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Transrectal ultrasound (TRUS) is a cost-effective test for preoperative assessment of rectal cancer. However, whether the accuracy of TRUS staging is correlated with tumor location remains obscured. This study is designed to explore their relationship and confirm an optimal application of TRUS in rectal cancer restaging. From 2005 to 2011, rectal cancer patients with TRUS data were retrospectively reviewed. Patients were divided into five groups according to tumor-involved rectal segment (SEG) above the anal verge: SEG I 1-3cm, II 3-6cm, III 6-9cm, IV 9-12cm, and V 12-16cm. The accuracy and long-term outcomes of tumor staging were compared between ultrasonographic and pathological stages. 219 patients were included, with 55 (25.1%) in SEG I, 123 (56.2%) in SEG II, 32 (14.6%) in SEG III, 4 (1.8%) in SEG IV and 5 (2.3%) in SEG V. The overall accuracy of TRUS staging was remarkably superior to clinical staging by CT (64.8% vs. 34.7%, ), with 70.3% and 82.2% for ultrasonographic T and N stages respectively. The accuracy of TRUS reached its peak value when tumors were located in SEG II. The 5-year overall survival had no significant difference between TRUS and pathology staging for all stages. A cox regression analysis indicated that high levels of CEA and tumor location were risk factors of inaccurate staging. TRUS is still a valuable examination for restaging of rectal cancer after neoadjuvant therapy. The application of TRUS would be optimal for rectal cancer located 3-6cm above the anal verge.
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http://dx.doi.org/10.7150/jca.22661 | DOI Listing |
Front Oncol
August 2025
Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Objective: The retrieval of 12 lymph nodes (LNs) remains a crucial criterion for accurate staging and prognosis evaluation in rectal cancer (RC). However, some patients fail to meet this threshold after surgery. This study developed a nomogram model based on clinical variables to predict the probability of retrieving 12 LNs postoperatively.
View Article and Find Full Text PDFJ Appl Clin Med Phys
September 2025
Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Clinical Research Center for Radiation Oncology, Shanghai Key Laboratory of Radiation Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Purpose: This study aims to assess percentage of automated AIO plans that met clinical treatment standards of radiotherapy plans generated by the fully automated All-in-one (AIO) process.
Methods: The study involved 117 rectal cancer patients who underwent AIO treatment. Fully automated regions of interest (ROI) and treatment plans were developed without manual intervention, comparing them to manually generated plans used in clinical practice.
J Magn Reson Imaging
September 2025
Key Laboratory of Intelligent Medical Imaging of Wenzhou, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Background: Tumor deposits (TDs) are an important prognostic factor in rectal cancer. However, integrated models combining clinical, habitat radiomics, and deep learning (DL) features for preoperative TDs detection remain unexplored.
Purpose: To investigate fusion models based on MRI for preoperative TDs identification and prognosis in rectal cancer.
Int Urol Nephrol
September 2025
Department of Urology, Brigham and Women's Hospital, Harvard Medical School, 45 Francis St, ASB II-3, Boston, MA, 02115, USA.
Background: With the advancement of MR-based imaging, prostate cancer ablative therapies have seen increased interest to reduce complications of prostate cancer treatment. Although less invasive, they do carry procedural risks, including rectal injury. To date, the medicolegal aspects of ablative therapy remain underexplored.
View Article and Find Full Text PDFAnn Surg Oncol
September 2025
Department of Surgery, Divisions of Surgical Oncology, Colon and Rectal Surgery, Immunotherapy, University of Louisville School of Medicine, Louisville, KY, USA.