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Evaluating complete response prediction rates in locally advanced rectal cancer with different radiomics segmentation approaches.
Kaval, Gizem; Dagoglu Kartal, Merve Gulbiz; Azamat, Sena; Cingoz, Eda; Ertas, Gokhan; Karaman, Sule; Kurtuldu, Basak; Keskin, Metin; Berker, Neslihan; Karabulut, Senem; Oral, Ethem Nezih; Dagoglu Sakin, Nergiz.
Afiliación
  • Kaval G; Department of Radiation Oncology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Türkiye.
  • Dagoglu Kartal MG; Department of Radiology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Türkiye.
  • Azamat S; Department of Radiology, Cam and Sakura City Hospital, Istanbul, Türkiye.
  • Cingoz E; Department of Radiology, Bagcilar Training and Research Hospital, Istanbul, Türkiye.
  • Ertas G; Department of Biomedical Engineering, Yeditepe University, Istanbul, Türkiye.
  • Karaman S; Department of Radiation Oncology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Türkiye.
  • Kurtuldu B; Department of Emergency, Hackalibaba Hospital, Trabzon, Türkiye.
  • Keskin M; Department of General Surgery, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Türkiye.
  • Berker N; Department of Pathology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Türkiye.
  • Karabulut S; Department of Medical Oncology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Türkiye.
  • Oral EN; Department of Radiation Oncology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Türkiye.
  • Dagoglu Sakin N; Department of Radiation Oncology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Türkiye.
Pathol Oncol Res ; 30: 1611744, 2024.
Article en En | MEDLINE | ID: mdl-38694706
ABSTRACT

Purpose:

Studies examining prediction of complete response (CR) in locally advanced rectum cancer (LARC) from pre/post chemoradiotherapy (CRT) magnetic resonance imaging (MRI) are performed mostly with segmentations of the tumor, whereas only in two studies segmentation included tumor and mesorectum. Additionally, pelvic extramesorectal region, which is included in the clinical target volume (CTV) of radiotherapy, may contain information. Therefore, we aimed to compare predictive rates of radiomics analysis with features extracted from segmentations of tumor, tumor+mesorectum, and CTV. Methods and materials Ninety-three LARC patients who underwent CRT in our institution between 2012 and 2019 were retrospectively scanned. Patients were divided into CR and non-CR groups. Tumor, tumor+mesorectum and CTV were segmented on T2 preCRT MRI images. Extracted features were compared for best area under the curve (AUC) of CR prediction with 15 machine-learning models.

Results:

CR was observed in 25 patients (26.8%), of whom 13 had pathological, and 12 had clinical complete response. For tumor, tumor+mesorectum and CTV segmentations, the best AUC were 0.84, 0.81, 0.77 in the training set and 0.85, 0.83 and 0.72 in the test set, respectively; sensitivity and specificity for the test set were 76%, 90%, 76% and 71%, 67% and 62%, respectively.

Conclusion:

Although the highest AUC result is obtained from the tumor segmentation, the highest accuracy and sensitivity are detected with tumor+mesorectum segmentation and these findings align with previous studies, suggesting that the mesorectum contains valuable insights for CR. The lowest result is obtained with CTV segmentation. More studies with mesorectum and pelvic nodal regions included in segmentation are needed.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias del Recto / Imagen por Resonancia Magnética / Quimioradioterapia Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Pathol Oncol Res Asunto de la revista: NEOPLASIAS / PATOLOGIA Año: 2024 Tipo del documento: Article Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias del Recto / Imagen por Resonancia Magnética / Quimioradioterapia Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Pathol Oncol Res Asunto de la revista: NEOPLASIAS / PATOLOGIA Año: 2024 Tipo del documento: Article Pais de publicación: Suiza