Objectives: We evaluated the diagnostic performance of magnetic resonance imaging (MRI) in terms of identifying extramural venous invasion (EMVI) in rectal cancer patients with preoperative chemoradiotherapy (CRT) and its prognostic significance.
Methods: During 2008-2010, 200 patients underwent surgery following preoperative CRT for rectal cancer. Two radiologists independently reviewed all pre- and post-CRT MRI retrospectively. We investigated diagnostic performance of pre-CRT MR-EMVI (MR-EMVI) and post-CRT MR-EMVI (yMR-EMVI), based on pathological EMVI as the standard of reference. We assessed correlation between MRI findings and patients' prognosis, such as disease-free survival (DFS) and overall survival (OS). Additionally, subgroup analysis in MR- or yMR-EMVI-positive patients was performed to confirm the significance of the severity of EMVI in MRI on patient's prognosis.
Results: The sensitivity and specificity of yMR-EMVI were 76.19% and 79.75% (area under the curve: 0.830), respectively. In univariate analysis, yMR-EMVI was the only significant MRI factor in DFS (P = 0.027). The mean DFS for yMR-EMVI (+) patients was significantly less than for yMR-EMVI (-) patients: 57.56 months versus 72.46 months.
Conclusion: yMR-EMVI demonstrated good diagnostic performance. yMR-EMVI was the only significant EMVI-related MRI factor that correlated with patients' DFS in univariate analysis; however, it was not significant in multivariate analysis.
Key Points: • Diagnostic performance of MRI for EMVI after preoperative chemoradiotherapy is good. • The mean DFS was lower in yMR-EMVI-positive than yMR-EMVI-negative patients. • MRI can facilitate prognosis prediction of rectal cancer patients with preoperative chemoradiotherapy.
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http://dx.doi.org/10.1007/s00330-017-4978-6 | DOI Listing |
Ann Neurol
January 2025
Research Unit of Neurology, Neurophysiology and Neurobiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Rome, Italy.
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January 2025
Medical Genetics & Genomics Unit, AULSS8 Berica, Vicenza, Italy.
This document aims to provide good practice recommendations in order to support maternal-foetal medicine specialists, clinical geneticists and clinical laboratory geneticists in the management of pregnancies obtained after the transfer of an embryo tested with preimplantation genetic testing (PGT). It was drafted by geneticists expert in preimplantation genetics and prenatal genetic diagnosis belonging to the "Working Group in Cytogenomics, Prenatal and Reproductive Genetics" of the "Italian Society of Human Genetics" (SIGU). In particular, the paper addresses the diagnostic algorithm to be applied in prenatal follow-up depending on the type of PGT performed, the results obtained and the related diagnostic value based on the most recent literature data and Italian and international recommendations.
View Article and Find Full Text PDFZ Gerontol Geriatr
January 2025
Geriatrie, Universität Witten-Herdecke, Alfred Herrhausenstraße 50, 58455, Witten, Germany.
Chronic obstructive pulmonary disease (COPD) is a frequent disease from which approximately 8% of individuals aged 40 years and above suffer. The prevalence increases up to fivefold as age advances. Following an introduction including the etiology, measurement, characteristic features and classification of COPD, this article presents the consensus recommendations of the German Working Group on Pneumology in Older Patients.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, National Clinical Research Center for Eye Disease, Shanghai, 200080, China.
The objectives of this study are to construct a deep convolutional neural network (DCNN) model to diagnose and classify meibomian gland dysfunction (MGD) based on the in vivo confocal microscope (IVCM) images and to evaluate the performance of the DCNN model and its auxiliary significance for clinical diagnosis and treatment. We extracted 6643 IVCM images from the three hospitals' IVCM database as the training set for the DCNN model and 1661 IVCM images from the other two hospitals' IVCM database as the test set to examine the performance of the model. Construction of the DCNN model was performed using DenseNet-169.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
Vision transformer (ViT)and convolutional neural networks (CNNs) each possess distinct strengths in medical imaging: ViT excels in capturing long-range dependencies through self-attention, while CNNs are adept at extracting local features via spatial convolution filters. While ViT may struggle with capturing detailed local spatial information, critical for tasks like anomaly detection in medical imaging, shallow CNNs often fail to effectively abstract global context. This study aims to explore and evaluate hybrid architectures that integrate ViT and CNN to leverage their complementary strengths for enhanced performance in medical vision tasks, such as segmentation, classification, reconstruction, and prediction.
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