Differentiation of intrathoracic lymph node histopathology by volumetric dual energy CT radiomic analysis.

PURPOSE: To determine the performance of volumetric dual energy low kV and iodine radiomic features for the differentiation of intrathoracic lymph node histopathology, and influence of contrast protocol. MATERIALS AND METHODS: Intrathoracic lymph nodes with histopathologic correlation (neoplastic, granulomatous sarcoid, benign) within 90 days of DECT chest imaging were volumetrically segmented. 1691 volumetric radiomic features were extracted from iodine maps and low-kV images, totaling 3382 features. Univariate analysis was performed using 2-sample t-test and filtered for false discoveries. Multivariable analysis was used to compute AUCs for lymph node classification tasks. RESULTS: 129 lymph nodes from 72 individuals (mean age 61 ± 15 years) were included, 52 neoplastic, 51 benign, and 26 granulomatous-sarcoid. Among all contrast enhanced DECT protocol exams (routine, PE and CTA), univariable analysis demonstrated no significant differences in iodine and low kV features between neoplastic and non-neoplastic lymph nodes; in the subset of neoplastic versus benign lymph nodes with routine DECT protocol, 199 features differed (p = .01- < 0.05). Multivariable analysis using both iodine and low kV features yielded AUCs >0.8 for differentiating neoplastic from non-neoplastic lymph nodes (AUC 0.86), including subsets of neoplastic from granulomatous (AUC 0.86) and neoplastic from benign (AUC 0.9) lymph nodes, among all contrast protocols. CONCLUSIONS: Volumetric DECT radiomic features demonstrate strong collective performance in differentiation of neoplastic from non-neoplastic intrathoracic lymph nodes, and are influenced by contrast protocol.

Diseases Involving the Lung Peribronchovascular Region: A CT Imaging Pathologic Classification.

TOPIC IMPORTANCE: Chest CT imaging holds a major role in the diagnosis of lung diseases, many of which affect the peribronchovascular region. Identification and categorization of peribronchovascular abnormalities on CT imaging can assist in formulating a differential diagnosis and directing further diagnostic evaluation. REVIEW FINDINGS: The peribronchovascular region of the lung encompasses the pulmonary arteries, airways, and lung interstitium. Understanding disease processes associated with structures of the peribronchovascular region and their appearances on CT imaging aids in prompt diagnosis. This article reviews current knowledge in anatomic and pathologic features of the lung interstitium composed of intercommunicating prelymphatic spaces, lymphatics, collagen bundles, lymph nodes, and bronchial arteries; diffuse lung diseases that present in a peribronchovascular distribution; and an approach to classifying diseases according to patterns of imaging presentations. Lung peribronchovascular diseases can appear on CT imaging as diffuse thickening, fibrosis, masses or masslike consolidation, ground-glass or air space consolidation, and cysts, acknowledging that some diseases may have multiple presentations. SUMMARY: A category approach to peribronchovascular diseases on CT imaging can be integrated with clinical features as part of a multidisciplinary approach for disease diagnosis.

Radiation Therapy for Lung Cancer: Imaging Appearances and Pitfalls.

Radiation therapy is part of a multimodality treatment approach to lung cancer. The radiologist must be aware of both the expected and the unexpected imaging findings of the post-radiation therapy patient, including the time course for development of post- radiation therapy pneumonitis and fibrosis. In this review, a brief discussion of radiation therapy techniques and indications is presented, followed by an image-heavy differential diagnostic approach. The review focuses on computed tomography imaging examples to help distinguish normal postradiation pneumonitis and fibrosis from alternative complications, such as infection, local recurrence, or radiation-induced malignancy.

Incidental Apical Pleuroparenchymal Scarring on Computed Tomography: Diagnostic Yield, Progression, Morphologic Features and Clinical Significance.

PURPOSE: Apical pleuroparenchymal scarring (APPS) is commonly seen on chest computed tomography (CT), though the imaging and clinical features, to the best of our knowledge, have never been studied. The purpose was to understand APPS's typical morphologic appearance and associated clinical features. PATIENTS AND METHODS: A random generator selected 1000 adult patients from all 21516 chest CTs performed at urban outpatient centers from January 1, 2016 to December 31, 2016. Patients with obscuring apical diseases were excluded to eliminate confounding factors. After exclusions, 780 patients (median age: 64 y; interquartile range: 56 to 72 y; 55% males) were included for analysis. Two radiologists evaluated the lung apices of each CT for the extent of abnormality in the axial plane (mild: <5 mm, moderate: 5 to 10 mm, severe: >10 mm), craniocaudal plane (extension halfway to the aortic arch, more than halfway, vs below the arch), the predominant pattern (nodular vs reticular and symmetry), and progression. Cohen kappa coefficient was used to assess radiologists' agreement in scoring. Ordinal logistic regression was used to determine associations of clinical and imaging variables with APPS. RESULTS: APPS was present on 65% (507/780) of chest CTs (54% mild axial; 80% mild craniocaudal). The predominant pattern was nodular and symmetric. Greater age, female sex, lower body mass index, greater height, and white race were associated with more extensive APPS. APPS was not found to be associated with lung cancer in this cohort. CONCLUSION: Classifying APPS by the extent of disease in the axial or craniocaudal planes, in addition to the predominant pattern, enabled statistically significant associations to be determined, which may aid in understanding the pathophysiology of apical scarring and potential associated risks.

ACR Appropriateness Criteria® Incidentally Detected Indeterminate Pulmonary Nodule.

Incidental pulmonary nodules are common. Although the majority are benign, most are indeterminate for malignancy when first encountered making their management challenging. CT remains the primary imaging modality to first characterize and follow-up incidental lung nodules. This document reviews available literature on various imaging modalities and summarizes management of indeterminate pulmonary nodules detected incidentally. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Prevalence of Adenopathy at Chest Computed Tomography After Vaccination for Severe Acute Respiratory Syndrome Coronavirus 2.

OBJECTIVE: This study aimed to determine the prevalence of axillary and subpectoral (SP) lymph nodes after ipsilateral COVID-19 vaccine administration on chest computed tomography (CT). METHODS: Subjects with chest CTs between 2 and 25 days after a first or second vaccine dose, December 15, 2020, to February 12, 2021, were included. Orthogonal measures of the largest axillary and SP nodes were recorded by 2 readers blinded to vaccine administration and clinical details. A mean nodal diameter discrepancy of ≥6 mm between contralateral stations was considered positive for asymmetry. Correlation with the side of vaccination, using a Spearman rank correlation, was performed on the full cohort and after excluding patients with diseases associated with adenopathy. RESULTS: Of the 138 subjects (81 women, 57 men; mean [SD] age, 74.4 ± 11.7 years), 48 (35%) had asymmetrically enlarged axillary and/or SP lymph nodes, 42 (30%) had ipsilateral, and 6 (4%) had contralateral to vaccination ( P = 0.003). Exclusion of 29 subjects with conditions associated with adenopathy showed almost identical correlation, with asymmetric nodes in 32 of 109 (29%) ipsilateral and in 5 of 109 (5%) contralateral to vaccination ( P = 0.002). CONCLUSIONS: Axillary and/or SP lymph nodes ipsilateral to vaccine administration represents a clinical conundrum. Asymmetric nodes were detected at CT in 30% of subjects overall and 29% of subjects without conditions associated with adenopathy, approximately double the prevalence rate reported to the Centers for Disease Control and Prevention by vaccine manufacturers. When interpreting examinations correlation with vaccine administration timing and site is important for pragmatic management.

Combined whole-lesion radiomic and iodine analysis for differentiation of pulmonary tumors.

Quantitative radiomic and iodine imaging features have been explored for diagnosis and characterization of tumors. In this work, we invistigate combined whole-lesion radiomic and iodine analysis for the differentiation of pulmonary tumors on contrast-enhanced dual-energy CT (DECT) chest images. 100 biopsy-proven solid lung lesions on contrast-enhanced DECT chest exams within 3 months of histopathologic sampling were identified. Lesions were volumetrically segmented using open-source software. Lesion segmentations and iodine density volumes were loaded into a radiomics prototype for quantitative analysis. Univariate analysis was performed to determine differences in volumetric iodine concentration (mean, median, maximum, minimum, 10th percentile, 90th percentile) and first and higher order radiomic features (n = 1212) between pulmonary tumors. Analyses were performed using a 2-sample t test, and filtered for false discoveries using Benjamini-Hochberg method. 100 individuals (mean age 65 ± 13 years; 59 women) with 64 primary and 36 metastatic lung lesions were included. Only one iodine concentration parameter, absolute minimum iodine, significantly differed between primary and metastatic pulmonary tumors (FDR-adjusted p = 0.015, AUC 0.69). 310 (FDR-adjusted p = 0.0008 to p = 0.0491) radiomic features differed between primary and metastatic lung tumors. Of these, 21 features achieved AUC ≥ 0.75. In subset analyses of lesions imaged by non-CTPA protocol (n = 72), 191 features significantly differed between primary and metastatic tumors, 19 of which achieved AUC ≥ 0.75. In subset analysis of tumors without history of prior treatment (n = 59), 40 features significantly differed between primary and metastatic tumors, 11 of which achieved AUC ≥ 0.75. Volumetric radiomic analysis provides differentiating capability beyond iodine quantification. While a high number of radiomic features differentiated primary versus metastatic pulmonary tumors, fewer features demonstrated good individual discriminatory utility.

Solitary Pulmonary Nodule Evaluation: Pearls and Pitfalls.

Lung nodules are frequently encountered while interpreting chest CTs and are challenging to detect, characterize, and manage given they can represent both benign or malignant etiologies. An understanding of features associated with malignancy and causes of interpretive pitfalls is helpful to avoid misdiagnoses. This review addresses pertinent topics related to the etiologies for missed lung nodules on radiography and CT. Additionally, CT imaging technical pitfalls and challenges in addition to issues in the evaluation of nodule morphology, attenuation, and size will be discussed. Nodule management guidelines will be addressed as well as recent investigations that further our understanding of lung nodules.

Inter-Reader Variability of Volumetric Subsolid Pulmonary Nodule Radiomic Features.

OBJECTIVE: To evaluate the inter-observer consistency for subsolid pulmonary nodule radiomic features. MATERIALS AND METHODS: Subsolid nodules were selected by reviewing radiology reports of CT examinations performed December 1, 2015 to April 1, 2016. Patients with CTs at two time points were included in this study. There were 55 patients with subsolid nodules, of whom 14 had two nodules. Of 69 subsolid nodules, 66 were persistent at the second time point, yielding 135 lesions for segmentation. Two thoracic radiologists and an imaging fellow segmented the lesions using a semi-automated volumetry algorithm (Syngo.via Vb20, Siemens). Coefficient of variation (CV) was used to assess consistency of 91 quantitative measures extracted from the subsolid nodule segmentations, including first and higher order texture features. The accuracy of segmentation was visually graded by an experienced thoracic radiologist. Influencing factors on radiomic feature consistency and segmentation accuracy were assessed using generalized estimating equation analyses and the Exact Mann-Whitney test. RESULTS: Mean patient age was 71 (38-93 years), with 39 women and 16 men. Mean nodule volume was 1.39mL, range .03-48.2mL, for 135 nodules. Several radiomic features showed high inter-reader consistency (CV<5%), including entropy, uniformity, sphericity, and spherical disproportion. Descriptors such as surface area and energy had low consistency across inter-reader segmentations (CV>10%). Nodule percent solid component and attenuation influenced inter-reader variability of some radiomic features. The presence of contrast did not significantly affect the consistency of subsolid nodule radiomic features. Near perfect segmentation, within 5% of actual nodule size, was achieved in 68% of segmentations, and very good segmentation, within 25% of actual nodule size, in 94%. Morphologic features including nodule margin and shape (each p <0.01), and presence of air bronchograms (p = 0.004), bubble lucencies (p = 0.02) and broad pleural contact (p < 0.01) significantly affected the probability of near perfect segmentation. Stroke angle (p = 0.001) and length (p < 0.001) also significantly influenced probability of near perfect segmentation. CONCLUSIONS: The inter-observer consistency of radiomic features for subsolid pulmonary nodules varies, with high consistency for several features, including sphericity, spherical disproportion, and first and higher order entropy, and normalized non-uniformity. Nodule morphology influences the consistency of subsolid nodule radiomic features, and the accuracy of subsolid nodule segmentation.

Managing Incidental Findings on Thoracic CT: Lung Findings. A White Paper of the ACR Incidental Findings Committee.

The ACR Incidental Findings Committee presents recommendations for managing incidentally detected lung findings on thoracic CT. The Chest Subcommittee is composed of thoracic radiologists who endorsed and developed the provided guidance. These recommendations represent a combination of current published evidence and expert opinion and were finalized by informal iterative consensus. The recommendations address commonly encountered incidental findings in the lungs and are not intended to be a comprehensive review of all pulmonary incidental findings. The goal is to improve the quality of care by providing guidance on management of incidentally detected thoracic findings.

Incidental Lung Nodules on Cross-sectional Imaging: Current Reporting and Management.

Pulmonary nodules are the most common incidental finding in the chest, particularly on computed tomographs that include a portion or all of the chest, and may be encountered more frequently with increasing utilization of cross-sectional imaging. Established guidelines address the reporting and management of incidental pulmonary nodules, both solid and subsolid, synthesizing nodule and patient features to distinguish benign nodules from those of potential clinical consequence. Standard nodule assessment is essential for the accurate reporting of nodule size, attenuation, and morphology, all features with varying risk implications and thus management recommendations.

Shades of Gray: Subsolid Nodule Considerations and Management.

Subsolid nodules are common on chest CT imaging and may be either benign or malignant. Their varied features and broad differential diagnoses present management challenges. Although subsolid nodules often represent lung adenocarcinomas, other possibilities are common and influence management. Practice guidelines exist for subsolid nodule management for both incidentally and screening-detected nodules, incorporating patient and nodule characteristics. This review highlights the similarities and differences among these algorithms, with the intent of providing a resource for comparison and aid in choosing management options.

Radiologic and pathologic correlation of anterior mediastinal lesions.

Anterior mediastinal lesions while rare, are heterogeneous in etiology, with broad differential considerations that may be narrowed by drawing on discriminating clinical, radiologic, and histopathologic features. This manuscript will review the radiographic and pathologic correlation of anterior mediastinal lesions of thymic, lymphomatous, and germ-cell origin.

Distribution of Mediastinal Lesions Across Multi-Institutional, International, Radiology Databases.

INTRODUCTION: Mediastinal lesions are uncommon; studies on their distribution are, in general, small and from a single institution. Furthermore, these studies are usually based on pathology or surgical databases and, therefore, miss many lesions that did not undergo biopsy or resection. Our aim was to identify the distribution of lesions in the mediastinum in a large international, multi-institutional cohort. METHODS: At each participating institution, a standardized retrospective radiology database search was performed for interpretations of computed tomography, positron emission tomography-computed tomography, and magnetic resonance imaging scans including any of the following terms: "mediastinal nodule," "mediastinal lesion," "mediastinal mass," or "mediastinal abnormality" (2011-2014). Standardized data were collected. Statistical analysis was performed. RESULTS: Among 3308 cases, thymomas (27.8%), benign mediastinal cysts (20.0%), and lymphomas (16.1%) were most common. The distribution of lesions varied among mediastinal compartments; thymomas (38.3%), benign cysts (16.8%), and neurogenic tumors (53.9%) were the most common lesions in the prevascular, visceral, and paravertebral mediastinum, respectively (p < 0.001). Mediastinal compartment was associated with age; patients with paravertebral lesions were the youngest (p < 0.0001). Mediastinal lesions differed by continent or country, with benign cysts being the most common mediastinal lesions in the People's Republic of China, thymomas in Europe, and lymphomas in North America and Israel (p < 0.001). Benign cysts, thymic carcinomas, and metastases were more often seen in larger hospitals, whereas lymphomas and thymic hyperplasia occurred more often in smaller hospitals (p < 0.01). CONCLUSIONS: Our study confirmed that the spectrum and frequency of mediastinal lesions depend on mediastinal compartment and age. This information provides helpful demographic data and is important when considering the differential diagnosis of a mediastinal lesion.

Approach to Peribronchovascular Disease on CT.

Diseases that are predominantly peribronchovascular in distribution on computed tomography by definition involve the bronchi, adjacent vasculature, and associated lymphatics involving the central or axial lung interstitium. An understanding of diseases that can present with focal peribronchovascular findings is useful for establishing diagnoses and guiding patient management. This review will cover clinical and imaging features that may assist in differentiating amongst the various causes of primarily peribronchovascular disease.

Spectrum of Lung Adenocarcinoma.

Lung cancer remains the most common cause of cancer death in the United States of America and worldwide despite continued advances in lung cancer screening as well as surgical, medical, and radiation oncological treatments. Adenocarcinoma is the most common histological subtype of primary lung cancer and has recently been reorganized into a spectrum ranging from preinvasive lesions to invasive adenocarcinoma. An understanding of the pathology, diagnosis, and management of the spectrum of lung adenocarcinoma is more important than ever, considering the central role of the radiologist. The aim of this review is to describe the subtypes of the lung adenocarcinoma spectrum in terms of histological and imaging features, their pattern of growth on imaging, management, staging, and evolving knowledge of tumor genetics.

Management of Incidental Lung Nodules.

The incidental pulmonary nodule is commonly encountered when interpreting chest CTs. The management of pulmonary nodules requires a multidisciplinary approach entailing integration of nodule size and features, clinical risk factors, and patient preference and comorbidities. Guidelines have been issued for the management of both solid and subsolid nodules, with the Fleischner Society issuing revised guidelines in 2017. This article focuses on the CT imaging characteristics and clinical behavior of pulmonary nodules, with review of the current management guidelines that reflect this knowledge.

Management of Incidental Lung Nodules: Current Strategy and Rationale.

Incidentally detected lung nodules are increasingly common in routine diagnostic computed tomography (CT) imaging. Formal management recommendations for incidental nodules, such as those outlined by the Fleischner Society, must therefore reflect a balance of malignancy risk and the clinical context in which nodules are discovered. Nodule size, attenuation, morphology, and location all influence the likelihood of malignancy and, thus, the necessity and timing of follow-up according to current Fleischner recommendations. As technological advancements in CT imaging continue, there may be greater reliance on advanced computerized analysis of lung nodule features to help determine the risk of clinically significant disease.

Lepidic Predominant Pulmonary Lesions (LPL): CT-based Distinction From More Invasive Adenocarcinomas Using 3D Volumetric Density and First-order CT Texture Analysis.

RATIONALE AND OBJECTIVES: This study aimed to differentiate pathologically defined lepidic predominant lesions (LPL) from more invasive adenocarcinomas (INV) using three-dimensional (3D) volumetric density and first-order texture histogram analysis of surgically excised stage 1 lung adenocarcinomas. MATERIALS AND METHODS: This retrospective study was institutional review board approved and Health Insurance Portability and Accountability Act compliant. Sixty-four cases of pathologically proven stage 1 lung adenocarcinoma surgically resected between September 2006 and October 2015, including LPL (n = 43) and INV (n = 21), were evaluated using high-resolution computed tomography. Quantitative measurements included nodule volume, percent solid volume (% solid), and first-order texture histogram analysis including skewness, kurtosis, entropy, and mean nodule attenuation within each histogram quartile. Binomial logistic regression models were used to identify the best set of parameters distinguishing LPL from INV. RESULTS: Univariate analysis of 3D volumetric density and histogram features was statistically significant between LPL and INV groups (P < .05). Accuracy of a binomial logistic model to discriminate LPL from INV based on size and % solid was 85.9%. With optimized probability cutoff, the model achieves 81% sensitivity, 76.7% specificity, and area under the receiver operating characteristic curve of 0.897 (95% confidence interval, 0.821-0.973). An additional model based on size and mean nodule attenuation of the third quartile (Hu_Q3) of the histogram achieved similar accuracy of 81.3% and area under the receiver operating characteristic curve of 0.877 (95% confidence interval, 0.790-0.964). CONCLUSIONS: Both 3D volumetric density and first-order texture analysis of stage 1 lung adenocarcinoma allow differentiation of LPL from more invasive adenocarcinoma with overall accuracy of 85.9%-81.3%, based on multivariate analyses of either size and % solid or size and Hu_Q3, respectively.