Men treated for prostate cancer often have unexpected outcomes despite predictive models based on stage, grade and prostate-specific antigen (PSA). Previous results have indicated that nuclear morphometry can predict patient outcome in urologic malignancies. Application of this analytical method in prostate cancer treated with radiation therapy is limited. We have evaluated the predictive ability of nuclear morphometry in such patients. Histologic sections from 23 men with clinically localized adenocarcinoma of the prostate treated with radiation therapy were studied. Nuclear morphometric parameters were assessed using a previously described and validated system. Univariate and multivariate logistic regression analyses and a Cox proportional hazards model were used to assess the ability of nuclear morphometric parameters to predict recurrence and disease-free interval. Ten patients had no recurrence with median follow-up of 47. 5 months, while 13 had recurrence. Gleason grade was not predictive of treatment outcome. Pre-treatment PSA data, available for only 11 patients, were predictive of treatment outcome. Several nuclear morphometric parameters predicted recurrence, including upper quartile of suboptimal circle fit and upper quartile of feret-diameter ratio. A prognostic factor score incorporating these 2 parameters was derived, which predicted disease-free interval (p = 0.0014). Int. J. Cancer (Pred. Oncol.) 84:594-597, 1999.
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http://dx.doi.org/10.1002/(sici)1097-0215(19991222)84:6<594::aid-ijc9>3.0.co;2-d | DOI Listing |
Plants (Basel)
January 2025
Faculty of Forestry, University of Sarajevo, Zmaja od Bosne 8, 71 000 Sarajevo, Bosnia and Herzegovina.
Polyploidy is a powerful mechanism driving genetic, physiological, and phenotypic changes among cytotypes of the same species across both large and small geographic scales. These changes can significantly shape population structure and increase the evolutionary and adaptation potential of cytotypes. , an edaphic steno-endemic species with a narrow distribution in the Balkan Peninsula, serves as an intriguing case study.
View Article and Find Full Text PDFKidney Res Clin Pract
January 2025
Department of Radiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Background: We aimed to explore changes in decision-related brain microstructure, brain functional activities, and functional connectivity, and their correlations with cognitive function in end-stage kidney disease (ESKD) patients undergoing peritoneal dialysis (PD). Furthermore, the impact of dialysis on these changes was examined.
Methods: Thirty ESKD patients undergoing PD, 20 chronic kidney disease (CKD) stage 5 patients without dialysis (predialysis CKD stage 5), and 30 healthy controls (HC) were recruited for the study.
J Alzheimers Dis
January 2025
Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Background: Single-subject voxel-based morphometry (VBM) is a powerful technique for reader-independent detection of brain atrophy in structural magnetic resonance imaging (MRI) to support the (differential) diagnosis and staging of neurodegenerative diseases in individual patients. However, VBM is sensitive to the MRI scanner platform and details of the acquisition sequence. To mitigate this limitation, we recently proposed and validated a convolutional neural network (CNN)-based VBM which does not rely on a normative reference database.
View Article and Find Full Text PDFNeuroimage
February 2025
Department of Medical Imaging, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, China. Electronic address:
Hum Brain Mapp
January 2025
Amsterdam UMC, Department of Radiology and Nuclear Medicine, University of Amsterdam, Amsterdam, the Netherlands.
Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-and-error process of finding an effective treatment for major depressive disorder (MDD). We tested and compared machine learning-based methods that predict individual-level pharmacotherapeutic treatment response using cortical morphometry from multisite longitudinal cohorts. We conducted an international analysis of pooled data from six sites of the ENIGMA-MDD consortium (n = 262 MDD patients; age = 36.
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