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Multiscale approach predictions for biological outcomes in ion-beam cancer therapy.

ABSTRACT: Ion-beam therapy provides advances in cancer treatment, offering the possibility of excellent dose localization and thus maximising cell-killing within the tumour. The full potential of such therapy can only be realised if the fundamental mechanisms leading to lethal cell damage under ion irradiation are well understood. The key question is whether it is possible to quantitatively predict macroscopic biological effects caused by ion radiation on the basis of physical and chemical effects related to the ion-medium interactions on a nanometre scale. We demonstrate that the phenomenon-based MultiScale Approach to the assessment of radiation damage with ions gives a positive answer to this question. We apply this approach to numerous experiments where survival curves were obtained for different cell lines and conditions. Contrary to other, in essence empirical methods for evaluation of macroscopic effects of ionising radiation, the MultiScale Approach predicts the biodamage based on the physical effects related to ionisation of the medium, transport of secondary particles, chemical interactions, thermo-mechanical pathways of biodamage, and heuristic biological criteria for cell survival. We anticipate this method to give great impetus to the practical improvement of ion-beam cancer therapy and the development of more efficient treatment protocols.

SUBMITTER: Verkhovtsev A

PROVIDER: S-EPMC4906349 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Multiscale approach predictions for biological outcomes in ion-beam cancer therapy.

Verkhovtsev Alexey A Surdutovich Eugene E Solov'yov Andrey V AV

Scientific reports 20160614

Ion-beam therapy provides advances in cancer treatment, offering the possibility of excellent dose localization and thus maximising cell-killing within the tumour. The full potential of such therapy can only be realised if the fundamental mechanisms leading to lethal cell damage under ion irradiation are well understood. The key question is whether it is possible to quantitatively predict macroscopic biological effects caused by ion radiation on the basis of physical and chemical effects related ...[more]

PMID: 27297618

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Project description:BackgroundHelium (4He) ion beam therapy provides favorable biophysical characteristics compared to currently administered particle therapies, i.e., reduced lateral scattering and enhanced biological damage to deep-seated tumors like heavier ions, while simultaneously lessened particle fragmentation in distal healthy tissues as observed with lighter protons. Despite these biophysical advantages, raster-scanning 4He ion therapy remains poorly explored e.g., clinical translational is hampered by the lack of reliable and robust estimation of physical and radiobiological uncertainties. Therefore, prior to the upcoming 4He ion therapy program at the Heidelberg Ion-beam Therapy Center (HIT), we aimed to characterize the biophysical phenomena of 4He ion beams and various aspects of the associated models for clinical integration.MethodsCharacterization of biological effect for 4He ion beams was performed in both homogenous and patient-like treatment scenarios using innovative models for estimation of relative biological effectiveness (RBE) in silico and their experimental validation using clonogenic cell survival as the gold-standard surrogate. Towards translation of RBE models in patients, the first GPU-based treatment planning system (non-commercial) for raster-scanning 4He ion beams was devised in-house (FRoG).ResultsOur data indicate clinically relevant uncertainty of ±5-10% across different model simulations, highlighting their distinct biological and computational methodologies. The in vitro surrogate for highly radio-resistant tissues presented large RBE variability and uncertainty within the clinical dose range.ConclusionsExisting phenomenological and mechanistic/biophysical models were successfully integrated and validated in both Monte Carlo and GPU-accelerated analytical platforms against in vitro experiments, and tested using pristine peaks and clinical fields in highly radio-resistant tissues where models exhibit the greatest RBE uncertainty. Together, these efforts mark an important step towards clinical translation of raster-scanning 4He ion beam therapy to the clinic.

Project description:PurposeAlthough both intensity-modulated radiation therapy (IMRT) and proton beam therapy (PBT) offer effective long-term disease control for localized prostate cancer (PCa), there are limited data directly comparing the 2 modalities.MethodsThe data from 334 patients treated with conventionally fractionated (79.2 GyRBE in 44 fractions) PBT or IMRT were retrospectively analyzed. Propensity score matching was used to balance factors associated with biochemical failure-free survival (BFFS). Age, race, and comorbidities (not BFFS associates) remained imbalanced after matching. Univariable and covariate-adjusted multivariable (MVA) Cox regression models were used to determine if modality affected BFFS.ResultsOf 334 patients, 176 (52.7%) were included in the matched cohort with exact matching to National Comprehensive Cancer Network (NCCN) risk group. With a median follow-up time of 9.0 years (interquartile range [IQR]: 7.8-10.2 years), long-term BFFS was similar between the IMRT and PBT matched arms with 8-year estimates of 85% (95% CI: 76%-91%) and 91% (95% CI: 82%-96%, P = .39), respectively. On MVA, modality was not significantly associated with BFFS in both the unmatched (hazard ratio [HR] = 0.75, 95% CI: 0.35-1.63, P = .47) and matched (HR = 0.87, 95% CI: 0.33-2.33, P = .78) cohorts. Prostate cancer-specific survival (PCSS) and overall survival (OS) were also similar (P > .05). However, in an unmatched analysis, the PBT arm had significantly fewer incidences of secondary cancers within the irradiated field (0.6%, 95% CI: 0.0%-3.1% versus 4.5%, 95% CI: 1.8%-9.0%, P = .028).ConclusionsBoth PBT and IMRT offer excellent long-term disease control for PCa, with no significant differences between the 2 modalities in BFFS, PCSS, and OS in matched patients. In the unmatched cohort, fewer incidences of secondary malignancy were noted in the PBT group; however, owing to overall low incidence of secondary cancer and imbalanced patient characteristics between the 2 groups, these data are strictly hypothesis generating and require further investigation.

Project description:Background and purposeCarbon ion radiation therapy (CIRT) is recognized as an effective alternative treatment modality for early stage lung cancer, but a quantitative understanding of relative biological effectiveness (RBE) compared to photon therapy is lacking. In this work, a mechanistic tumor response model previously validated for lung photon radiotherapy was used to estimate the RBE of CIRT compared to photon radiotherapy, as a function of dose and the fractionation schedule.Materials and methodsClinical outcome data of 9 patient cohorts (394 patients) treated with CIRT for early stage lung cancer, representing all published data, were included. Fractional dose, number of fractions, treatment schedule, and local control rates were used for model simulations relative to standard photon outcomes. Four parameters were fitted: α, α/β, and the oxygen enhancement ratios of cells either accessing only glucose, not oxygen (OERI), or cells dying from starvation (OERH). The resulting dose-response relationship of CIRT was compared with the previously determined dose-response relationship of photon radiotherapy for lung cancer, and an RBE of CIRT was derived.ResultsBest-fit CIRT parameters were: α = 1.12 Gy-1 [95%-CI: 0.97-1.26], α/β = 23.9 Gy [95%-CI: 8.9-38.9], and the oxygen induced radioresistance of hypoxic cell populations were characterized by OERI = 1.08 [95%-CI: 1.00-1.41] (cells lacking oxygen but not glucose), and OERH = 1.01 [95%-CI: 1.00-1.44] (cells lacking oxygen and glucose). Depending on dose and fractionation, the derived RBE ranges from 2.1 to 1.5, with decreasing values for larger fractional dose and fewer number of fractions.ConclusionFitted radiobiological parameters were consistent with known carbon in vitro radiobiology, and the resulting dose-response curve well-fitted the reported data over a wide range of dose-fractionation schemes. The same model, with only a few fitted parameters of clear mechanistic meaning, thus synthesizes both photon radiotherapy and CIRT clinical experience with early stage lung tumors.

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Multiscale approach predictions for biological outcomes in ion-beam cancer therapy.

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Multiscale approach predictions for biological outcomes in ion-beam cancer therapy.

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