Purpose: Texture analysis (TA) parameters (variance of SI, mean of gradient, variance of gradient, kurtosis of SI, and entropy) in patients with invasive ductal carcinoma (IDC) contribute to objective assessment of neoadjuvant chemotherapy (NACT) activity. The objective was to assess TA parameters in early identification of non-responders (NR) in NACT, after the 2nd cycle of NACT.
Material And Methods: Fifty patients (N = 50) were included in the retrospective analysis of baseline and MRI following the 2nd cycle of NACT. TA parameters were computed and correlated to the lesion size and DWI-ADC in NR (N1 = 25). Additional matched responders (R, N2 = 25) assessed for the same parameters, served as the control group.
Results: Tumor size and ADC did not change significantly in NR after the 2nd cycle of NACT (2.88 ± 0.38 vs. 2.76 ± 0.36 [cm], p = 0.131; 1.01 ± 0.14 vs. 1.05 ± 0.13 [mm/s × 10], p = 0.363), but TA parameters changed significantly: variance of gradient (346.5 ± 12.6 vs. 355.6 ± 16.9, p = 0.01), kurtosis of SI (1.47 ± 0.09 vs. 1.54 ± 0.11, p = 0.02), entropy LH (60.39 ± 4.34 vs. 64.42 ± 3.05, p = 0.001) and entropy HL (61.02 ± 5.51 vs. 65.63 ± 3.63, p < 0.00001). TA parameters, particularly entropy (EN LH 64.42 ± 3.05 vs. 61.59 ± 1.76, p < 0.0001; EN HL 65.63 ± 3.63 vs. 62.89 ± 2.05, p < 0.0001), significantly differ between NR and R in early response assessment.
Conclusion: Entropy, kurtosis of SI and variance of gradient tend to increase in NR. TA parameters significantly differ between NR and R after the 2nd cycle of NACT. TA parameters, related to morpho-functional parameters may contribute to early NR identification.
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http://dx.doi.org/10.1016/j.clinimag.2020.04.016 | DOI Listing |
Ann Neurol
December 2024
Department of Neurology, Jewish Hospital Berlin, Berlin, Germany.
Objective: Among patients with acute stroke, we aimed to identify those who will later develop central post-stroke pain (CPSP) versus those who will not (non-pain sensory stroke [NPSS]) by assessing potential differences in somatosensory profile patterns and evaluating their potential as predictors of CPSP.
Methods: In a prospective longitudinal study on 75 acute stroke patients with somatosensory symptoms, we performed quantitative somatosensory testing (QST) in the acute/subacute phase (within 10 days) and on follow-up visits for 12 months. Based on previous QST studies, we hypothesized that QST values of cold detection threshold (CDT) and dynamic mechanical allodynia (DMA) would differ between CPSP and NPSS patients before the onset of pain.
Zygote
December 2024
Tissue Engineering Department, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
This study explores the efficacy of a novel microfluidic device in isolating rheotactic sperm and assesses their advantages compared with other motile sperm. Two microfluidic devices were used in this study: the microfluidic device we designed to separate sperm based on rheotaxis and a simple passive microfluidic device. We compared the results with the density gradient centrifugation technique.
View Article and Find Full Text PDFJMIR Ment Health
December 2024
Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim / Heidelberg University, Mannheim, Germany.
Background: Mobile devices for remote monitoring are inevitable tools to support treatment and patient care, especially in recurrent diseases such as major depressive disorder. The aim of this study was to learn if machine learning (ML) models based on longitudinal speech data are helpful in predicting momentary depression severity. Data analyses were based on a dataset including 30 inpatients during an acute depressive episode receiving sleep deprivation therapy in stationary care, an intervention inducing a rapid change in depressive symptoms in a relatively short period of time.
View Article and Find Full Text PDFJ Am Med Dir Assoc
December 2024
School of Nursing, Peking University, Beijing, China. Electronic address:
Objectives: Malnutrition is generally studied to be involved in outlining hazard frailty trajectories, resulting in adverse outcomes. In view of frailty's multidimensional nature, we aimed to assess the contribution of nutritional items in existing frailty tools to adverse outcomes, and develop and validate a nutritional frailty phenotype based on machine learning.
Design: A population-based prospective cohort study.
Chemosphere
December 2024
Department of Energy Systems Research, Ajou University, Suwon, 16499, Republic of Korea; Department of Environmental and Safety Engineering, Ajou University, Suwon, 16499, Republic of Korea. Electronic address:
This study investigated the potential of machine learning (ML) as a substitute for polynomial regression in conventional response surface methodology (RSM) for decolorizing textile wastewater via a UV/HO process. While polynomial regression offers limited adaptability, ML models provide superior flexibility in capturing nonlinear responses but are prone to overfitting, particularly with constrained RSM datasets. In this study, we evaluated decision tree (DT), random forest (RF), multilayer perceptron (MLP), and extreme gradient boosting (XGBoost) models with respect to a quadratic regression model.
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