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Abstract Background To introduce and compare multiple biological effectiveness guided (BG) proton plan optimization strategies minimizing variable relative biological effectiveness (RBE) induced dose burden in organs at risk (OAR) while maintaining plan quality with a constant RBE. Methods Dose-optimized (DOSEopt) proton pencil beam scanning reference treatment plans were generated for ten cranial patients with prescription doses ≥ 54 Gy(RBE) and ≥ 1 OAR close to the clinical target volume (CTV). For each patient, four additional BG plans were created. BG objectives minimized either proton track-ends, dose-averaged linear energy transfer (LETd), energy depositions from high-LET protons or variable RBE-weighted dose (DRBE) in adjacent serially structured OARs. Plan quality (RBE = 1.1) was assessed by CTV dose coverage and robustness (2 mm setup, 3.5% density), dose homogeneity and conformity in the planning target volumes and adherence to OAR tolerance doses. LETd, DRBE (Wedenberg model, α/βCTV = 10 Gy, α/βOAR = 2 Gy) and resulting normal tissue complication probabilities (NTCPs) for blindness and brainstem necrosis were derived. Differences between DOSEopt and BG optimized plans were assessed and statistically tested (Wilcoxon signed rank, α = 0.05). Results All plans were clinically acceptable. DOSEopt and BG optimized plans were comparable in target volume coverage, homogeneity and conformity. For recalculated DRBE in all patients, all BG plans significantly reduced near-maximum DRBE to critical OARs with differences up to 8.2 Gy(RBE) (p

Background: Proton spatially fractionated RT (SFRT) can potentially synergize the unique advantages of using proton Bragg peak and SFRT peak‐valley dose ratio (PVDR) to reduce the radiation‐induced damage for normal tissues. Uniform‐target‐dose (UTD) proton GRID is a proton SFRT modality that can be clinically desirable and conveniently adopted since its UTD resembles target dose distribution in conventional proton RT (CONV). However, UTD proton GRID is not used clinically, which is likely due to the lack of an effective treatment planning method. Purpose: This work will develop a novel treatment planning method using scissor beams (SB) for UTD proton GRID, with the joint optimization of PVDR and dose objectives. Methods: The SB method for spatial dose modulation in normal tissues with UTD has two steps: (1) a primary beam (PB) is halved with interleaved beamlets, to generate spatial dose modulation in normal tissues; (2) a complementary beam (CB) is added to fill in previously valley‐dose positions in the target to generate UTD, while the CB is angled slightly from the PB, to maintain spatial dose modulation in normal tissues. A treatment planning method with PVDR optimization via the joint total variation and L1 (TVL1) regularization is developed to jointly optimize PVDR and dose objectives. The plan optimization solution is obtained using an iterative convex relaxation algorithm. Results: The new methods SB and SB‐TVL1 were validated in comparison with CONV. Compared to CONV of relatively homogeneous dose distribution, SB had modulated spatial dose pattern in normal tissues with UTD and comparable plan quality. Compared to SB, SB‐TVL1 further maximized PVDR, with comparable dose‐volume parameters. Conclusions: A novel SB method is proposed that can generate modulated spatial dose pattern in normal tissues to achieve UTD proton GRID. A treatment planning method with PVDR optimization capability via TVL1 regularization is developed that can jointly optimize PVDR and dose objectives for proton GRID. [ABSTRACT FROM AUTHOR]

Background: Carbon ion beams are well accepted as densely ionizing radiation with a high linear energy transfer (LET). However, the current clinical practice does not fully exploit the highest possible dose‐averaged LET (LETd) and, consequently, the biological potential in the target. This aspect becomes worse in larger tumors for which inferior clinical outcomes and corresponding lower LETd was reported. Purpose: The vicinity to critical organs in general and the inferior overall survival reported for larger sacral chordomas treated with carbon ion radiotherapy (CIRT), makes the treatment of such tumors challenging. In this work it was aimed to increase the LETd in large volume tumors while maintaining the relative biological effectiveness (RBE)‐weighted dose, utilizing the LETd optimization functions of a commercial treatment planning system (TPS). Methods: Ten reference sequential boost carbon ion treatment plans, designed to mimic clinical plans for large sacral chordoma tumors, were generated. High dose clinical target volumes (CTV‐HD) larger than 250cm3$250 \,{\rm cm}^{3}$ were considered as large targets. The total RBE‐weighted median dose prescription with the local effect model (LEM) was DRBE,50%=73.6Gy$\textrm {D}_{\rm RBE, 50\%}=73.6 \,{\rm Gy}$ in 16 fractions (nine to low dose and seven to high dose planning target volume). No LETd optimization was performed in the reference plans, while LETd optimized plans used the minimum LETd (Lmin) optimization function in RayStation 2023B. Three different Lmin values were investigated and specified for the seven boost fractions: Lmin=60keV/μm$\textrm {L}_{\rm min}=60 \,{\rm keV}/{\umu }{\rm m}$, Lmin=80keV/μm$\textrm {L}_{\rm min}=80 \,{\rm keV}/{\umu }{\rm m}$ and Lmin=100keV/μm$\textrm {L}_{\rm min}=100 \,{\rm keV}/{\umu }{\rm m}$. To compare the LETd optimized against reference plans, LETd and RBE‐weighted dose based goals similar to and less strict than clinical ones were specified for the target. The goals for the organs at risk (OAR) remained unchanged. Robustness evaluation was studied for eight scenarios (±3.5%$\pm 3.5\%$ range uncertainty and ±3mm$\pm 3 \,{\rm mm}$ setup uncertainty along the main three axes). Results: The optimization method with Lmin=60keV/μm$\textrm {L}_{\rm min}=60 \,{\rm keV}/{\umu }{\rm m}$ resulted in an optimal LETd distribution with an average increase of LETd,98%${\rm {LET}}_{{\rm {d,}}98\%}$ (and LETd,50%${\rm {LET}}_{{\rm {d,}}50\%}$) in the CTV‐HD by 8.9±1.5keV/μm$8.9\pm 1.5 \,{\rm keV}/{\umu }{\rm m}$ (27%$27\%$) (and 6.9±1.3keV/μm$6.9\pm 1.3 \,{\rm keV}/{\umu }{\rm m}$ (17%$17\%$)), without significant difference in the RBE‐weighted dose. By allowing ±5%$\pm 5\%$ over‐ and under‐dosage in the target, the LETd,98%${\rm {LET}}_{{\rm {d,}}98\%}$ (and LETd,50%${\rm {LET}}_{{\rm {d,}}50\%}$) can be increased by 11.3±1.2keV/μm$11.3\pm 1.2 \,{\rm keV}/{\umu }{\rm m}$ (34%$34\%$) (and 11.7±3.4keV/μm$11.7\pm 3.4 \,{\rm keV}/{\umu }{\rm m}$ (29%$29\%$)), using the optimization parameters Lmin=80keV/μm$\textrm {L}_{\rm min}=80 \,{\rm keV}/{\umu }{\rm m}$. The pass rate for the OAR goals in the LETd optimized plans was in the same level as the reference plans. LETd optimization lead to less robust plans compared to reference plans. Conclusions: Compared to conventionally optimized treatment plans, the LETd in the target was increased while maintaining the RBE‐weighted dose using TPS LETd optimization functionalities. Regularly assessing RBE‐weighted dose robustness and acquiring more in‐room images remain crucial and inevitable aspects during treatment. [ABSTRACT FROM AUTHOR]

Abstract Background Existing pencil beam analytical (PBA) algorithms for proton therapy treatment planning are not ideal for sites with heterogeneous tissue density and do not account for the spatial variations in proton relative biological effectiveness (vRBE). Using a commercially available Monte Carlo (MC) treatment planning system, we compared various dosimetric endpoints between proton PBA, proton MC, and photon treatment plans among patients with mediastinal lymphoma. Methods Eight mediastinal lymphoma patients with both free breathing (FB) and deep inspiration breath hold (DIBH) CT simulation scans were analyzed. The original PBA plans were re-calculated with MC. New proton plans that used MC for both optimization and dose calculation with equivalent CTV/ITV coverage were also created. A vRBE model, which uses a published model for DNA double strand break (DSB) induction, was applied on MC plans to study the potential impact of vRBE on cardiac doses. Comparative photon plans were generated on the DIBH scan. Results Re-calculation of FB PBA plans with MC demonstrated significant under coverage of the ITV V99 and V95. Target coverage was recovered by re-optimizing the PT plan with MC with minimal change to OAR doses. Compared to photons with DIBH, MC-optimized FB and DIBH proton plans had significantly lower dose to the mean lung, lung V5, breast tissue, and spinal cord for similar target coverage. Even with application of vRBE in the proton plans, the putative increase in RBE at the end of range did not decrease the dosimetric advantages of proton therapy in cardiac substructures. Conclusions MC should be used for PT treatment planning of mediastinal lymphoma to ensure adequate coverage of target volumes. Our preliminary data suggests that MC-optimized PT plans have better sparing of the lung and breast tissue compared to photons. Also, the potential for end of range RBE effects are unlikely to be large enough to offset the dosimetric advantages of proton therapy in cardiac substructures for mediastinal targets, although these dosimetric findings require validation with late toxicity data.

Background: Applying tolerance doses for organs at risk (OAR) from photon therapy introduces uncertainties in proton therapy when assuming a constant relative biological effectiveness (RBE) of 1.1. Purpose: This work introduces the novel dirty and clean dose concept, which allows for creating treatment plans with a more photon‐like dose response for OAR and, thus, less uncertainties when applying photon‐based tolerance doses. Methods: The concept divides the 1.1‐weighted dose distribution into two parts: the clean and the dirty dose. The clean and dirty dose are deposited by protons with a linear energy transfer (LET) below and above a set LET threshold, respectively. For the former, a photon‐like dose response is assumed, while for the latter, the RBE might exceed 1.1. To reduce the dirty dose in OAR, a MaxDirtyDose objective was added in treatment plan optimization. It requires setting two parameters: LET threshold and max dirty dose level. A simple geometry consisting of one target volume and one OAR in water was used to study the reduction in dirty dose in the OAR depending on the choice of the two MaxDirtyDose objective parameters during plan optimization. The best performing parameter combinations were used to create multiple dirty dose optimized (DDopt) treatment plans for two cranial patient cases. For each DDopt plan, 1.1‐weighted dose, variable RBE‐weighted dose using the Wedenberg RBE model and dose‐average LETd distributions as well as resulting normal tissue complication probability (NTCP) values were calculated and compared to the reference plan (RefPlan) without MaxDirtyDose objectives. Results: In the water phantom studies, LET thresholds between 1.5 and 2.5 keV/µm yielded the best plans and were subsequently used. For the patient cases, nearly all DDopt plans led to a reduced Wedenberg dose in critical OAR. This reduction resulted from an LET reduction and translated into an NTCP reduction of up to 19 percentage points compared to the RefPlan. The 1.1‐weighted dose in the OARs was slightly increased (patient 1: 0.45 Gy(RBE), patient 2: 0.08 Gy(RBE)), but never exceeded clinical tolerance doses. Additionally, slightly increased 1.1‐weighted dose in healthy brain tissue was observed (patient 1: 0.81 Gy(RBE), patient 2: 0.53 Gy(RBE)). The variation of NTCP values due to variation of α/β from 2 to 3 Gy was much smaller for DDopt (2 percentage points (pp)) than for RefPlans (5 pp). Conclusions: The novel dirty and clean dose concept allows for creating biologically more robust proton treatment plans with a more photon‐like dose response. The reduced uncertainties in RBE can, therefore, mitigate uncertainties introduced by using photon‐based tolerance doses for OAR. [ABSTRACT FROM AUTHOR]

Background: Large tumor size has been reported as a predicting factor for inferior clinical outcome in carbon ion radiotherapy (CIRT). Besides the clinical factors accompanied with such tumors, larger tumors receive typically more low linear energy transfer (LET) contributions than small ones which may be the underlying physical cause. Although dose averaged LET is often used as a single parameter descriptor to quantify the beam quality, there is no evidence that this parameter is the optimal clinical predictor for the complex mixed radiation fields in CIRT. Purpose: Purpose of this study was to investigate on a novel dosimetric quantity, namely high‐LET‐dose (D>Lthr$\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$, the physical dose filtered based on an LET threshold) as a single parameter estimator to differentiate between carbon ion treatment plans (cTP) with a small and large tumor volume. Methods: Ten cTPs with a planning target volume, PTV≥500cm3$\mathrm{PTV}\ge {500}\,{{\rm cm}^{3}}$ (large) and nine with a PTV<500cm3$\mathrm{PTV}<{500}\,{{\rm cm}^{3}}$ (small) were selected for this study. To find a reasonable LET threshold (Lthr$\textrm {L}_{\textrm {thr}}$) that results in a significant difference in terms of D>Lthr$\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$, the voxel based normalized high‐LET‐dose (D̂>Lthr$\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$) distribution in the clinical target volume (CTV) was studied on a subset (12 out of 19 cTPs) for 18 LET thresholds, using standard distribution descriptors (mean, variance and skewness). The classical dose volume histogram concept was used to evaluate the D>Lthr$\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D̂>Lthr$\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ distributions within the target of all 19 cTPs at the before determined Lthr$\textrm {L}_{\textrm {thr}}$. Statistical significance of the difference between the two groups in terms of mean D>Lthr$\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D̂>Lthr$\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ volume histogram parameters was evaluated by means of (two‐sided) t‐test or Mann‐Whitney‐U‐test. In addition, the minimum target coverage at the above determined Lthr$\textrm {L}_{\textrm {thr}}$ was compared and validated against three other thresholds to verify its potential in differentiation between small and large volume tumors. Results: An Lthr$\textrm {L}_{\textrm {thr}}$ of approximately 30keV/μm${30}\,{\rm keV/}\umu {\rm m}$ was found to be a reasonable threshold to classify the two groups. At this threshold, the D>Lthr$\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D̂>Lthr$\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ were significantly larger (p<0.05$p<0.05$) in small CTVs. For the small tumor group, the near‐minimum and median D>Lthr$\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ (and D̂>Lthr$\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$) in the CTV were in average 9.3±1.5Gy$9.3\pm {1.5}\,{\rm Gy}$ (0.31 ± 0.08) and 13.6±1.6Gy$13.6\pm {1.6}\,{\rm Gy}$ (0.46 ± 0.06), respectively. For the large tumors, these parameters were 6.6±0.2Gy$6.6\pm {0.2}\,{\rm Gy}$ (0.20 ± 0.01) and 8.6±0.4Gy$8.6\pm {0.4}\,{\rm Gy}$ (0.28 ± 0.02). The difference between the two groups in terms of mean near‐minimum and median D>Lthr$\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ (D̂>Lthr$\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$) was 2.7 Gy (11%) and 5.0 Gy (18%), respectively. Conclusions: The feasibility of high‐LET‐dose based evaluation was shown in this study where a lower D>Lthr$\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ was found in cTPs with a large tumor size. Further investigation is needed to draw clinical conclusions. The proposed methodology in this work can be utilized for future high‐LET‐dose based studies. [ABSTRACT FROM AUTHOR]