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BACKGROUND: Exposure assessment is integral to the diagnosis of hypersensitivity pneumonitis (HP). Although the clinical relevance of exposed antigens is essential for the assessment, many of the previous guidelines or reports have only evaluated simple exposure histories or immunological tests. To overcome this problem, the Exposure Assessment Form (EAF) was developed as an assessment tool for classifying the exposure grade from G0 to G4. The EAF was modified from the description in the Japanese clinical practice guide 2022 for HP published by the Japanese Respiratory Society. METHODS: One hundred and seventy-two consecutive patients with interstitial lung disease who underwent multidisciplinary discussion (MDD) at our hospital were retrospectively examined. We assessed whether the use of the EAF improved the diagnostic performance of the international guideline of HP. We also evaluated whether the exposure grade affected the prognosis of HP. RESULTS: Even when a HP diagnosis was made with a confidence of 70% or higher according to the international guideline, less than half of these cases resulted in a final diagnosis of HP when the exposure grades were lower than G3. When the result of the EAF was integrated into the exposure definition of the international guideline, the specificity of the diagnostic performance improved, while sensitivity was maintained. Furthermore, HP patients with an exposure grade of G3 or higher showed a tendency to take a longer time to initiate medication. CONCLUSIONS: This is the first study to evaluate the clinical relevance of possible antigens using the EAF. Assessing the exposure grade prevents overdiagnosis and improves the diagnostic performance of the international guideline.
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Alveolitis Alérgica Extrínseca , Enfermedades Pulmonares Intersticiales , Humanos , Estudios Retrospectivos , Relevancia Clínica , Alveolitis Alérgica Extrínseca/diagnóstico , Enfermedades Pulmonares Intersticiales/diagnóstico , AntígenosRESUMEN
BACKGROUND AND OBJECTIVES: This study compares the clinical properties of original breast ultrasound images and those synthesized by a generative adversarial network (GAN) to assess the clinical usefulness of GAN-synthesized images. MATERIALS AND METHODS: We retrospectively collected approximately 200 breast ultrasound images for each of five representative histological tissue types (cyst, fibroadenoma, scirrhous, solid, and tubule-forming invasive ductal carcinomas) as training images. A deep convolutional GAN (DCGAN) image-generation model synthesized images of the five histological types. Two diagnostic radiologists (reader 1 with 13 years of experience and reader 2 with 7 years of experience) were given a reading test consisting of 50 synthesized and 50 original images (≥1-month interval between sets) to assign the perceived histological tissue type. The percentages of correct diagnoses were calculated, and the reader agreement was assessed using the kappa coefficient. RESULTS: The synthetic and original images were indistinguishable. The correct diagnostic rates from the synthetic images for readers 1 and 2 were 86.0% and 78.0% and from the original images were 88.0% and 78.0%, respectively. The kappa values were 0.625 and 0.650 for the synthetic and original images, respectively. The diagnoses made from the DCGAN synthetic images and original images were similar. CONCLUSION: The DCGAN-synthesized images closely resemble the original ultrasound images in clinical characteristics, suggesting their potential utility in clinical education and training, particularly for enhancing diagnostic skills in breast ultrasound imaging.
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Neoplasias de la Mama , Quistes , Humanos , Femenino , Estudios Retrospectivos , Ultrasonografía Mamaria , Neoplasias de la Mama/diagnóstico por imagen , EscolaridadRESUMEN
PURPOSE: To compare different biopsy systems with different-sized needles by determining the weight of the tissue cores, which is one of the important factors for precise pathological diagnoses, and to provide a rationale for choosing the appropriate breast biopsy system with the appropriate needle for breast cancer biopsy. METHODS: Six different vacuum-assisted biopsy (VAB) systems and one core needle biopsy (CNB) system with different-sized needles in different modes were compared, representing 15 total combinations. Tissue cores were obtained from a chicken breast phantom, which is a common substitute for human breast tissue. Five cores were taken for each combination and weighed. RESULTS: The CNB combination provided significantly lighter tissue cores compared with the VAB combinations with the same-size (14-G) needle (P < 0.01). The combinations using the thickest needle obtained the heaviest among all systems (P < 0.02). The untethered battery-free VAB system yielded the lightest specimen among the VAB systems with the same-sized (12-G) needle (P < 0.04). The percent coefficient of variation (%CV) of the core weights obtained using VAB without a basket was significantly smaller compared with the core weights obtained using VAB with a basket (P < 0.01). CONCLUSION: VAB systems can yield larger tissue cores compared with CNB systems. The size of the tissue cores varies even with the same-sized needle among different VAB systems. When performing a breast tissue biopsy, it is important to consider not only CNB versus VAB but also what specific device to use with which needle size.
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PURPOSE: This study aimed to enhance the diagnostic accuracy of contrast-enhanced breast magnetic resonance imaging (MRI) using gadobutrol for differentiating benign breast lesions from malignant ones. Moreover, this study sought to address the limitations of current imaging techniques and criteria based on the Breast Imaging Reporting and Data System (BI-RADS). MATERIALS AND METHODS: In a multicenter retrospective study conducted in Japan, 200 women were included, comprising 100 with benign lesions and 100 with malignant lesions, all classified under BI-RADS categories 3 and 4. The MRI protocol included 3D fast gradient echo T1- weighted images with fat suppression, with gadobutrol as the contrast agent. The analysis involved evaluating patient and lesion characteristics, including age, size, location, fibroglandular tissue, background parenchymal enhancement (BPE), signal intensity, and the findings of mass and non-mass enhancement. In this study, univariate and multivariate logistic regression analyses were performed, along with decision tree analysis, to identify significant predictors for the classification of lesions. RESULTS: Differences in lesion characteristics were identified, which may influence malignancy risk. The multivariate logistic regression model revealed age, lesion location, shape, and signal intensity as significant predictors of malignancy. Decision tree analysis identified additional diagnostic factors, including lesion margin and BPE level. The decision tree models demonstrated high diagnostic accuracy, with the logistic regression model showing an area under the curve of 0.925 for masses and 0.829 for non-mass enhancements. CONCLUSION: This study underscores the importance of integrating patient age, lesion location, and BPE level into the BI-RADS criteria to improve the differentiation between benign and malignant breast lesions. This approach could minimize unnecessary biopsies and enhance clinical decision-making in breast cancer diagnostics, highlighting the effectiveness of gadobutrol in breast MRI evaluations.