Dose-response curves for MRI-detected radiation-induced temporal lobe reactions in patients after proton and carbon ion therapy: Does the same RBE-weighted dose lead to the same biological effect?

Possibilities and challenges when using synthetic computed tomography in an adaptive carbon-ion treatment workflow

BACKGROUND AND PURPOSE

Anatomical surveillance during ion-beam therapy is the basis for an effective tumor treatment and optimal organ at risk (OAR) sparing. Synthetic computed tomography (sCT) based on magnetic resonance imaging (MRI) can replace the X-ray based planning CT (X-rayCT) in photon radiotherapy and improve the workflow efficiency without additional imaging dose. The extension to carbon-ion radiotherapy is highly challenging; complex patient positioning, unique anatomical situations, distinct horizontal and vertical beam incidence directions, and limited training data are only few problems. This study gives insight into the possibilities and challenges of using sCTs in carbon-ion therapy.

MATERIALS AND METHODS

For head and neck patients immobilised with thermoplastic masks 30 clinically applied actively scanned carbon-ion treatment plans on 15 CTs comprising 60 beams were analyzed. Those treatment plans were re-calculated on MRI based sCTs which were created employing a 3D U-Net. Dose differences and carbon-ion spot displacements between sCT and X-rayCT were evaluated on a patient specific basis.

RESULTS

Spot displacement analysis showed a peak displacement by 0.2 cm caused by the immobilisation mask not measurable with the MRI. 95.7% of all spot displacements were located within 1 cm. For the clinical target volume (CTV) the median D_50% agreed within -0.2% (-1.3 to 1.4%), while the median D_0.01cc differed up to 4.2% (-1.3 to 25.3%) comparing the dose distribution on the X-rayCT and the sCT. OAR deviations depended strongly on the position and the dose gradient. For three patients no deterioration of the OAR parameters was observed. Other patients showed large deteriorations, e.g. for one patient D_2% of the chiasm differed by 28.1%.

CONCLUSION

The usage of sCTs opens several new questions, concluding that we are not ready yet for an MR-only workflow in carbon-ion therapy, as envisaged in photon therapy. Although omitting the X-rayCT seems unfavourable in the case of carbon-ion therapy, an sCT could be advantageous for monitoring, re-planning, and adaptation.

NTCP modelling for high-grade temporal radionecrosis in a large cohort of patients receiving pencil beam scanning proton therapy for skull base and head and neck tumors

PURPOSE/OBJECTIVES

To develop a normal tissue complication probability (NTCP) model including clinical and dosimetric parameters for high-grade temporal lobe radionecroses (TRN) after pencil beam scanning (PBS) proton therapy (PT).

MATERIALS/METHODS

Data of 299 patients with skull base and Head and Neck tumors treated with PBS PT with a total dose of ≥60 Gy_RBE from 05/2004-11/2018 were included. Patients with a ≥ grade (G) 2 TRN (CTCAE v5.0 criteria) were considered as having a high-grade TRN. Nine clinical and 27 dosimetric parameters were considered for structure-wise modelling. After elimination of strongly cross-correlated variables, logistic regression models were generated using penalized LASSO regression. Bootstrapping was performed to assess parameter selection robustness. Model performance was evaluated via cross-correlation by assessing the area under the curve of receiver operating characteristic curves (AUC-ROC) and calibration with a Hosmer-Lemeshow test statistic.

RESULTS

After a median radiological follow-up of 51.5 months (range, 4-190), 27 (9%) patients developed a ≥ G2 TRN. Eleven patients had bitemporal necrosis, resulting in 38 events in 598 temporal lobes for structure-wise analysis. During Bootstrapping analysis, the highest selection frequency was found for prescription dose (PD), followed by Age, V_40Gy[%], Hypertension (HBP) and D_1cc[Gy]. During cross validation Age*PD* D_1cc[Gy]*HBP was superior in all described test statistics. Full cohort structure wise and patient wise models were built with a maximum AUC-ROC of 0.79 (structure-wise) and 0.76 (patient-wise).

CONCLUSION

While developing a logistic regression NTCP model to predict ≥ G2 TRN, the best fit was found for the model containing Age, PD, D_1cc[Gy] and HBP as risk factors. External validation will be the next step to improve generalizability and potential introduction into clinical routine.

Predicted probabilities of brain injury after carbon ion radiotherapy for head and neck and skull base tumors in long-term survivors

BACKGROUND AND PURPOSE

We aimed to determine the risk factors for radiation-induced brain injury (RIBI¹) after carbon ion radiotherapy (CIRT) to predict their probabilities in long-term survivors.

MATERIALS AND METHODS

We evaluated 104 patients with head, neck, and skull base tumors who underwent CIRT in a regimen of 32 fractions and were followed up for at least 24 months. RIBI was assessed using the Common Terminology Criteria for Adverse Events.

RESULTS

The median follow-up period was 45.5 months; 19 (18.3 %) patients developed grade ≥2 RIBI. The maximal absolute dose covering 5 mL of the brain (D5ml) was the only significant risk factor for grade ≥2 RIBI in the multivariate logistic regression analysis (p = 0.001). The tolerance doses of D5ml for the 5% and 50% probabilities of developing grade ≥2 RIBI were estimated to be 55.4 Gy (relative biological effectiveness [RBE]) and 68.4 Gy (RBE) by a logistic model, respectively.

CONCLUSION

D5ml was most significantly associated with grade ≥2 RIBI and may enable the prediction of its probability.

Brainstem NTCP and Dose Constraints for Carbon Ion RT-Application and Translation From Japanese to European RBE-Weighted Dose

Background and Purpose

The Italian National Center of Oncological Hadrontherapy (CNAO) has applied dose constraints for carbon ion RT (CIRT) as defined by Japan’s National Institute of Radiological Sciences (NIRS). However, these institutions use different models to predict the relative biological effectiveness (RBE). CNAO applies the Local Effect Model I (LEM I), which in most clinical situations predicts higher RBE than NIRS’s Microdosimetric Kinetic Model (MKM). Equal constraints therefore become more restrictive at CNAO. Tolerance doses for the brainstem have not been validated for LEM I-weighted dose (D_{LEM I}). However, brainstem constraints and a Normal Tissue Complication Probability (NTCP) model were recently reported for MKM-weighted dose (D_MKM), showing that a constraint relaxation to D_{MKM|0.7 cm³} <30 Gy (RBE) and D_{MKM|0.1 cm³} <40 Gy (RBE) was feasible. The aim of this work was to evaluate the brainstem NTCP associated with CNAO’s current clinical practice and to propose new brainstem constraints for LEM I-optimized CIRT at CNAO.

Material and Methods

We reproduced the absorbed dose of 30 representative patient treatment plans from CNAO. Subsequently, we calculated both D_{LEM I} and D_MKM, and the relationship between D_MKM and D_{LEM I} for various brainstem dose metrics was analyzed. Furthermore, the NTCP model developed for D_MKM was applied to estimate the NTCPs of the delivered plans.

Results

The translation of CNAO treatment plans to D_MKM confirmed that the former CNAO constraints were conservative compared with D_MKM constraints. Estimated NTCPs were 0% for all but one case, in which the NTCP was 2%. The relationship D_MKM/D_{LEM I} could be described by a quadratic regression model which revealed that the validated D_MKM constraints corresponded to D_{LEM I|0.7 cm³} <41 Gy (RBE) (95% CI, 38–44 Gy (RBE)) and D_{LEM I|0.1 cm³} <49 Gy (RBE) (95% CI, 46–52 Gy (RBE)).

Conclusion

Our study demonstrates that RBE-weighted dose translation is of crucial importance in order to exchange experience and thus harmonize CIRT treatments globally. To mitigate uncertainties involved, we propose to use the lower bound of the 95% CI of the translation estimates, i.e., D_{LEM I|0.7 cm³} <38 Gy (RBE) and D_{LEM I|0.1 cm³} <46 Gy (RBE) as brainstem dose constraints for 16 fraction CIRT treatments optimized with LEM I.

Radiation biology considerations of proton therapy for gastrointestinal cancers

Clinical enthusiasm for proton therapy (PT) is high, with an exponential increase in the number of centers offering treatment. Attraction for this charged particle therapy modality stems from the favorable proton dose distribution, with low radiation dose absorption on entry and maximum radiation deposition at the Bragg peak. The current clinical convention is to use a fixed relative biological effectiveness (RBE) value of 1.1 in order to correct the physical dose relative to photon therapy (i.e., proton radiation is 10% more biologically effective then photon radiation). In recent years, concerns about the potential side effects of PT have emerged. Various studies and review articles have sought to better quantify the RBE of PT and shine some light on the complexity of this problem. Reduction in biologic hot spots of non-target tissue is paramount in proton radiation therapy (RT) planning as the primary benefit of proton RT is a reduction in organ at risk (OAR) irradiation. New and emerging clinical data is in support of variable proton biological effectiveness and demonstrate late toxicity, presumably associated with high biological dose, to OAR. Overall, PT has promise to treat many cancer sites with similar efficacy as conventional RT but with fewer acute and late toxicities. However, further knowledge of biologic effective dose and its impact on both cancer and adjacent OAR is paramount for effective and safe treatment of patients with PT.

RBE-weighted doses in target volumes of chordoma and chondrosarcoma patients treated with carbon ion radiotherapy: Comparison of local effect models I and IV

BACKGROUND AND PURPOSE

To compare the relative biological effectiveness (RBE)-weighted dose distributions in the target volume of chordoma and chondrosarcoma patients when using two different versions of the local effect model (LEM I vs. IV) under identical conditions.

MATERIALS AND METHODS

The patient collective included 59 patients treated with 20 fractions of carbon ion radiotherapy for chordoma and low-grade chondrosarcoma of the skull base at the Helmholtzzentrum für Schwerionenforschung (GSI) in 2002 and 2003. Prescribed doses to the planning target volume (PTV) were 60 (n = 49), 66 (n = 2) and 70 (n = 8) Gy (RBE). The original treatment plans that were initially biologically optimized with LEM I, were now recalculated using LEM IV based on the absorbed dose distributions. The resulting RBE-weighted dose distributions were quantitatively compared to assess the clinical impact of LEM IV relative to LEM I in the target volume.

RESULTS

LEM IV predicts 20-30 Gy (RBE) increased maximum doses as compared to LEM I, while minimum doses are decreased by 2-5 Gy (RBE). Population-based mean and median doses deviated by less than 2 Gy (RBE) between both models.

CONCLUSIONS

LEM I and LEM IV-based RBE-weighted doses in the target volume may be significantly different. Replacing the applied model in patient treatments may therefore lead to local over- or underdosages in the tumor. If LEM IV is to be tested clinically, comparisons of the RBE-weighted dose distributions of both models are required for the individual patients to assess whether the LEM IV-plan would also be acceptable and prescribed dose as well as clinical outcome data have to be carefully reassessed.

Simultaneous optimization of RBE-weighted dose and nanometric ionization distributions in treatment planning with carbon ions

Inverse treatment planning in intensity modulated particle therapy (IMPT) with scanned carbon-ion beams is currently based on the optimization of RBE-weighted dose to satisfy requirements of target coverage and limited toxicity to organs-at-risk (OARs) and healthy tissues. There are many feasible IMPT plans that meet these requirements, which allows the introduction of further criteria to narrow the selection of a biologically optimal treatment plan. We propose a novel treatment planning strategy based on the simultaneous optimization of RBE-weighted dose and nanometric ionization details (ID) as a new physical characteristic of the delivered plan beyond LET. In particular, we focus on the distribution of large ionization clusters (more than 3 ionizations) to enhance the biological effect across the target volume while minimizing biological effect in normal tissues. Carbon-ion treatment plans for different patient geometries and beam configurations generated with the simultaneous optimization strategy were compared against reference plans obtained with RBE-weighted dose optimization alone. Quality indicators, inhomogeneity index and planning volume histograms of RBE-weighted dose and large ionization clusters were used to evaluate the treatment plans. We show that with simultaneous optimization, ID distributions can be optimized in carbon-ion radiotherapy without compromising the RBE-weighted dose distributions. This strategy can potentially be used to account for optimization of endpoints closely related to radiation quality to achieve better tumor control and reduce risks of complications.

A mechanistic relative biological effectiveness model-based biological dose optimization for charged particle radiobiology studies

In charged particle therapy, the objective is to exploit both the physical and radiobiological advantages of charged particles to improve the therapeutic index. Use of the beam scanning technique provides the flexibility to implement biological dose optimized intensity-modulated ion therapy (IMIT). An easy-to-implement algorithm was developed in the current study to rapidly generate a uniform biological dose distribution, namely the product of physical dose and the relative biological effectiveness (RBE), within the target volume using scanned ion beams for charged particle radiobiological studies. Protons, helium ions and carbon ions were selected to demonstrate the feasibility and flexibility of our method. The general-purpose Monte Carlo simulation toolkit Geant4 was used for particle tracking and generation of physical and radiobiological data needed for later dose optimizations. The dose optimization algorithm was developed using the Python (version 3) programming language. A constant RBE-weighted dose (RWD) spread-out Bragg peak (SOBP) in a water phantom was selected as the desired target dose distribution to demonstrate the applicability of the optimization algorithm. The mechanistic repair-misrepair-fixation (RMF) model was incorporated into the Monte Carlo particle tracking to generate radiobiological parameters and was used to predict the RBE of cell survival in the iterative process of the biological dose optimization for the three selected ions. The post-optimization generated beam delivery strategy can be used in radiation biology experiments to obtain radiobiological data to further validate and improve the accuracy of the RBE model. This biological dose optimization algorithm developed for radiobiology studies could potentially be extended to implement biologically optimized IMIT plans for patients.