Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer
Abstract Purpose Chemotherapy administration is a balancing act between giving enough to achieve the desired tumour response while limiting adverse effects. Chemotherapy dosing is based on body surface area (BSA). Emerging evidence suggests body composition plays a crucial role in the pharmacokineti...
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Springer
2025-05-01
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| Series: | Journal of Cancer Research and Clinical Oncology |
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| Online Access: | https://doi.org/10.1007/s00432-025-06219-5 |
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| author | Alex Besson Ke Cao Ahmed Mardinli Lara Wirth Josephine Yeung Rory Kokelaar Peter Gibbs Fiona Reid Justin M. Yeung |
| author_facet | Alex Besson Ke Cao Ahmed Mardinli Lara Wirth Josephine Yeung Rory Kokelaar Peter Gibbs Fiona Reid Justin M. Yeung |
| author_sort | Alex Besson |
| collection | DOAJ |
| description | Abstract Purpose Chemotherapy administration is a balancing act between giving enough to achieve the desired tumour response while limiting adverse effects. Chemotherapy dosing is based on body surface area (BSA). Emerging evidence suggests body composition plays a crucial role in the pharmacokinetic and pharmacodynamic profile of cytotoxic agents and could inform optimal dosing. This study aims to assess how lumbosacral body composition influences adverse events in patients receiving neoadjuvant chemotherapy for rectal cancer. Methods A retrospective study (February 2013 to March 2023) examined the impact of body composition on neoadjuvant treatment outcomes for rectal cancer patients. Staging CT scans were analysed using a validated AI model to measure lumbosacral skeletal muscle (SM), intramuscular adipose tissue (IMAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue volume and density. Multivariate analyses explored the relationship between body composition and chemotherapy outcomes. Results 242 patients were included (164 males, 78 Females), median age 63.4 years. Chemotherapy dose reductions occurred more frequently in females (26.9% vs. 15.9%, p = 0.042) and in females with greater VAT density (-82.7 vs. -89.1, p = 0.007) and SM: IMAT + VAT volume ratio (1.99 vs. 1.36, p = 0.042). BSA was a poor predictor of dose reduction (AUC 0.397, sensitivity 38%, specificity 60%) for female patients, whereas the SM: IMAT + VAT volume ratio (AUC 0.651, sensitivity 76%, specificity 61%) and VAT density (AUC 0.699, sensitivity 57%, specificity 74%) showed greater predictive ability. Body composition didn’t influence dose adjustment of male patients. Conclusion Lumbosacral body composition outperformed BSA in predicting adverse events in female patients with rectal cancer undergoing neoadjuvant chemotherapy. |
| format | Article |
| id | doaj-art-5510ef192e094da9bdfc2b83a776e2af |
| institution | DOAJ |
| issn | 1432-1335 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Springer |
| record_format | Article |
| series | Journal of Cancer Research and Clinical Oncology |
| spelling | doaj-art-5510ef192e094da9bdfc2b83a776e2af2025-08-20T02:39:23ZengSpringerJournal of Cancer Research and Clinical Oncology1432-13352025-05-0115151710.1007/s00432-025-06219-5Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancerAlex Besson0Ke Cao1Ahmed Mardinli2Lara Wirth3Josephine Yeung4Rory Kokelaar5Peter Gibbs6Fiona Reid7Justin M. Yeung8Department of Surgery - Western Precinct, The University of MelbourneDepartment of Surgery - Western Precinct, The University of MelbourneDepartment of Surgery - Western Precinct, The University of MelbourneDepartment of Surgery - Western Precinct, The University of MelbourneDepartment of Surgery - Western Precinct, The University of MelbourneDepartment of Surgery - Western Precinct, The University of MelbourneWalter and Eliza Hall Institute, ParkvilleDepartment of Surgery - Western Precinct, The University of MelbourneDepartment of Surgery - Western Precinct, The University of MelbourneAbstract Purpose Chemotherapy administration is a balancing act between giving enough to achieve the desired tumour response while limiting adverse effects. Chemotherapy dosing is based on body surface area (BSA). Emerging evidence suggests body composition plays a crucial role in the pharmacokinetic and pharmacodynamic profile of cytotoxic agents and could inform optimal dosing. This study aims to assess how lumbosacral body composition influences adverse events in patients receiving neoadjuvant chemotherapy for rectal cancer. Methods A retrospective study (February 2013 to March 2023) examined the impact of body composition on neoadjuvant treatment outcomes for rectal cancer patients. Staging CT scans were analysed using a validated AI model to measure lumbosacral skeletal muscle (SM), intramuscular adipose tissue (IMAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue volume and density. Multivariate analyses explored the relationship between body composition and chemotherapy outcomes. Results 242 patients were included (164 males, 78 Females), median age 63.4 years. Chemotherapy dose reductions occurred more frequently in females (26.9% vs. 15.9%, p = 0.042) and in females with greater VAT density (-82.7 vs. -89.1, p = 0.007) and SM: IMAT + VAT volume ratio (1.99 vs. 1.36, p = 0.042). BSA was a poor predictor of dose reduction (AUC 0.397, sensitivity 38%, specificity 60%) for female patients, whereas the SM: IMAT + VAT volume ratio (AUC 0.651, sensitivity 76%, specificity 61%) and VAT density (AUC 0.699, sensitivity 57%, specificity 74%) showed greater predictive ability. Body composition didn’t influence dose adjustment of male patients. Conclusion Lumbosacral body composition outperformed BSA in predicting adverse events in female patients with rectal cancer undergoing neoadjuvant chemotherapy.https://doi.org/10.1007/s00432-025-06219-5Rectal cancerChemotherapyDose modificationBody compositionArtificial intelligence |
| spellingShingle | Alex Besson Ke Cao Ahmed Mardinli Lara Wirth Josephine Yeung Rory Kokelaar Peter Gibbs Fiona Reid Justin M. Yeung Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer Journal of Cancer Research and Clinical Oncology Rectal cancer Chemotherapy Dose modification Body composition Artificial intelligence |
| title | Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer |
| title_full | Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer |
| title_fullStr | Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer |
| title_full_unstemmed | Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer |
| title_short | Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer |
| title_sort | artificial intelligence generated 3d body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer |
| topic | Rectal cancer Chemotherapy Dose modification Body composition Artificial intelligence |
| url | https://doi.org/10.1007/s00432-025-06219-5 |
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