Current colorectal cancer chemotherapy dosing limitations and novel assessments to personalize treatments

Arafat, Yasser; Loft, Matthew; Cao, Ke; Reid, Fiona; Kosmider, Suzanne; Lee, Margret; Gibbs, Peter; Faragher, Ian

doi:10.1111/ans.18046

Cited by 5 publications

(6 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Body composition measurements, in particular SM surface area, have been associated with rectal cancer response to neoadjuvant therapy and corresponding survival outcomes [ 23 , 24 ]. Furthermore, body composition has been suggested as a superior method of dosing chemotherapy for CRC, to decrease rates of dose-limiting toxicity [ 8 , 25 ]. Currently, 2D body composition is still commonly measured as there is limited clinically validated software available for researchers and clinicians to use.…”

Section: Discussionmentioning

confidence: 99%

Identification of Differences in Body Composition Measures Using 3D-Derived Artificial Intelligence from Multiple CT Scans across the L3 Vertebra Compared to a Single Mid-Point L3 CT Scan

Cao,

Yeung,

Arafat

et al. 2023

Radiology Research and Practice

Self Cite

View full text Add to dashboard Cite

Purpose. Body composition analysis in colorectal cancer (CRC) typically utilises a single 2D-abdominal axial CT slice taken at the mid-L3 level. The use of artificial intelligence (AI) allows for analysis of the entire L3 vertebra (non-mid-L3 and mid-L3). The goal of this study was to determine if the use of an AI approach offered any additional information on capturing body composition measures. Methods. A total of 2203 axial CT slices of the entire L3 level (4–46 slices were available per patient) were retrospectively collected from 203 CRC patients treated at Western Health, Melbourne (97 males; 47.8%). A pretrained artificial intelligence (AI) model was used to segment muscle, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) on these slices. The difference in body composition measures between mid-L3 and non-mid-L3 scans was compared for each patient, and for males and females separately. Results. Body composition measures derived from non-mid-L3 scans exhibited a median range of 0.85% to 6.28% (average percent difference) when compared to the use of a single mid-L3 scan. Significant variation in the VAT surface area ( p = 0.02) was observed in females compared to males, whereas male patients exhibited a greater variation in SAT surface area ( p < 0.001) and radiodensity ( p = 0.007). Conclusion. Significant differences in various body composition measures were observed when comparing non-mid-L3 slices to only the mid-L3 slice. Researchers should be aware that considering only the use of a single midpoint L3 CT scan slice will impact the estimate of body composition measurements.

show abstract

Section: Discussionmentioning

confidence: 99%

Identification of Differences in Body Composition Measures Using 3D-Derived Artificial Intelligence from Multiple CT Scans across the L3 Vertebra Compared to a Single Mid-Point L3 CT Scan

Cao,

Yeung,

Arafat

et al. 2023

Radiology Research and Practice

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, many CRC patients receiving chemotherapy experience significant toxic side effects and dose-limiting toxicities (DLT) (Health 2017 ). This may necessitate dose reduction or discontinuation of their treatment, ultimately resulting in decreased cancer treatment efficacy and suboptimal clinical outcomes (Starobova and Vetter 2017 ; Arafat 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Can AI-based body composition assessment outperform body surface area in predicting dose-limiting toxicities for colonic cancer patients on chemotherapy?

Cao

Arafat

Choi

et al. 2023

J Cancer Res Clin Oncol

Self Cite

View full text Add to dashboard Cite

Purpose Gold standard chemotherapy dosage is based on body surface area (BSA); however many patients experience dose-limiting toxicities (DLT). We aimed to evaluate the effectiveness of BSA, two-dimensional (2D) and three-dimensional (3D) body composition (BC) measurements derived from Lumbar 3 vertebra (L3) computed tomography (CT) slices, in predicting DLT in colon cancer patients. Methods 203 patients (60.87 ± 12.42 years; 97 males, 47.8%) receiving adjuvant chemotherapy (Oxaliplatin and/or 5-Fluorouracil) were retrospectively evaluated. An artificial intelligence segmentation model was used to extract 2D and 3D body composition measurements from each patients' single mid-L3 CT slice as well as multiple-L3 CT scans to produce a 3D BC report. DLT was defined as any incidence of dose reduction or discontinuation due to chemotherapy toxicities. A receiver operating characteristic (ROC) analysis was performed on BSA and individual body composition measurements to demonstrate their predictive performance. Results A total of 120 (59.1%) patients experienced DLT. Age and BSA did not vary significantly between DLT and non-DLT group. Females were significantly more likely to experience DLT (p = 4.9 × 10–3). In all patients, the predictive effectiveness of 2D body composition measurements (females: AUC = 0.50–0.54; males: AUC = 0.50–0.61) was equivalent to that of BSA (females: AUC = 0.49; males: AUC = 0.58). The L3 3D skeletal muscle volume was the most predictive indicator of DLT (AUC of 0.66 in females and 0.64 in males). Conclusion Compared to BSA and 2D body composition measurements, 3D L3 body composition measurements had greater potential to predict DLT in CRC patients receiving chemotherapy and this was sex dependent.

show abstract

“…Still, these methods also cause serious side effects on healthy organ function. [2][3][4][5] Therefore, the development of novel cancer treatment strategies that minimize side effects is crucial. In recent years, phototherapy, involving photodynamic therapy (PDT) and photothermal therapy (PTT), has been acknowledged as one of the most representative therapeutic strategies due to its noninvasiveness, low toxicity, low side effects, and high targeting selectivity.…”

Section: Introductionmentioning

confidence: 99%

A near-infrared and lysosome-targeted BODIPY photosensitizer for photodynamic and photothermal synergistic therapy

Liu,

Gao,

et al. 2023

Org. Biomol. Chem.

View full text Add to dashboard Cite

show abstract

Current colorectal cancer chemotherapy dosing limitations and novel assessments to personalize treatments

Cited by 5 publications

References 15 publications

Identification of Differences in Body Composition Measures Using 3D-Derived Artificial Intelligence from Multiple CT Scans across the L3 Vertebra Compared to a Single Mid-Point L3 CT Scan

Identification of Differences in Body Composition Measures Using 3D-Derived Artificial Intelligence from Multiple CT Scans across the L3 Vertebra Compared to a Single Mid-Point L3 CT Scan

Can AI-based body composition assessment outperform body surface area in predicting dose-limiting toxicities for colonic cancer patients on chemotherapy?

A near-infrared and lysosome-targeted BODIPY photosensitizer for photodynamic and photothermal synergistic therapy

Contact Info

Product

Resources

About