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Measurable imaging-based changes in enhancement of intrahepatic cholangiocarcinoma after radiotherapy reflect physical mechanisms of response.

Authors :
De B
Dogra P
Zaid M
Elganainy D
Sun K
Amer AM
Wang C
Rooney MK
Chang E
Kang HC
Wang Z
Bhosale P
Odisio BC
Newhook TE
Tzeng CD
Cao HST
Chun YS
Vauthey JN
Lee SS
Kaseb A
Raghav K
Javle M
Minsky BD
Noticewala SS
Holliday EB
Smith GL
Koong AC
Das P
Cristini V
Ludmir EB
Koay EJ
Source :
MedRxiv : the preprint server for health sciences [medRxiv] 2024 Sep 12. Date of Electronic Publication: 2024 Sep 12.
Publication Year :
2024

Abstract

Background: Although escalated doses of radiation therapy (RT) for intrahepatic cholangiocarcinoma (iCCA) are associated with durable local control (LC) and prolonged survival, uncertainties persist regarding personalized RT based on biological factors. Compounding this knowledge gap, the assessment of RT response using traditional size-based criteria via computed tomography (CT) imaging correlates poorly with outcomes. We hypothesized that quantitative measures of enhancement would more accurately predict clinical outcomes than size-based assessment alone and developed a model to optimize RT.<br />Methods: Pre-RT and post-RT CT scans of 154 patients with iCCA were analyzed retrospectively for measurements of tumor dimensions (for RECIST) and viable tumor volume using quantitative European Association for Study of Liver (qEASL) measurements. Binary classification and survival analyses were performed to evaluate the ability of qEASL to predict treatment outcomes, and mathematical modeling was performed to identify the mechanistic determinants of treatment outcomes and to predict optimal RT protocols.<br />Results: Multivariable analysis accounting for traditional prognostic covariates revealed that percentage change in viable volume following RT was significantly associated with OS, outperforming stratification by RECIST. Binary classification identified ≥33% decrease in viable volume to optimally correspond to response to RT. The model-derived, patient-specific tumor enhancement growth rate emerged as the dominant mechanistic determinant of treatment outcome and yielded high accuracy of patient stratification (80.5%), strongly correlating with the qEASL-based classifier.<br />Conclusion: Following RT for iCCA, changes in viable volume outperformed radiographic size-based assessment using RECIST for OS prediction. CT-derived tumor-specific mathematical parameters may help optimize RT for resistant tumors.<br />Competing Interests: Conflicts of interest: BD reports honoraria from Sermo, Inc and funding from the Radiological Society of North America. EBH reports grants from Merck Serono. CMT reports a consulting/advisory role with Accuray. ACK reports ownership of shares in Aravive, Inc. PD reports honoraria from ASTRO, ASCO, Imedex, and Bayer. EJK reports grants from National Institutes of Health, Stand Up 2 Cancer, MD Anderson Cancer Center, Philips Healthcare, Elekta, and GE Healthcare; personal fees from RenovoRx and Taylor and Francis; and a consulting/advisory role with Augmenix. All reported conflicts are outside the current work.

Details

Language :
English
Database :
MEDLINE
Journal :
MedRxiv : the preprint server for health sciences
Publication Type :
Academic Journal
Accession number :
39314943
Full Text :
https://doi.org/10.1101/2024.09.11.24313334