AIMC Topic: Margins of Excision

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A systematic scoping review exploring variation in practice in specimen mammography for Intraoperative Margin Analysis in Breast Conserving Surgery and the role of artificial intelligence in optimising diagnostic accuracy.

European journal of radiology
PURPOSE: Specimen Mammography (SM) is commonly used in Breast Conserving Surgery (BCS) for intraoperative margin analysis. A systematic scoping review was conducted to identify sources of methodological variation in Specimen Mammography Interpretatio...

Deep learning-enabled fluorescence imaging for surgical guidance: training for oral cancer depth quantification.

Journal of biomedical optics
SIGNIFICANCE: Oral cancer surgery requires accurate margin delineation to balance complete resection with post-operative functionality. Current fluorescence imaging systems provide two-dimensional margin assessment yet fail to quantify tumor depth p...

Utilizing deep learning model for assessing melanocytic density in resection margins of lentigo maligna.

Diagnostic pathology
BACKGROUND: Surgical excision with clear histopathological margins is the preferred treatment to prevent progression of lentigo maligna (LM) to invasive melanoma. However, the assessment of resection margins on sun-damaged skin is challenging. We dev...

Artificial Intelligence for Mohs and Dermatologic Surgery: A Systematic Review and Meta-Analysis.

Dermatologic surgery : official publication for American Society for Dermatologic Surgery [et al.]
BACKGROUND: Over the past decade, several studies have shown that potential of artificial intelligence (AI) in dermatology. However, there has yet to be a systematic review evaluating the usage of AI specifically within the field of Mohs micrographic...

Hyperspectral imaging with machine learning for in vivo skin carcinoma margin assessment: a preliminary study.

Physical and engineering sciences in medicine
Surgical excision is the most effective treatment of skin carcinomas (basal cell carcinoma or squamous cell carcinoma). Preoperative assessment of tumoral margins plays a decisive role for a successful result. The aim of this work was to evaluate the...

From quantitative metrics to clinical success: assessing the utility of deep learning for tumor segmentation in breast surgery.

International journal of computer assisted radiology and surgery
PURPOSE: Preventing positive margins is essential for ensuring favorable patient outcomes following breast-conserving surgery (BCS). Deep learning has the potential to enable this by automatically contouring the tumor and guiding resection in real ti...

Real-time classification of tumour and non-tumour tissue in colorectal cancer using diffuse reflectance spectroscopy and neural networks to aid margin assessment.

International journal of surgery (London, England)
BACKGROUND: Colorectal cancer is the third most commonly diagnosed malignancy and the second leading cause of mortality worldwide. A positive resection margin following surgery for colorectal cancer is linked with higher rates of local recurrence and...