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Background Detection of extranodal extension (ENE) at pathology is a poor prognostic indicator for rectal cancer, but whether ENE can be identified at pretreatment MRI is, to the knowledge of the authors, unknown. Purpose To evaluate the performance of pretreatment MRI in detecting ENE using a matched pathologic reference standard and to assess its prognostic value in patients with rectal cancer. Materials and Methods This single-center study included a prospective development data set consisting of participants with rectal adenocarcinoma who underwent pretreatment MRI and radical surgery (December 2021 to January 2023). MRI characteristics were identified by their association with ENE-positive nodes (χ test and multivariable logistic regression) and the performance of these MRI features was assessed (area under the receiver operating characteristic curve [AUC]). Interobserver agreement was assessed by Cohen κ coefficient. The prognostic value of ENE detected with MRI for predicting 3-year disease-free survival was assessed by Cox regression analysis in a retrospective independent validation cohort of patients with locally advanced rectal cancer (December 2019 to July 2020). Results The development data set included 147 participants (mean age, 62 years ± 11 [SD]; 87 male participants). The retrospective cohort included 110 patients (mean age, 60 years ± 9; 79 male participants). Presence of vessel interruption and fusion (both < .001), heterogeneous internal structure, and the broken-ring and tail signs (odds ratio range, 4.10-23.20; value range, <.001 to .002) were predictors of ENE at MRI, and together achieved an AUC of 0.91 (95% CI: 0.88, 0.93) in detecting ENE. Interobserver agreement was moderate for the presence of vessel interruption and fusion (κ = 0.46 for both) and substantial for others (κ = 0.61-0.67). The presence of ENE at pretreatment MRI was independently associated with worse 3-year disease-free survival (hazard ratio, 3.00; = .02). Conclusion ENE can be detected at pretreatment MRI, and its presence was associated with worse prognosis for patients with rectal cancer. © RSNA, 2024 See also the editorial by Eberhardt in this issue.
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http://dx.doi.org/10.1148/radiol.232605 | DOI Listing |
Med Acupunct
August 2025
Department of Specialty Medicine, Ohio University, Athens, Ohio, USA.
Introduction: This review evaluates the safety protocols for acupuncture, emphasizing the need for stringent measures due to the procedure's invasive nature.
Discussion: It discusses the necessity of global safety standards, including mandatory accreditation and licensing for practitioners to mitigate risks such as needle contamination and improper technique. The study advocates for extensive training and continuous education programs to ensure practitioners master both theoretical and practical aspects of acupuncture.
Front Oncol
August 2025
Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.
Purpose: Identifying radiomics features that help predict whether glioblastoma patients are prone to developing epilepsy may contribute to an improvement of preventive treatment and a better understanding of the underlying pathophysiology.
Materials And Methods: In this retrospective study, 3-T MRI data of 451 pretreatment glioblastoma patients (mean age: 61.2 ± 11.
Skeletal Radiol
September 2025
Department of Radiology, Federal University of Sao Paulo (UNIFESP), Napoleão de Barros St, 800, São Paulo, SP, 04024-000, Brazil.
Objective: To evaluate multiparametric MRI features of pediatric soft-tissue sarcomas, comparing pre-treatment and post-treatment features, and assessing correlation with clinical outcomes.
Materials And Methods: Retrospective cohort study, including pediatric patients (≤ 18 years) with histologically-confirmed soft-tissue sarcomas who underwent MRI with anatomic and functional sequences in consecutive series. Post-treatment MRI was available for a subset, and features were recorded by two readers.
Phys Imaging Radiat Oncol
July 2025
Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Background And Purpose: Predicting hepatocellular carcinoma (HCC) response to Stereotactic Body Radiation Therapy (SBRT) can be challenging. Here, we assessed the value of a radiomics-based machine learning (ML) approach for predicting HCC response to SBRT, using pre-treatment and early post-treatment magnetic resonance imaging (MRI).
Materials And Methods: This retrospective single-center study included 87 patients (M 67, mean age 65.
Neuropsychopharmacology
September 2025
Center for Depression Research and Clinical Care, Peter O'Donnell Jr. Brain Institute and the Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA.
This report sought to employ multi-modal integration of pre-treatment brain (electroencephalogram, resting-state functional magnetic resonance imaging) and blood (immune and metabolic) biomarkers to facilitate causal inference-based treatment selection by virtue of establishing predictability of remission to multi-stage antidepressant treatment. Data from two stages of pharmacotherapy in the 'Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression' (EMBARC) study from participants with both brain and blood biomarkers were included (N = 197). Participants were initially randomized to sertraline or placebo (Stage 1), and depending on clinical response at week-8, their therapy in Stage 2 was either maintained or switched (to sertraline, if a non-responder to placebo, or to bupropion, if a non-responder to sertraline).
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