Introduction. In surgical oncology, histological analysis of excised tumor specimen is the conventional method to assess the safety of the resection margins. We tested the feasibility of using MRI to assess the resection margins of freshly explanted tumor specimens in rats. Materials and Methods. Fourteen specimen of sarcoma were resected in rats and analysed both with MRI and histologically. Slicing of the specimen was identical for the two methods and corresponding slices were paired. 498 margins were measured in length and classified using the UICC classification (R0, R1, and R2). Results. The mean difference between the 498 margins measured both with histology and MRI was 0.3 mm (SD 1.0 mm). The agreement interval of the two measurement methods was [-1.7 mm; 2.2 mm]. In terms of the UICC classification, a strict correlation was observed between MRI- and histology-based classifications (κ = 0.84, P < 0.05). Discussion. This experimental study showed the feasibility to use MRI images of excised tumor specimen to assess the resection margins with the same degree of accuracy as the conventional histopathological analysis. When completed, MRI acquisition of resected tumors may alert the surgeon in case of inadequate margin and help advantageously the histopathological analysis.
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http://dx.doi.org/10.1155/2014/686790 | DOI Listing |
Cureus
December 2024
Department of Breast, Plastic and Reconstructive Surgery, Royal Hallamshire Hospital, Sheffield, GBR.
Background The incidence of margin re-excision following breast conserving surgery (BCS) is a quality measure in the National Health Service. The threshold is less than 20% of all BCS procedures. Despite three decades of studies and a wealth of literature identifying multiple factors associated with increased risk for margin involvement, an accepted threshold rate affecting one in five procedures remains high.
View Article and Find Full Text PDFColorectal Dis
February 2025
Department of Surgery, Radboud University Medical Centre, Nijmegen, The Netherlands.
Aim: Locally advanced colon cancer (LACC) often necessitates complex prognosis-determining treatment. This study investigated the impact of hospital volume on short- and long-term outcomes following surgery for LACC.
Method: Data involving all patients with LACC categorized as clinical T4 and/or N2, between 2015 and 2019 in the Netherlands, were extracted from the Netherlands Cancer Registry.
Introduction: Sarcomas are rare cancers originating from mesenchymal tissues, manifesting in diverse anatomical locations, but notably in connective tissue, muscles and the skeleton. Thoracic sarcomas present a unique diagnostic and surgical challenge attributable to their rarity and pathoanatomy. Standard practice currently comprises wide surgical excision, often accompanied by adjuvant chemotherapy and/or radiotherapy.
View Article and Find Full Text PDFBMC Res Notes
January 2025
Department of Surgery, Department of Clinical Sciences, Division of Surgery, Skåne University Hospital, Lund University, Lund, Sweden.
Objectives: Positive resection margins after breast-conserving surgery (BCS) most often demands a repeat surgery. To preoperatively identify patients at risk of positive margins, a multivariable model has been developed that predicts positive margins after BCS with a high accuracy. This study aimed to externally validate this prediction model to explore its generalizability and assess if additional preoperatively available variables can further improve its predictive accuracy.
View Article and Find Full Text PDFInt J Oral Sci
January 2025
School of Cyber Science and Engineering, Sichuan University, Chengdu, China.
The presence of a positive deep surgical margin in tongue squamous cell carcinoma (TSCC) significantly elevates the risk of local recurrence. Therefore, a prompt and precise intraoperative assessment of margin status is imperative to ensure thorough tumor resection. In this study, we integrate Raman imaging technology with an artificial intelligence (AI) generative model, proposing an innovative approach for intraoperative margin status diagnosis.
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