AIMC Topic: Rectal Neoplasms

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Improving rectal tumor segmentation with anomaly fusion derived from anatomical inpainting: a multicenter study.

Scientific reports
Accurate rectal tumor segmentation using magnetic resonance imaging (MRI) is paramount for effective treatment planning. It allows for volumetric and other quantitative tumor assessments, potentially aiding in prognostication and treatment response e...

Developing and external validating a prediction model using machine learning and logistic regression: informing the surgical approach for robotic surgery based on preoperative MRI.

Journal of robotic surgery
BACKGROUND: Preoperative prediction of surgical difficulty in robotic-assisted total mesorectal excision for rectal cancer remains challenging. While pelvic anatomical parameters measured by MRI have been associated with surgical complexity in laparo...

Research hotspots and trends of robotic rectal cancer surgery: a bibliometric analysis (2006-2025).

Journal of robotic surgery
Rectal cancer presents complex surgical challenges due to the confined pelvic anatomy. Robotic-assisted surgery has gained prominence for its enhanced precision, dexterity, and ergonomics compared to conventional laparoscopy. This bibliometric analys...

Automatically quantifying spatial heterogeneity of immune and tumor hypoxia environment and predicting disease-free survival for patients with rectal cancer.

Cancer immunology, immunotherapy : CII
Immunohistochemistry (IHC) remains the gold standard for evaluating protein expression in tumor microenvironment analysis. This approach hinders robust correlation analyses between spatial heterogeneity in the tumor microenvironment and clinical outc...

Machine learning combined with body composition predicts surgical difficulty in mid-low rectal cancer surgery.

Annals of medicine
BACKGROUND: This study sought to identify critical body composition characteristics associated with surgical difficulty in Laparoscopic Total Mesorectal Excision (LaTME) and to develop and validate an interpretable machine learning model using body c...

Deep learning-based vessel and nerve recognition model for lateral lymph node dissection: a retrospective feasibility study.

Langenbeck's archives of surgery
PURPOSE: Lateral lymph node dissection for rectal cancer is challenging because of the presence of blood vessels and nerves essential for postoperative genitourinary function and leg movements. Identifying these structures during surgery is crucial. ...

Machine learning-enhanced normal tissue complication probability modeling for late sciatic nerve toxicity prediction in carbon-ion radiotherapy: model development and clinical validation.

Physics in medicine and biology
To develop a machine learning-enhanced normal tissue complication probability (NTCP) model for predicting late sciatic nerve toxicity (LSNT) in sacrococcygeal chordoma (SC) and locally recurrent rectal cancer (LRRC) patients undergoing carbon-ion rad...

Automatic segmentation of male pelvic floor soft tissue structures for anatomical simulation and morphological assessment in lower rectal cancer surgery.

Techniques in coloproctology
BACKGROUND: Pelvic anatomy is a complex network of organs that varies between individuals. Understanding the anatomy of individual patients is crucial for precise rectal cancer surgeries. Therefore, developing technology that can allow visualization ...

Development and validation of machine-learning model based on dynamic tumor markers in predicting pathological complete response after neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer: a multicenter cohort study.

International journal of colorectal disease
OBJECTIVE: In this study, we constructed a new pCR predictor based on dynamic tumor marker changes before and after NCRT, the dynamic tumor marker score (DTMS), and combined it with other clinicopathological features to build a machine-learning model...

Predicting Lymph Node Metastasis in Rectal Cancer: Development and Validation of a Machine Learning Model Using Clinical Data.

JMIR medical informatics
BACKGROUND: Rectal cancer (RC) is a common malignant tumor, with lymph node metastasis (LNM) being a critical determinant of patient prognosis. Traditional diagnostic methods have limitations, necessitating the development of predictive models using ...