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1.
Radiol Clin North Am ; 61(5): 847-859, 2023 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-37495292

RESUMO

Heart transplantation has been increasingly performed for patients with end-stage heart failure most commonly related to ischemic and non-ischemic cardiomyopathies. The major complications are procedure-related complications, infection, acute rejection, cardiac allograft vasculopathy, and malignancy. Radiologists have an important role in the evaluation of transplant candidates and early detection of postoperative complications.


Assuntos
Transplante de Coração , Humanos , Transplante de Coração/efeitos adversos , Transplante de Coração/métodos , Complicações Pós-Operatórias/diagnóstico por imagem , Fatores de Risco
2.
Radiol Case Rep ; 17(12): 4924-4927, 2022 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-36299866

RESUMO

IgG4-related disease (IgG4-RD) is an immune-mediated multiorgan fibroinflammatory disorder with variable clinical presentations. IgG4-RD cardiovascular involvement is considered rare, with pulmonary arterial involvement reported in a small subset of cases. Known pulmonary artery manifestations include pulmonary arteritis, pulmonary artery stenoses and central pulmonary artery aneurysms. Here we report 2 different patients with multifocal dilatation of the segmental and subsegmental pulmonary arteries with differing degrees of severity. Both patients also had coronary arterial abnormalities.

4.
JAMA Netw Open ; 5(8): e2229289, 2022 08 01.
Artigo em Inglês | MEDLINE | ID: mdl-36044215

RESUMO

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.


Assuntos
Aprendizado Profundo , Derrame Pleural , Pneumonia , Pneumotórax , Adulto , Inteligência Artificial , Estudos de Coortes , Humanos , Masculino , Pessoa de Meia-Idade , Pneumonia/diagnóstico por imagem
5.
AJR Am J Roentgenol ; 219(1): 55-65, 2022 07.
Artigo em Inglês | MEDLINE | ID: mdl-35080453

RESUMO

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.


Assuntos
Detecção Precoce de Câncer , Neoplasias Pulmonares , Idoso , Detecção Precoce de Câncer/métodos , Feminino , Humanos , Pulmão/patologia , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/patologia , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Tomografia Computadorizada por Raios X/métodos
7.
Cancers (Basel) ; 13(14)2021 Jul 16.
Artigo em Inglês | MEDLINE | ID: mdl-34298783

RESUMO

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.

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