumonia. Radiographics. Nov-Dec 2013;33(7):1951-75. doi:10.1148/rg.337130057. [PubMed] [Google Scholar]
61. Mohr LC. Hypersensitivity pneumonitis. Curr Opin Pulm Med. 2004 Sep;10(5):401-11. doi:10.1097/01.mcp.0000135675.95674.29. [PubMed] [Google Scholar]
62. Hansell DM, Wells AU, Padley SP, Müller NL. Hypersensitivity pneumonitis: correlation of individual CT patterns with functional abnormalities. Radiology. 1996 Apr;199(1):123-8. doi:10.1148/radiology.199.1.8633133. [PubMed] [Google Scholar]
63. Elicker BM, Jones KD, Henry TS, Collard HR. Multidisciplinary Approach to Hypersensitivity Pneumonitis. J Thorac Imaging. 2016 Mar;31(2):92-103. doi:10.1097/RTI.0000000000000186. [PubMed] [Google Scholar]
64. Kligerman S, Raptis C, Larsen B, Henry TS, Caporale A, Tazelaar H, Schiebler ML, Wehrli FW, Klein JS, Kanne J. (2020). Radiologic, Pathologic, Clinical, and Physiologic Findings of Electronic Cigarette or Vaping Product Use–associated Lung Injury (EVALI): Evolving Knowledge and Remaining Questions. Radiology. 2020 Mar;294(3):491-505. doi:10.1148/radiol.2020192585. [PubMed] [Google Scholar]
65. Layden J, Ghinai I, Pray I, Kimball A, Layer M, Tenforde M, Navon L, Hoots B, Salvatore P, Elderbrook M, Haupt T, Kanne J, Patel M, Saathoff-Huber L, King BA, Schier JG., Mikosz CA, Meiman J. (2020). Pulmonary Illness Related to E-Cigarette Use in Illinois and Wisconsin-Final Report. N Engl J Med. 2020 Mar 5;382(10):903-916. doi:10.1056/NEJMoa1911614. [PubMed] [Google Scholar]
66. Moritz ED, Zapata LB, Lekiachvili A, Glidden E, Annor FB. et al.. Lung Injury Response Epidemiology/Surveillance Task Force (2019). Update: Characteristics of Patients in a National Outbreak of E-cigarette, or Vaping, Product Use-Associated Lung Injuries-United States, October 2019. MMWR Morb Mortal Wkly Rep. 2019 Nov 1;68(43):985-989. doi:10.15585/mmwr.mm6843e1. [PMC free article] [PubMed] [Google Scholar]
68. Camus P, Fanton A, Bonniaud P, Camus C, Foucher P. Interstitial lung disease induced by drugs and radiation. Respiration. Jul-Aug 2004;71(4):301-26. doi:10.1159/000079633. [PubMed] [Google Scholar]
69. Wang GX, Guo LQ, Gainor JF, Fintelmann FJ. (2017). Immune Checkpoint Inhibitors in Lung Cancer: Imaging Considerations. AJR Am J Roentgenol. 2017 Sep;209(3):567-575. doi:10.2214/AJR.16.17770. [PubMed] [Google Scholar]
70. Gluecker T, Capasso P, Schnyder P, Gudinchet F, Schaller M, Revelly J, Chiolero R, Vock P, Wicky S. Clinical and Radiologic Features of Pulmonary Edema. Radiographics. Nov-Dec 1999;19(6):1507-31 ; discussion 1532-3. doi:10.1148/radiographics.19.6.g99no211507. [PubMed] [Google Scholar]
71. Storto ML, Kee ST, Golden JA, Webb WR. Hydrostatic pulmonary edema: high-resolution CT findings. AJR Am J Roentgenol. 1995 Oct;165(4):817-20. doi:10.2214/ajr.165.4.7676973. [PubMed] [Google Scholar]
72. Komiya K, Ishii H, Murakami J, Yamamoto H, Okada F, Satoh K, Takahashi O, Tobino K, Ichikado K, Johkoh T, Kadota J. Comparison of chest computed tomography features in the acute phase of cardiogenic pulmonary edema and acute respiratory distress syndrome on arrival at the emergency department. J Thorac Imaging. 2013 Sep;28(5):322-8. doi:10.1097/RTI.0b013e31828d40b2. [PubMed] [Google Scholar]
73. Arentz M, Yim E, Klaff L, Lokhandwala S, Riedo FX, Chong M, Lee M. (2020). Characteristics and Outcomes of 21 Critically Ill Patients With COVID-19 in Washington State. JAMA. 2020 Mar 19;323(16):1612-1614. doi:10.1001/jama.2020.4326. [PMC free article] [PubMed] [Google Scholar]
74. Franquet T, Giménez A, Rosón N, Torrubia S, Sabaté JM, Pérez C. Aspiration diseases: findings, pitfalls, and differential diagnosis. Radiographics. May-Jun 2000;20(3):673-85. doi:10.1148/radiographics.20.3.g00ma01673. [PubMed] [Google Scholar]
75. Mandell LA, Niederman MS. Aspiration Pneumonia. N Engl J Med. 2019;380(7):651-663. doi:10.1056/NEJMra1714562 [PubMed] [Google Scholar]
76. Kim M, Lee KY, Lee KW, Bae KT. MDCT evaluation of foreign bodies and liquid aspiration pneumonia in adults. AJR Am J Roentgenol. 2008 Apr;190(4):907-15. doi:10.2214/AJR.07.2766. [PubMed] [Google Scholar]
77. Komiya K, Ishii H, Umeki K, et al.. Computed tomography findings of aspiration pneumonia in 53 patients. Geriatr Gerontol Int. 2013;13(3):580-585. doi:10.1111/j.1447-0594.2012.00940.x [PubMed] [Google Scholar]
78. James A, Karunakaran P, Kini R, Thangavel P. Patulous upper esophageal sphincter-an unusual endoscopic finding. Turk J Gastroenterol. 2018 Jan;29(1):116-118. doi:10.5152/tjg.2018.17189. [PMC free article] [PubMed] [Google Scholar]
79. Cortese G, Nicali R, Placido R. et al.. Radiological aspects of diffuse alveolar haemorrhage. Radiol Med. 2008 Feb;113(1):16-28. doi:10.1007/s11547-008-0229-x. [PubMed] [Google Scholar]
80. Frazier AA, Franks TJ, Cooke EO, Mohammed TL, Pugatch RD, Galvin JR. From the archives of the AFIP: pulmonary alveolar proteinosis. Radiographics. May-Jun 2008;28(3):883-99; quiz 915. doi:10.1148/rg.283075219. [PubMed] [Google Scholar]
81. Salisbury ML, Gu T, Murray S, Gross BH, Chughtai A. et al.. Hypersensitivity Pneumonitis: Radiologic Phenotypes Are Associated With Distinct Survival Time and Pulmonary Function Trajectory. Chest. 2019 Apr;155(4):699-711. doi:10.1016/j.chest.2018.08.1076. [PMC free article] [PubMed] [Google Scholar]
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