Your browser doesn't support javascript.
loading
Gastrointestinal stromal tumours: Preoperative imaging features to predict recurrence after curative resection.
Jung, Haerang; Lee, Sang Min; Kim, Young Chul; Byun, Jieun; Park, Jin Young; Oh, Bo Young; Kwon, Mi Jung; Kim, Jeehyoung.
Afiliación
  • Jung H; Department of Radiology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea. Electronic address: hrjung92@hanmail.net.
  • Lee SM; Department of Radiology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea. Electronic address: twin393@hanmail.net.
  • Kim YC; Department of Radiology, Hallym University Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Republic of Korea. Electronic address: yochoru@gmail.com.
  • Byun J; Department of Radiology, Ewha Womans University Medical Center, Ewha Womans University College of Medicine, Seoul, Republic of Korea. Electronic address: sueno54@naver.com.
  • Park JY; Department of Radiology, Busan Paik Hospital, College of Medicine, Inje University, Busan, Republic of Korea. Electronic address: kachulove@hanmail.net.
  • Oh BY; Department of Surgery, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea. Electronic address: obbyy@hanmail.net.
  • Kwon MJ; Department of Pathology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea. Electronic address: mulank99@hallym.or.kr.
  • Kim J; Department of Orthopedic Surgery, Seoul Sacred Heart General Hospital, Seoul, Republic of Korea. Electronic address: kjhnav@naver.com.
Eur J Radiol ; 149: 110193, 2022 Apr.
Article en En | MEDLINE | ID: mdl-35149340
ABSTRACT

PURPOSE:

To identify whether preoperative factors could predict the recurrence after curative resection of gastrointestinal stromal tumours (GISTs) and evaluate the performance of a prediction model using preoperative factors for GIST recurrence compared to a model using preoperative/postoperative factors.

METHOD:

This retrospective study included patients who underwent curative resection and preoperative CT for GIST. CT imaging features as preoperative factors were analysed by two abdominal radiologists. Modified National Institutes of Health scores were accessed as a postoperative factor. Multiple logistic regression analysis was performed to assess the preoperative and postoperative factors in predicting GIST recurrence. Through the logistic regression, two prediction models using preoperative factors only and both preoperative/postoperative factors were constructed, respectively. The internal validation of the prediction models was performed using bootstrapping sampling.

RESULTS:

Data in 113 patients were evaluated. Among them, 14 patients had recurrence. The multiple logistic regression analysis demonstrated that non-gastric location (odds ratio [OR] = 5.12, p = 0.029), ill-defined margin (OR = 4.93, p = 0.023), and prominent vessels around tumour (OR = 6.78, p = 0.007) were significant factors. The prediction models using these preoperative factors and adding a postoperative factor showed an area under the receiver operating characteristic curve of 0.863 and 0.897, respectively, which were not statistically different. The bootstrapping sampling showed the two models were valid.

CONCLUSION:

The prediction model derived from non-gastric location, ill-defined margin, and prominent vessels around tumour can be used preoperatively to estimate the risk of recurrence after resection of GIST.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tumores del Estroma Gastrointestinal Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Eur J Radiol Año: 2022 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tumores del Estroma Gastrointestinal Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Eur J Radiol Año: 2022 Tipo del documento: Article
...