Advanced search
1 file | 14.60 KB Add to list

Predicting pathological response to neoadjuvant chemotherapy in osteosarcoma using dynamic contrast-enhanced MRI : internal and external validation of a semi-quantitative model

Author
Organization
Abstract
Objective To identify which dynamic contrast-enhanced (DCE-)MRI features best predict histological response to neoadjuvant chemotherapy in patients with an osteosarcoma. Methods Patients with osteosarcoma who underwent DCE-MRI before and after neoadjuvant chemotherapy prior to resection were retrospectively included at two different centers. Data from the center with the larger cohort (training cohort) was used to identify which method for region-of-interest selection (whole slab or focal area method) and which change in DCE-MRI features (time to enhancement, wash-in rate, maximum relative enhancement and area under the curve) gave the most accurate prediction of histological response. Models were created using logistic regression and cross-validated. The most accurate model was then externally validated using data from the other center (test cohort). Results Fifty-five (27 poor response) and 30 (19 poor response) patients were included in training and test cohorts, respectively. Intraclass correlation coefficient of relative DCE-MRI features ranged 0.81–0.97 with the whole slab and 0.57–0.85 with the focal area segmentation method. Poor histological response was best predicted with the whole slab segmentation method using a single feature threshold, relative wash-in rate <2.3. Mean accuracy was 0.85 (95%CI: 0.75–0.95), and area under the receiver operating characteristic curve (AUC-index) was 0.93 (95%CI: 0.86–1.00). In external validation, accuracy and AUC-index were 0.80 and 0.80. Conclusion In this study, a relative wash-in rate of <2.3 determined with the whole slab segmentation method predicted histological response to neoadjuvant chemotherapy in osteosarcoma. Consistent performance was observed in an external test cohort.

Downloads

  • Abstract ESSR TVDB.docx
    • full text (Accepted manuscript)
    • |
    • open access
    • |
    • ZIP archive
    • |
    • 14.60 KB

Citation

Please use this url to cite or link to this publication:

MLA
Van Den Berghe, Thomas, et al. “Predicting Pathological Response to Neoadjuvant Chemotherapy in Osteosarcoma Using Dynamic Contrast-Enhanced MRI : Internal and External Validation of a Semi-Quantitative Model.” 2023 ESSR Annual Scientific Meeting, Abstracts, 2023 ESSR Annual Scientific Meeting, 2023.
APA
Van Den Berghe, T., Kalisvaart, G. M., Grootjans, W., Lejoly, M., Huysse, W., Bovée, J. V. M. G., … Bloem, J. L. (2023). Predicting pathological response to neoadjuvant chemotherapy in osteosarcoma using dynamic contrast-enhanced MRI : internal and external validation of a semi-quantitative model. 2023 ESSR Annual Scientific Meeting, Abstracts. Presented at the 2023 ESSR Annual Scientific Meeting, Bilbao, Spain.
Chicago author-date
Van Den Berghe, Thomas, Gijsbert M. Kalisvaart, Willem Grootjans, Maryse Lejoly, Wouter Huysse, Judith V.M.G. Bovée, David Creytens, et al. 2023. “Predicting Pathological Response to Neoadjuvant Chemotherapy in Osteosarcoma Using Dynamic Contrast-Enhanced MRI : Internal and External Validation of a Semi-Quantitative Model.” In 2023 ESSR Annual Scientific Meeting, Abstracts. 2023 ESSR Annual Scientific Meeting.
Chicago author-date (all authors)
Van Den Berghe, Thomas, Gijsbert M. Kalisvaart, Willem Grootjans, Maryse Lejoly, Wouter Huysse, Judith V.M.G. Bovée, David Creytens, Hans Gelderblom, Frank M. Speetjens, Michiel A.J. van de Sande, Lioe-Fee de Geus-Oei, Koenraad Verstraete, and Johannes L. Bloem. 2023. “Predicting Pathological Response to Neoadjuvant Chemotherapy in Osteosarcoma Using Dynamic Contrast-Enhanced MRI : Internal and External Validation of a Semi-Quantitative Model.” In 2023 ESSR Annual Scientific Meeting, Abstracts. 2023 ESSR Annual Scientific Meeting.
Vancouver
1.
Van Den Berghe T, Kalisvaart GM, Grootjans W, Lejoly M, Huysse W, Bovée JVMG, et al. Predicting pathological response to neoadjuvant chemotherapy in osteosarcoma using dynamic contrast-enhanced MRI : internal and external validation of a semi-quantitative model. In: 2023 ESSR Annual Scientific Meeting, Abstracts. 2023 ESSR Annual Scientific Meeting; 2023.
IEEE
[1]
T. Van Den Berghe et al., “Predicting pathological response to neoadjuvant chemotherapy in osteosarcoma using dynamic contrast-enhanced MRI : internal and external validation of a semi-quantitative model,” in 2023 ESSR Annual Scientific Meeting, Abstracts, Bilbao, Spain, 2023.
@inproceedings{01H40CN1BZBQ2C78YG44WAWGHR,
  abstract     = {{Objective
To identify which dynamic contrast-enhanced (DCE-)MRI features best predict histological response to neoadjuvant chemotherapy in patients with an osteosarcoma.

Methods
Patients with osteosarcoma who underwent DCE-MRI before and after neoadjuvant chemotherapy prior to resection were retrospectively included at two different centers. Data from the center with the larger cohort (training cohort) was used to identify which method for region-of-interest selection (whole slab or focal area method) and which change in DCE-MRI features (time to enhancement, wash-in rate, maximum relative enhancement and area under the curve) gave the most accurate prediction of histological response. Models were created using logistic regression and cross-validated. The most accurate model was then externally validated using data from the other center (test cohort).

Results
Fifty-five (27 poor response) and 30 (19 poor response) patients were included in training and test cohorts, respectively. Intraclass correlation coefficient of relative DCE-MRI features ranged 0.81–0.97 with the whole slab and 0.57–0.85 with the focal area segmentation method. Poor histological response was best predicted with the whole slab segmentation method using a single feature threshold, relative wash-in rate <2.3. Mean accuracy was 0.85 (95%CI: 0.75–0.95), and area under the receiver operating characteristic curve (AUC-index) was 0.93 (95%CI: 0.86–1.00). In external validation, accuracy and AUC-index were 0.80 and 0.80.

Conclusion
In this study, a relative wash-in rate of <2.3 determined with the whole slab segmentation method predicted histological response to neoadjuvant chemotherapy in osteosarcoma. Consistent performance was observed in an external test cohort.}},
  author       = {{Van Den Berghe, Thomas and Kalisvaart, Gijsbert M. and Grootjans, Willem and Lejoly, Maryse and Huysse, Wouter and Bovée, Judith V.M.G. and Creytens, David and Gelderblom, Hans and Speetjens, Frank M. and van de Sande, Michiel A.J. and de Geus-Oei, Lioe-Fee and Verstraete, Koenraad and Bloem, Johannes L.}},
  booktitle    = {{2023 ESSR Annual Scientific Meeting, Abstracts}},
  language     = {{eng}},
  location     = {{Bilbao, Spain}},
  publisher    = {{2023 ESSR Annual Scientific Meeting}},
  title        = {{Predicting pathological response to neoadjuvant chemotherapy in osteosarcoma using dynamic contrast-enhanced MRI : internal and external validation of a semi-quantitative model}},
  year         = {{2023}},
}