Association of Artificial Intelligence-Aided Chest Radiograph Interpretation With Reader Performance and Efficiency.

Importance: The efficient and accurate interpretation of radiologic images is paramount. Objective: To evaluate whether a deep learning-based artificial intelligence (AI) engine used concurrently can improve reader performance and efficiency in interpreting chest radiograph abnormalities. Design, Setting, and Participants: This multicenter cohort study was conducted from April to November 2021 and involved radiologists, including attending radiologists, thoracic radiology fellows, and residents, who independently participated in 2 observer performance test sessions. The sessions included a reading session with AI and a session without AI, in a randomized crossover manner with a 4-week washout period in between. The AI produced a heat map and the image-level probability of the presence of the referrable lesion. The data used were collected at 2 quaternary academic hospitals in Boston, Massachusetts: Beth Israel Deaconess Medical Center (The Medical Information Mart for Intensive Care Chest X-Ray [MIMIC-CXR]) and Massachusetts General Hospital (MGH). Main Outcomes and Measures: The ground truths for the labels were created via consensual reading by 2 thoracic radiologists. Each reader documented their findings in a customized report template, in which the 4 target chest radiograph findings and the reader confidence of the presence of each finding was recorded. The time taken for reporting each chest radiograph was also recorded. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) were calculated for each target finding. Results: A total of 6 radiologists (2 attending radiologists, 2 thoracic radiology fellows, and 2 residents) participated in the study. The study involved a total of 497 frontal chest radiographs-247 from the MIMIC-CXR data set (demographic data for patients were not available) and 250 chest radiographs from MGH (mean [SD] age, 63 [16] years; 133 men [53.2%])-from adult patients with and without 4 target findings (pneumonia, nodule, pneumothorax, and pleural effusion). The target findings were found in 351 of 497 chest radiographs. The AI was associated with higher sensitivity for all findings compared with the readers (nodule, 0.816 [95% CI, 0.732-0.882] vs 0.567 [95% CI, 0.524-0.611]; pneumonia, 0.887 [95% CI, 0.834-0.928] vs 0.673 [95% CI, 0.632-0.714]; pleural effusion, 0.872 [95% CI, 0.808-0.921] vs 0.889 [95% CI, 0.862-0.917]; pneumothorax, 0.988 [95% CI, 0.932-1.000] vs 0.792 [95% CI, 0.756-0.827]). AI-aided interpretation was associated with significantly improved reader sensitivities for all target findings, without negative impacts on the specificity. Overall, the AUROCs of readers improved for all 4 target findings, with significant improvements in detection of pneumothorax and nodule. The reporting time with AI was 10% lower than without AI (40.8 vs 36.9 seconds; difference, 3.9 seconds; 95% CI, 2.9-5.2 seconds; P < .001). Conclusions and Relevance: These findings suggest that AI-aided interpretation was associated with improved reader performance and efficiency for identifying major thoracic findings on a chest radiograph.

Lung-RADS Category 3 and 4 Nodules on Lung Cancer Screening in Clinical Practice.

BACKGROUND. Lung-RADS category 3 and 4 nodules account for most screening-detected lung cancers and are considered actionable nodules with management implications. The cancer frequency among such nodules is estimated in the Lung-RADS recommendations and has been investigated primarily by means of retrospectively assigned Lung-RADS classifications. OBJECTIVE. The purpose of this study was to assess the frequency of cancer among lung nodules assigned Lung-RADS category 3 or 4 at lung cancer screening (LCS) in clinical practice and to evaluate factors that affect the cancer frequency within each category. METHODS. This retrospective study was based on review of clinical radiology reports of 9148 consecutive low-dose CT LCS examinations performed for 4798 patients between June 2014 and January 2021 as part of an established LCS program. Unique nodules assigned Lung-RADS category 3 or 4 (4A, 4B, or 4X) that were clinically categorized as benign or malignant in a multidisciplinary conference that considered histologic analysis and follow-up imaging were selected for further analysis. Benign diagnoses based on stability required at least 12 months of follow-up imaging. Indeterminate nodules were excluded. Cancer frequencies were evaluated. RESULTS. Of the 9148 LCS examinations, 857 (9.4%) were assigned Lung-RADS category 3, and 721 (7.9%) were assigned category 4. The final analysis included 1297 unique nodules in 1139 patients (598 men, 541 women; mean age, 66.0 ± 6.3 years). A total of 1108 of 1297 (85.4%) nodules were deemed benign, and 189 of 1297 (14.6%) were deemed malignant. The frequencies of malignancy of category 3, 4A, 4B, and 4X nodules were 3.9%, 15.5%, 36.3%, and 76.8%. A total of 45 of 46 (97.8%) endobronchial nodules (all category 4A) were deemed benign on the basis of resolution. Cancer frequency was 13.1% for solid, 24.4% for part-solid, and 13.5% for ground-glass nodules. CONCLUSION. In the application of Lung-RADS to LCS clinical practice, the frequency of Lung-RADS category 3 and 4 nodules and the cancer frequency in these categories were higher than the prevalence and cancer risk estimated for category 3 and 4 nodules in the Lung-RADS recommendations and those reported in earlier studies in which category assignments were retrospective. Nearly all endobronchial category 4A nodules were benign. CLINICAL IMPACT. Future Lung-RADS iterations should consider the findings of this study from real-world practice to improve the clinical utility of the system.

Clinical and Imaging Features of Non-Small Cell Lung Cancer with G12C KRAS Mutation.

KRAS G12C mutations are important oncogenic mutations that confer sensitivity to direct G12C inhibitors. We retrospectively identified patients with KRAS+ NSCLC from 2015 to 2019 and assessed the imaging features of the primary tumor and the distribution of metastases of G12C NSCLC compared to those of non-G12C KRAS NSCLC and NSCLC driven by oncogenic fusion events (RET, ALK, ROS1) and EGFR mutations at the time of initial diagnosis. Two hundred fifteen patients with KRAS+ NSCLC (G12C: 83; non-G12C: 132) were included. On single variate analysis, the G12C group was more likely than the non-G12C KRAS group to have cavitation (13% vs. 5%, p = 0.04) and lung metastasis (38% vs. 21%; p = 0.043). Compared to the fusion rearrangement group, the G12C group had a lower frequency of pleural metastasis (21% vs. 41%, p = 0.01) and lymphangitic carcinomatosis (4% vs. 39%, p = 0.0001) and a higher frequency of brain metastasis (42% vs. 22%, p = 0.005). Compared to the EGFR+ group, the G12C group had a lower frequency of lung metastasis (38% vs. 67%, p = 0.0008) and a higher frequency of distant nodal metastasis (10% vs. 2%, p = 0.02). KRAS G12C NSCLC may have distinct primary tumor imaging features and patterns of metastasis when compared to those of NSCLC driven by other genetic alterations.

Characteristics and Outcomes of Lung Cancers Detected on Low-Dose Lung Cancer Screening CT.

BACKGROUND: Lung cancer screening (LCS) with low-dose CT (LDCT) was implemented in the United States following the National Lung Screening Trial (NLST). The real-world benefits of implementing LCS are yet to be determined with outcome-oriented data. The study objective is to investigate the characteristics and outcomes of screening-detected lung cancers. METHODS: This single-institution retrospective study included LCS patients between June 2014 and December 2019. Patient demographics, number of screening rounds, imaging features, clinical workup, disease extent, histopathology, treatment, complications, and mortality outcomes of screening-detected lung cancers were extracted and compared with NLST data. RESULTS: LCS LDCTs (7,480) were performed on 4,176 patients. The cancer detection rate was 3.8%, higher than reported by NLST (2.4%, P < 0.0001), and cancers were most often found in patients ≥65 years (62%), older than those in NLST (41%, P < 0.0001). The patients' ethnicity was similar to NLST, P = 0.87. Most LCS-detected cancers were early stage I tumors (71% vs. 54% in NLST, P < 0.0001). Two thirds of cancers were detected in the first round of screening (67.1%) and were multifocal lung cancers in 15%. As in NLST, the complication rate after invasive workup or surgery was low (24% vs. 28% in NLST, P = 0.32). Over a median follow-up of 3.3 years, the mortality rate was 0.45%, lower than NLST (1.33%, P < 0.0001). CONCLUSIONS: LCS implementation achieved a higher cancer detection rate, detection of early-stage cancers, and more multifocal lung cancers compared with the NLST, with low complications and mortality. IMPACT: The real-world implementation of LCS has been successful for detection of lung cancer with favorable outcomes.

Comparison of Chest CT Findings of COVID-19, Influenza, and Organizing Pneumonia: A Multireader Study.

BACKGROUND. Previous studies compared CT findings of COVID-19 pneumonia with those of other infections; however, to our knowledge, no studies to date have included noninfectious organizing pneumonia (OP) for comparison. OBJECTIVE. The objectives of this study were to compare chest CT features of COVID-19, influenza, and OP using a multireader design and to assess the performance of radiologists in distinguishing between these conditions. METHODS. This retrospective study included 150 chest CT examinations in 150 patients (mean [± SD] age, 58 ± 16 years) with a diagnosis of COVID-19, influenza, or non-infectious OP (50 randomly selected abnormal CT examinations per diagnosis). Six thoracic radiologists independently assessed CT examinations for 14 individual CT findings and for Radiological Society of North America (RSNA) COVID-19 category and recorded a favored diagnosis. The CT characteristics of the three diagnoses were compared using random-effects models; the diagnostic performance of the readers was assessed. RESULTS. COVID-19 pneumonia was significantly different (p < .05) from influenza pneumonia for seven of 14 chest CT findings, although it was different (p < .05) from OP for four of 14 findings (central or diffuse distribution was seen in 10% and 7% of COVID-19 cases, respectively, vs 20% and 21% of OP cases, respectively; unilateral distribution was seen in 1% of COVID-19 cases vs 7% of OP cases; non-tree-in-bud nodules was seen in 32% of COVID-19 cases vs 53% of OP cases; tree-in-bud nodules were seen in 6% of COVID-19 cases vs 14% of OP cases). A total of 70% of cases of COVID-19, 33% of influenza cases, and 47% of OP cases had typical findings according to RSNA COVID-19 category assessment (p < .001). The mean percentage of correct favored diagnoses compared with actual diagnoses was 44% for COVID-19, 29% for influenza, and 39% for OP. The mean diagnostic accuracy of favored diagnoses was 70% for COVID-19 pneumonia and 68% for both influenza and OP. CONCLUSION. CT findings of COVID-19 substantially overlap with those of influenza and, to a greater extent, those of OP. The diagnostic accuracy of the radiologists was low in a study sample that contained equal proportions of these three types of pneumonia. CLINICAL IMPACT. Recognized challenges in diagnosing COVID-19 by CT are furthered by the strong overlap observed between the appearances of COVID-19 and OP on CT. This challenge may be particularly evident in clinical settings in which there are substantial proportions of patients with potential causes of OP such as ongoing cancer therapy or autoimmune conditions.

PET/MRI assessment of lung nodules in primary abdominal malignancies: sensitivity and outcome analysis.

PURPOSE: To evaluate PET/MR lung nodule detection compared to PET/CT or CT, to determine growth of nodules missed by PET/MR, and to investigate the impact of missed nodules on clinical management in primary abdominal malignancies. METHODS: This retrospective IRB-approved study included [18F]-FDG PET/MR in 126 patients. All had standard of care chest imaging (SCI) with diagnostic chest CT or PET/CT within 6 weeks of PET/MR that served as standard of reference. Two radiologists assessed lung nodules (size, location, consistency, position, and [18F]-FDG avidity) on SCI and PET/MR. A side-by-side analysis of nodules on SCI and PET/MR was performed. The nodules missed on PET/MR were assessed on follow-up SCI to ascertain their growth (≥ 2 mm); their impact on management was also investigated. RESULTS: A total of 505 nodules (mean 4 mm, range 1-23 mm) were detected by SCI in 89/126 patients (66M:60F, mean age 60 years). PET/MR detected 61 nodules for a sensitivity of 28.1% for patient and 12.1% for nodule, with higher sensitivity for > 7 mm nodules (< 30% and > 70% respectively, p < 0.05). 75/337 (22.3%) of the nodules missed on PET/MR (follow-up mean 736 days) demonstrated growth. In patients positive for nodules at SCI and negative at PET/MR, missed nodules did not influence patients' management. CONCLUSIONS: Sensitivity of lung nodule detection on PET/MR is affected by nodule size and is lower than SCI. 22.3% of missed nodules increased on follow-up likely representing metastases. Although this did not impact clinical management in study group with primary abdominal malignancy, largely composed of extra-thoracic advanced stage cancers, with possible different implications in patients without extra-thoracic spread.

Management and Outcomes of Suspected Infectious and Inflammatory Lung Abnormalities Identified on Lung Cancer Screening CT.

BACKGROUND. Incidental findings are frequently encountered during lung cancer screening (LCS). Limited data describe the prevalence of suspected acute infectious and inflammatory lung processes on LCS and how they should be managed. OBJECTIVE. The purpose of this study was to determine the prevalence, radiologic reporting and management, and outcome of suspected infectious and inflammatory lung processes identified incidentally during LCS and to propose a management algorithm. METHODS. This retrospective study included 6314 low-dose CT (LDCT) examinations performed between June 2014 and April 2019 in 3800 patients as part of an established LCS program. Radiology reports were reviewed, and patients with potentially infectious or inflammatory lung abnormalities were identified and analyzed for descriptors of imaging findings, Lung-RADS designation, recommendations, and clinical outcomes. Using the descriptors, outcomes, and a greater than 2% threshold risk of malignancy, a follow-up algorithm was developed to decrease additional imaging without affecting cancer detection. RESULTS. A total of 331/3800 (8.7%) patients (178 men, 153 women; mean age [range], 66 [53-87] years) undergoing LCS had lung findings that were attributed to infection or inflammation. These abnormalities were reported as potentially significant findings using the S modifier in 149/331 (45.0%) and as the dominant nodule used to determine the Lung-RADS category in 96/331 (29.0%). Abnormalities were multiple or multifocal in 260/331 (78.5%). Common descriptors were ground-glass (155/331; 46.8%), tree-in-bud (56/331; 16.9%), consolidation (41/331; 12.4%), and clustered (67/331; 20.2%) opacities. A follow-up chest CT outside of screening was performed within 12 months or less in 264/331 (79.8%) and within 6 months or less in 186/331 (56.2%). A total of 260/331 (78.5%) opacities resolved on follow-up imaging. Two malignancies (2/331; 0.6%) were associated with these abnormalities and both had consolidations. Theoretic adoption of a proposed management algorithm for suspected infectious and inflammatory findings reduced unnecessary follow-up imaging by 82.6% without missing a single malignancy. CONCLUSION. Presumed acute infectious or inflammatory lung abnormalities are frequently encountered in the setting of LCS. These opacities are commonly multifocal and resolve on follow-up. Less than 1% are associated with malignancy. CLINICAL IMPACT. Adoption of a conservative management algorithm can standardize recommendations and reduce unnecessary imaging without increasing the risk of missing a malignancy.

Low contrast volume dual-energy CT of the chest: Quantitative and qualitative assessment.

PURPOSE: To evaluate the image quality of chest CT performed on dual-energy scanners using low contrast volume for routine chest (DECT-R) and pulmonary angiography (DECTPA) protocols. MATERIALS AND METHODS: This retrospective study included dual-energy CT scans of chest performed with low contrast volume in 84 adults (34M:50F; Age 69 ± 16 years: Weight 71 ± 16kg). There were 42 patients with DECT-R and 42 patients with DECT-PA protocols. Images were reviewed by two thoracic radiologists. Qualitative assessment was done on a four-point scale, for subjective assessment of contrast enhancement and artifacts (1 = Excellent, 2 = optimal, 3 = suboptimal, and 4 = Limited) in the pulmonary arteries and thoracic aorta, on virtual monoenergetic and material decomposition iodine (MDI) images. Quantitative assessment was performed by measuring the CT (Hounsfield) units in aorta and pulmonary arteries. The estimated glomerular filtration rate (eGFR) was calculated before and after CT scans. Two tailed student's t-test was performed to assess the significance of findings, and strength of correlation between readers was determined by Cohen's kappa test. RESULTS: DECT-PA and DECT-R demonstrated excellent/adequate contrast density within the pulmonary arteries (up to segmental branch), and aorta. There was no suboptimal or limited examination. There was strong interobserver agreement for arterial enhancement in pulmonary arteries (kappa = 0.62-0.89) and for thoracic aorta (kappa = 0.62-0.94). Pulmonary emboli were seen in 3/42(7%) in DECT-R and in 5/42(12%) in DECT-PA. There was no significant change in eGFR before and after IV contrast injection (p = 0.46-0.52). CONCLUSION: DECT-R and DECT-PA performed with low contrast volume provide diagnostic quality opacification of the pulmonary vessels and aorta vessels.

Clinical and Imaging Features of Non-Small-Cell Lung Cancer in Young Patients.

BACKGROUND: Non-small-cell lung cancer (NSCLC) in young adult patients is rare, with scarce data available in patients aged < 40 years and even less in those aged < 35 years. Our goal was to determine the presenting symptoms, clinicopathologic characteristics, and imaging features of young patients with NSCLC at time of diagnosis and compare them to those of older adults. PATIENTS AND METHODS: We retrospectively analyzed the medical records and imaging of young patients (≤ 40 years old) with NSCLC treated at our institution between 1998 and 2018. Patients < 35 years old were compared to those between 35 and 40 years old. Characteristics of patients ≤ 40 years old were compared to older patients (> 40 years) from publicly available data sets. RESULTS: We identified 166 young patients with NSCLC (median age, 36.6 years; range, 18-40 years). Most presented with nonspecific respiratory symptoms and were diagnosed with pneumonia (84/136, 62%). Compared to patients < 35 years old, patients 35-40 years old were more likely to have malignancy detected incidentally (15% vs. 5%, P = .04). Patients < 35 years old were more likely to have central tumors (55% vs. 33%, P = .02) and to have bone (38% vs. 19%, P = .007) and lung (39% vs. 24%, P = .03) metastases. Compared to older patients (> 40 years), young patients were more likely to be never smokers (65.0% vs. 14.7%, P < .001) and to have advanced disease (88% vs. 66%, P < .001). CONCLUSION: Young patients with NSCLC often present with nonspecific symptoms and have advanced disease at diagnosis, often mimicking other pathologies. Awareness of the clinical presentation and imaging features of NSCLC in young patients may help minimize delays in diagnoses.

Detection of Extrapulmonary Malignancy During Lung Cancer Screening: 5-Year Analysis at a Tertiary Hospital.

PURPOSE: The aims of this study were to determine the prevalence and outcomes of extrapulmonary malignancies identified on lung cancer screening (LCS) and to determine the cost associated with the investigation of these lesions. METHODS: This retrospective study included 7,414 low-dose CT studies performed between June 2014 and December 2019 on 4,160 patients as part of an established LCS program. Patients with indeterminate extrapulmonary lesions were identified, and the diagnostic workup, management, and outcomes of the lesions were determined. Costs related to diagnostic evaluation were estimated using 2020 total facility relative value units and the 2020 Medicare conversion factor. Out-of-pocket costs were extracted from billing records. RESULTS: There were 20 extrapulmonary malignancies among 241 reported lesions in 225 patients (mean age, 66.1 ± 6.4 years; 109 men, 116 women). The prevalence of extrapulmonary malignancy was 20 of 4,160 (0.48%). Early-stage cancers were detected in 13 of 20 (65%). No cancer-specific mortality was observed. The predictive value for malignancy varied by organ (P = .03) and was highest in the chest wall and axilla (36.4%), followed by bone (25%). The average cost on the basis of Medicare reimbursement for diagnosis of an extrapulmonary malignancy on LCS was $1,316.03 ($6.33 per participant and $109.21 per indeterminate incidental lesion). Most patients (203 of 225 [90.2%]) did not have out-of-pocket costs related to diagnostic workup. In those who did, the median cost was $160.60 (range, $75-$606.76). CONCLUSIONS: Low-dose CT for LCS detects extrapulmonary malignancy with high predictive value for certain locations. There is cost associated in the workup related to these incidental lesions, but most malignancies are detected at early stages and have good outcomes.

Clinical and imaging features predict mortality in COVID-19 infection in Iran.

The new coronavirus disease 2019 (COVID-19) pandemic has challenged many healthcare systems around the world. While most of the current understanding of the clinical features of COVID-19 is derived from Chinese studies, there is a relative paucity of reports from the remaining global health community. In this study, we analyze the clinical and radiologic factors that correlate with mortality odds in COVID-19 positive patients from a tertiary care center in Tehran, Iran. A retrospective cohort study of 90 patients with reverse transcriptase-polymerase chain reaction (RT-PCR) positive COVID-19 infection was conducted, analyzing demographics, co-morbidities, presenting symptoms, vital signs, laboratory values, chest radiograph findings, and chest CT features based on mortality. Chest radiograph was assessed using the Radiographic Assessment of Lung Edema (RALE) scoring system. Chest CTs were assessed according to the opacification pattern, distribution, and standardized severity score. Initial and follow-up Chest CTs were compared if available. Multiple logistic regression was used to generate a prediction model for mortality. The 90 patients included 59 men and 31 women (59.4 ± 16.6 years), including 21 deceased and 69 surviving patients. Among clinical features, advanced age (p = 0.02), low oxygenation saturation (p<0.001), leukocytosis (p = 0.02), low lymphocyte fraction (p = 0.03), and low platelet count (p = 0.048) were associated with increased mortality. High RALE score on initial chest radiograph (p = 0.002), presence of pleural effusions on initial CT chest (p = 0.005), development of pleural effusions on follow-up CT chest (p = 0.04), and worsening lung severity score on follow-up CT Chest (p = 0.03) were associated with mortality. A two-factor logistic model using patient age and oxygen saturation was created, which demonstrates 89% accuracy and area under the ROC curve of 0.86 (p<0.0001). Specific demographic, clinical, and imaging features are associated with increased mortality in COVID-19 infections. Attention to these features can help optimize patient management.

Radiomic features of primary tumor by lung cancer stage: analysis in BRAF mutated non-small cell lung cancer.

BACKGROUND: The clinical features and traditional semantic imaging characteristics of BRAF-mutated non-small cell lung cancer (NSCLC) have been previously reported. The radiomic features of BRAF-mutated NSCLC and their role in predicting cancer stage, however, have yet to be investigated. This study's goal is to assess the differences in CT radiomic features of primary NSCLC driven by BRAF mutation and stratified by tumor-node-metastasis (TNM) staging. METHODS: Our IRB approved study included 62 patients with BRAF mutations (V600 in 27 and non-V600 in 35 patients), who underwent contrast-enhanced chest CT. Tumor stage was determined based on the 8th edition of TNM staging. Two thoracic radiologists assessed the primary tumor imaging features such, including tumor size (maximum and minimum dimensions) and density (Hounsfield units, HU). De-identified transverse CT images (DICOM) were processed with 3D slicer (Version 4.7) for manual lesion segmentation and estimation of radiomic features. Descriptive statistics, multivariate logistic regression, and receiver operating characteristics (ROC) were performed. RESULTS: There were significant differences in the radiomic features based on cancer stages I-IV with the most significant differences between stage IV and stage I lesions [AUC 0.94 (95% CI: 0.86-0.99), P<0.04]. There were also significant differences in radiomic features between stage IV and combined stages I-III [40/113 radiomic features; AUC 0.71 (95% CI: 0.59-0.85); P<0.04-0.0001]. None of the clinical (0/6) or imaging (0/3) features were significantly different between stage IV and combined stages I-III. CONCLUSIONS: The radiomic features of primary tumor in BRAF driven NSCLC significantly vary with cancer stage, independent of standard imaging and clinical features.

Association between circulating tumor DNA burden and disease burden in patients with ALK-positive lung cancer.

BACKGROUND: Plasma genotyping is an emerging approach for the identification of genetic alterations mediating resistance to anaplastic lymphoma kinase (ALK)-targeted therapy. The authors reviewed plasma genotyping and imaging findings to assess the correlation between circulating tumor DNA (ctDNA) burden and disease burden in patients with ALK-positive lung cancer. METHODS: The authors analyzed 97 plasma specimens from 75 patients with ALK-positive lung cancer to identify ALK and non-ALK alterations. Disease burden was estimated by tabulating lesions per organ and calculating lesion diameters, areas, and volumes. Disease burden was correlated with the allelic frequency (AF) of plasma alterations. RESULTS: The mean interval between plasma collection and imaging was 8 days. ctDNA was detected in approximately 85% of plasma specimens. An ALK fusion and ALK mutation were detected in 79% and 76%, respectively, of plasma specimens. Using the maximum plasma alteration AF and maximum ALK alteration AF as independent surrogates of ctDNA burden, a higher disease burden measurement on imaging was found to be associated with higher ctDNA burden. Total body and extrathoracic tumor volume but not intrathoracic tumor volume correlated with ctDNA burden. Of all the disease sites assessed, the ctDNA burden correlated most with involvement of the liver, bones, and adrenal glands. Despite being the defining alteration in ALK-positive lung cancer, isolated plasma ALK fusion AF did not perform as well as the maximum plasma alteration AF or maximum ALK alteration AF for correlating tumor burden. CONCLUSIONS: In patients with ALK-positive lung cancer, the maximum plasma alteration AF and maximum ALK alteration AF correlate with the extrathoracic burden of disease and are more predictive of tumor burden compared with the ALK fusion AF alone. LAY SUMMARY: Analysis of genetic material shed from cancer cells into the circulation offers insights into the molecular composition of tumors. The circulating tumor DNA (ctDNA) varies over time and across individuals and is impacted by the distribution of disease. Herein, the authors estimated tumor burden on imaging and correlated it with ctDNA by calculating the maximum allelic frequency. The current study findings demonstrated that the greatest correlation exists between extrathoracic, extracranial tumor burden (particularly involvement of the liver, adrenal glands, or bones) and ctDNA burden, suggesting a biological basis for the interpatient and temporal intrapatient differences in ctDNA yield that have been described in previous studies.

Clinicopathologic and Imaging Features of Non-Small-Cell Lung Cancer with MET Exon 14 Skipping Mutations.

MET exon 14 (METex14) skipping mutations are an emerging potentially targetable oncogenic driver mutation in non-small-cell lung cancer (NSCLC). The imaging features and patterns of metastasis of NSCLC with primary METex14 skipping mutations (METex14-mutated NSCLC) are not well described. Our goal was to determine the clinicopathologic and imaging features that may suggest the presence of METex14 skipping mutations in NSCLC. This IRB-approved retrospective study included NSCLC patients with primary METex14 skipping mutations and pre-treatment imaging data between January 2013 and December 2018. The clinicopathologic characteristics were extracted from electronic medical records. The imaging features of the primary tumor and metastases were analyzed by two thoracic radiologists. In total, 84 patients with METex14-mutated NSCLC (mean age = 71.4 ± 10 years; F = 52, 61.9%, M = 32, 38.1%; smokers = 47, 56.0%, nonsmokers = 37, 44.0%) were included in the study. Most tumors were adenocarcinoma (72; 85.7%) and presented as masses (53/84; 63.1%) that were peripheral in location (62/84; 73.8%). More than one in five cancers were multifocal (19/84; 22.6%). Most patients with metastatic disease had only extrathoracic metastases (23/34; 67.6%). Fewer patients had both extrathoracic and intrathoracic metastases (10/34; 29.4%), and one patient had only intrathoracic metastases (1/34, 2.9%). The most common metastatic sites were the bones (14/34; 41.2%), the brain (7/34; 20.6%), and the adrenal glands (7/34; 20.6%). Four of the 34 patients (11.8%) had metastases only at a single site. METex14-mutated NSCLC has distinct clinicopathologic and radiologic features.