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21 pages, 1196 KiB

Open AccessArticle

Dosiomics-Based Prediction of Radiation-Induced Valvulopathy after Childhood Cancer

by Stefania Chounta, Rodrigue Allodji, Maria Vakalopoulou, Mahmoud Bentriou, Duyen Thi Do, Florent De Vathaire, Ibrahima Diallo, Brice Fresneau, Thibaud Charrier, Vincent Zossou, Stergios Christodoulidis, Sarah Lemler and Veronique Letort Le Chevalier

Cancers 2023, 15(12), 3107; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15123107 - 08 Jun 2023

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Abstract

Valvular Heart Disease (VHD) is a known late complication of radiotherapy for childhood cancer (CC), and identifying high-risk survivors correctly remains a challenge. This paper focuses on the distribution of the radiation dose absorbed by heart tissues. We propose that a dosiomics signature [...] Read more.

Valvular Heart Disease (VHD) is a known late complication of radiotherapy for childhood cancer (CC), and identifying high-risk survivors correctly remains a challenge. This paper focuses on the distribution of the radiation dose absorbed by heart tissues. We propose that a dosiomics signature could provide insight into the spatial characteristics of the heart dose associated with a VHD, beyond the already-established risk induced by high doses. We analyzed data from the 7670 survivors of the French Childhood Cancer Survivors’ Study (FCCSS), 3902 of whom were treated with radiotherapy. In all, 63 (1.6%) survivors that had been treated with radiotherapy experienced a VHD, and 57 of them had heterogeneous heart doses. From the heart–dose distribution of each survivor, we extracted 93 first-order and spatial dosiomics features. We trained random forest algorithms adapted for imbalanced classification and evaluated their predictive performance compared to the performance of standard mean heart dose (MHD)-based models. Sensitivity analyses were also conducted for sub-populations of survivors with spatially heterogeneous heart doses. Our results suggest that MHD and dosiomics-based models performed equally well globally in our cohort and that, when considering the sub-population having received a spatially heterogeneous dose distribution, the predictive capability of the models is significantly improved by the use of the dosiomics features. If these findings are further validated, the dosiomics signature may be incorporated into machine learning algorithms for radiation-induced VHD risk assessment and, in turn, into the personalized refinement of follow-up guidelines. Full article

(This article belongs to the Special Issue Analysis of Cancer Radiotherapy)

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15 pages, 2129 KiB

Open AccessArticle

Good Timing Matters: The Spatially Fractionated High Dose Rate Boost Should Come First

by Elisabeth Schültke, Felix Jaekel, Stefan Bartzsch, Elke Bräuer-Krisch, Herwig Requardt, Jean Albert Laissue, Hans Blattmann and Guido Hildebrandt

Cancers 2022, 14(23), 5964; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14235964 - 02 Dec 2022

Cited by 2 | Viewed by 1097

Abstract

Monoplanar microbeam irradiation (MBI) and pencilbeam irradiation (PBI) are two new concepts of high dose rate radiotherapy, combined with spatial dose fractionation at the micrometre range. In a small animal model, we have explored the concept of integrating MBI or PBI as a [...] Read more.

Monoplanar microbeam irradiation (MBI) and pencilbeam irradiation (PBI) are two new concepts of high dose rate radiotherapy, combined with spatial dose fractionation at the micrometre range. In a small animal model, we have explored the concept of integrating MBI or PBI as a simultaneously integrated boost (SIB), either at the beginning or at the end of a conventional, low-dose rate schedule of 5x4 Gy broad beam (BB) whole brain radiotherapy (WBRT). MBI was administered as array of 50 µm wide, quasi-parallel microbeams. For PBI, the target was covered with an array of 50 µm × 50 µm pencilbeams. In both techniques, the centre-to-centre distance was 400 µm. To assure that the entire brain received a dose of at least 4 Gy in all irradiated animals, the peak doses were calculated based on the daily BB fraction to approximate the valley dose. The results of our study have shown that the sequence of the BB irradiation fractions and the microbeam SIB is important to limit the risk of acute adverse effects, including epileptic seizures and death. The microbeam SIB should be integrated early rather than late in the irradiation schedule. Full article

(This article belongs to the Special Issue Analysis of Cancer Radiotherapy)

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15 pages, 1883 KiB

Open AccessArticle

Dose-Response Analysis Describes Particularly Rapid Repopulation of Non-Small Cell Lung Cancer during Concurrent Chemoradiotherapy

by Huei-Tyng Huang, Michael G. Nix, Douglas H. Brand, David Cobben, Crispin T. Hiley, John D. Fenwick and Maria A. Hawkins

Cancers 2022, 14(19), 4869; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14194869 - 05 Oct 2022

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Abstract

(1) Purpose: We analysed overall survival (OS) rates following radiotherapy (RT) and chemo-RT of locally-advanced non-small cell lung cancer (LA-NSCLC) to investigate whether tumour repopulation varies with treatment-type, and to further characterise the low α/β ratio found in a previous study. [...] Read more.

(1) Purpose: We analysed overall survival (OS) rates following radiotherapy (RT) and chemo-RT of locally-advanced non-small cell lung cancer (LA-NSCLC) to investigate whether tumour repopulation varies with treatment-type, and to further characterise the low α/β ratio found in a previous study. (2) Materials and methods: Our dataset comprised 2-year OS rates for 4866 NSCLC patients (90.5% stage IIIA/B) belonging to 51 cohorts treated with definitive RT, sequential chemo-RT (sCRT) or concurrent chemo-RT (cCRT) given in doses-per-fraction ≤3 Gy over 16–60 days. Progressively more detailed dose-response models were fitted, beginning with a probit model, adding chemotherapy effects and survival-limiting toxicity, and allowing tumour repopulation and α/β to vary with treatment-type and stage. Models were fitted using the maximum-likelihood technique, then assessed via the Akaike information criterion and cross-validation. (3) Results: The most detailed model performed best, with repopulation offsetting 1.47 Gy/day (95% confidence interval, CI: 0.36, 2.57 Gy/day) for cCRT but only 0.30 Gy/day (95% CI: 0.18, 0.47 Gy/day) for RT/sCRT. The overall fitted tumour α/β ratio was 3.0 Gy (95% CI: 1.6, 5.6 Gy). (4) Conclusion: The fitted repopulation rates indicate that cCRT schedule durations should be shortened to the minimum in which prescribed doses can be tolerated. The low α/β ratio suggests hypofractionation should be efficacious. Full article

(This article belongs to the Special Issue Analysis of Cancer Radiotherapy)

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