Searched for: person:koj03
in-biosketch:true
Low-field MRI lung opacity severity associated with decreased DLCO in post-acute Covid-19 patients
Azour, Lea; Segal, Leopoldo N; Condos, Rany; Moore, William H; Landini, Nicholas; Collazo, Destiny; Sterman, Daniel H; Young, Isabel; Ko, Jane; Brosnahan, Shari; Babb, James; Chandarana, Hersh
OBJECTIVES/OBJECTIVE:To evaluate the clinical significance of low-field MRI lung opacity severity. METHODS:Retrospective cross-sectional analysis of post-acute Covid-19 patients imaged with low-field MRI from 9/2020 through 9/2022, and within 1 month of pulmonary function tests (PFTs), 6-min walk test (6mWT), and symptom inventory (SI), and/or within 3 months of St. George Respiratory Questionnaire (SGRQ) was performed. Univariate and correlative analyses were performed with Wilcoxon, Chi-square, and Spearman tests. The association between disease and demographic factors and MR opacity severity, PFTs, 6mWT, SI, and SGRQ, and association between MR opacity severity with functional and patient-reported outcomes (PROs), was evaluated with mixed model analysis of variance, covariance and generalized estimating equations. Two-sided 5 % significance level was used, with Bonferroni multiple comparison correction. RESULTS:81 MRI exams in 62 post-acute Covid-19 patients (median age 57, IQR 41-64; 25 women) were included. Exams were a median of 8 months from initial illness. Univariate analysis showed lung opacity severity was associated with decreased %DLCO (ρ = -0.55, P = .0125), and lung opacity severity quartile was associated with decreased %DLCO, predicted TLC, FVC, and increased FEV1/FVC. Multivariable analysis adjusting for sex, initial disease severity, and interval from Covid-19 diagnosis showed MR lung opacity severity was associated with decreased %DLCO (P < .001). Lung opacity severity was not associated with PROs. CONCLUSION/CONCLUSIONS:Low-field MRI lung opacity severity correlated with decreased %DLCO in post-acute Covid-19 patients, but was not associated with PROs.
PMID: 39383681
ISSN: 1873-4499
CID: 5706142
Diseases Involving the Lung Peribronchovascular Region: A CT Imaging Pathologic Classification
Le, Linda; Narula, Navneet; Zhou, Fang; Smereka, Paul; Ordner, Jeffrey; Theise, Neil; Moore, William H; Girvin, Francis; Azour, Lea; Moreira, Andre L; Naidich, David P; Ko, Jane P
TOPIC IMPORTANCE/UNASSIGNED: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/RESULTS: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/CONCLUSIONS:A category approach to peribronchovascular diseases on CT imaging can be integrated with clinical features as part of a multidisciplinary approach for disease diagnosis.
PMID: 38909953
ISSN: 1931-3543
CID: 5706882
Thoracic Imaging [Editorial]
Ko, Jane P
PMID: 38816104
ISSN: 1557-8216
CID: 5663862
Radiation Therapy for Lung Cancer: Imaging Appearances and Pitfalls
Toussie, Danielle; Ginocchio, Luke A; Cooper, Benjamin T; Azour, Lea; Moore, William H; Villasana-Gomez, Geraldine; Ko, Jane P
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.
PMID: 38816092
ISSN: 1557-8216
CID: 5663852
Chest Intensive Care Unit Imaging: Pearls and Pitfalls
Villasana-Gomez, Geraldine; Toussie, Danielle; Kaufman, Brian; Stojanovska, Jadranka; Moore, William H; Azour, Lea; Traube, Leah; Ko, Jane P
Imaging plays a major role in the care of the intensive care unit (ICU) patients. An understanding of the monitoring devices is essential for the interpretation of imaging studies. An awareness of their expected locations aids in identifying complications in a timely manner. This review describes the imaging of ICU monitoring and support catheters, tubes, and pulmonary and cardiac devices, some more commonly encountered and others that have been introduced into clinical patient care more recently. Special focus will be placed on chest radiography and potential pitfalls encountered.
PMID: 38816084
ISSN: 1557-8216
CID: 5663832
Incidental Apical Pleuroparenchymal Scarring on Computed Tomography: Diagnostic Yield, Progression, Morphologic Features and Clinical Significance
Toussie, Danielle; Finkelstein, Mark; Mendoza, Dexter; Concepcion, Jose; Stojanovska, Jadranka; Azour, Lea; Ko, Jane P; Moore, William H; Singh, Ayushi; Sasson, Arielle; Bhattacharji, Priya; Eber, Corey
PURPOSE/OBJECTIVE: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/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/CONCLUSIONS: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.
PMID: 38798201
ISSN: 1536-0237
CID: 5663232
Photon-counting CT in Thoracic Imaging: Early Clinical Evidence and Incorporation Into Clinical Practice
Fletcher, Joel G; Inoue, Akitoshi; Bratt, Alex; Horst, Kelly K; Koo, Chi Wan; Rajiah, Prabhakar Shantha; Baffour, Francis I; Ko, Jane P; Remy-Jardin, Martine; McCollough, Cynthia H; Yu, Lifeng
Photon-counting CT (PCCT) is an emerging advanced CT technology that differs from conventional CT in its ability to directly convert incident x-ray photon energies into electrical signals. The detector design also permits substantial improvements in spatial resolution and radiation dose efficiency and allows for concurrent high-pitch and high-temporal-resolution multienergy imaging. This review summarizes (a) key differences in PCCT image acquisition and image reconstruction compared with conventional CT; (b) early evidence for the clinical benefit of PCCT for high-spatial-resolution diagnostic tasks in thoracic imaging, such as assessment of airway and parenchymal diseases, as well as benefits of high-pitch and multienergy scanning; (c) anticipated radiation dose reduction, depending on the diagnostic task, and increased utility for routine low-dose thoracic CT imaging; (d) adaptations for thoracic imaging in children; (e) potential for further quantitation of thoracic diseases; and (f) limitations and trade-offs. Moreover, important points for conducting and interpreting clinical studies examining the benefit of PCCT relative to conventional CT and integration of PCCT systems into multivendor, multispecialty radiology practices are discussed.
PMID: 38501953
ISSN: 1527-1315
CID: 5640382
ACR Appropriateness Criteria® Incidentally Detected Indeterminate Pulmonary Nodule
,; Martin, Maria D; Henry, Travis S; Berry, Mark F; Johnson, Geoffrey B; Kelly, Aine Marie; Ko, Jane P; Kuzniewski, Christopher T; Lee, Elizabeth; Maldonado, Fabien; Morris, Michael F; Munden, Reginald F; Raptis, Constantine A; Shim, Kyungran; Sirajuddin, Arlene; Small, William; Tong, Betty C; Wu, Carol C; Donnelly, Edwin F
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.
PMID: 38040464
ISSN: 1558-349x
CID: 5590512
Differentiating Imaging Features of Post-lobectomy Right Middle Lobe Torsion
Tamizuddin, Farah; Ocal, Selin; Toussie, Danielle; Azour, Lea; Wickstrom, Maj; Moore, William H; Kent, Amie; Babb, James; Fansiwala, Kush; Flagg, Eric; Ko, Jane P
PURPOSE/OBJECTIVE:The purpose of this study was to identify differences in imaging features between patients with confirmed right middle lobe (RML) torsion compared to those suspected yet without torsion. MATERIALS AND METHODS/METHODS:This retrospective study entailing a search of radiology reports from April 1, 2014, to April 15, 2021, resulted in 52 patients with suspected yet without lobar torsion and 4 with confirmed torsion, supplemented by 2 additional cases before the search period for a total of 6 confirmed cases. Four thoracic radiologists (1 an adjudicator) evaluated chest radiographs and computed tomography (CT) examinations, and Fisher exact and Mann-Whitney tests were used to identify any significant differences in imaging features (P<0.05). RESULTS:A reversed halo sign was more frequent for all readers (P=0.001) in confirmed RML torsion than patients without torsion (83.3% vs. 0% for 3 readers, one the adjudicator). The CT coronal bronchial angle between RML bronchus and bronchus intermedius was larger (P=0.035) in torsion (121.28 degrees) than nontorsion cases (98.26 degrees). Patients with torsion had a higher percentage of ground-glass opacity in the affected lobe (P=0.031). A convex fissure towards the adjacent lobe on CT (P=0.009) and increased lobe volume on CT (P=0.001) occurred more often in confirmed torsion. CONCLUSION/CONCLUSIONS:A reversed halo sign, larger CT coronal bronchial angle, greater proportion of ground-glass opacity, fissural convexity, and larger lobe volume on CT may aid in early recognition of the rare yet highly significant diagnosis of lobar torsion.
PMID: 37732714
ISSN: 1536-0237
CID: 5614062
Deep Learning Denoising of Low-Dose Computed Tomography Chest Images: A Quantitative and Qualitative Image Analysis
Azour, Lea; Hu, Yunan; Ko, Jane P; Chen, Baiyu; Knoll, Florian; Alpert, Jeffrey B; Brusca-Augello, Geraldine; Mason, Derek M; Wickstrom, Maj L; Kwon, Young Joon Fred; Babb, James; Liang, Zhengrong; Moore, William H
PURPOSE/OBJECTIVE:To assess deep learning denoised (DLD) computed tomography (CT) chest images at various low doses by both quantitative and qualitative perceptual image analysis. METHODS:Simulated noise was inserted into sinogram data from 32 chest CTs acquired at 100 mAs, generating anatomically registered images at 40, 20, 10, and 5 mAs. A DLD model was developed, with 23 scans selected for training, 5 for validation, and 4 for test.Quantitative analysis of perceptual image quality was assessed with Structural SIMilarity Index (SSIM) and Fréchet Inception Distance (FID). Four thoracic radiologists graded overall diagnostic image quality, image artifact, visibility of small structures, and lesion conspicuity. Noise-simulated and denoised image series were evaluated in comparison with one another, and in comparison with standard 100 mAs acquisition at the 4 mAs levels. Statistical tests were conducted at the 2-sided 5% significance level, with multiple comparison correction. RESULTS:At the same mAs levels, SSIM and FID between noise-simulated and reconstructed DLD images indicated that images were closer to a perfect match with increasing mAs (closer to 1 for SSIM, and 0 for FID).In comparing noise-simulated and DLD images to standard-dose 100-mAs images, DLD improved SSIM and FID. Deep learning denoising improved SSIM of 40-, 20-, 10-, and 5-mAs simulations in comparison with standard-dose 100-mAs images, with change in SSIM from 0.91 to 0.94, 0.87 to 0.93, 0.67 to 0.87, and 0.54 to 0.84, respectively. Deep learning denoising improved FID of 40-, 20-, 10-, and 5-mAs simulations in comparison with standard-dose 100-mAs images, with change in FID from 20 to 13, 46 to 21, 104 to 41, and 148 to 69, respectively.Qualitative image analysis showed no significant difference in lesion conspicuity between DLD images at any mAs in comparison with 100-mAs images. Deep learning denoising images at 10 and 5 mAs were rated lower for overall diagnostic image quality (P < 0.001), and at 5 mAs lower for overall image artifact and visibility of small structures (P = 0.002), in comparison with 100 mAs. CONCLUSIONS:Deep learning denoising resulted in quantitative improvements in image quality. Qualitative assessment demonstrated DLD images at or less than 10 mAs to be rated inferior to standard-dose images.
PMID: 36790870
ISSN: 1532-3145
CID: 5432132