Radiation therapy with phenotypic medicine: towards N-of-1 personalization.

In current clinical practice, radiotherapy (RT) is prescribed as a pre-determined total dose divided over daily doses (fractions) given over several weeks. The treatment response is typically assessed months after the end of RT. However, the conventional one-dose-fits-all strategy may not achieve the desired outcome, owing to patient and tumor heterogeneity. Therefore, a treatment strategy that allows for RT dose personalization based on each individual response is preferred. Multiple strategies have been adopted to address this challenge. As an alternative to current known strategies, artificial intelligence (AI)-derived mechanism-independent small data phenotypic medicine (PM) platforms may be utilized for N-of-1 RT personalization. Unlike existing big data approaches, PM does not engage in model refining, training, and validation, and guides treatment by utilizing prospectively collected patient's own small datasets. With PM, clinicians may guide patients' RT dose recommendations using their responses in real-time and potentially avoid over-treatment in good responders and under-treatment in poor responders. In this paper, we discuss the potential of engaging PM to guide clinicians on upfront dose selections and ongoing adaptations during RT, as well as considerations and limitations for implementation. For practicing oncologists, clinical trialists, and researchers, PM can either be implemented as a standalone strategy or in complement with other existing RT personalizations. In addition, PM can either be used for monotherapeutic RT personalization, or in combination with other therapeutics (e.g. chemotherapy, targeted therapy). The potential of N-of-1 RT personalization with drugs will also be presented.

Detecting outliers beyond tolerance limits derived from statistical process control in patient-specific quality assurance.

BACKGROUND: Tolerance limit is defined on pre-treatment patient specific quality assurance results to identify "out of the norm" dose discrepancy in plan. An out-of-tolerance plan during measurement can often cause treatment delays especially if replanning is required. In this study, we aim to develop an outlier detection model to identify out-of-tolerance plan early during treatment planning phase to mitigate the above-mentioned risks. METHODS: Patient-specific quality assurance results with portal dosimetry for stereotactic body radiotherapy measured between January 2020 and December 2021 were used in this study. Data were divided into thorax and pelvis sites and gamma passing rates were recorded using 2%/2 mm, 2%/1 mm, and 1%/1 mm gamma criteria. Statistical process control method was used to determine six different site and criterion-specific tolerance and action limits. Using only the inliers identified with our determined tolerance limits, we trained three different outlier detection models using the plan complexity metrics extracted from each treatment field-robust covariance, isolation forest, and one class support vector machine. The hyperparameters were optimized using the F1-score calculated from both the inliers and validation outliers' data. RESULTS: 308 pelvis and 200 thorax fields were used in this study. The tolerance (action) limits for 2%/2 mm, 2%/1 mm, and 1%/1 mm gamma criteria in the pelvis site are 99.1% (98.1%), 95.8% (91.1%), and 91.7% (86.1%), respectively. The tolerance (action) limits in the thorax site are 99.0% (98.7%), 97.0% (96.2%), and 91.5% (87.2%). One class support vector machine performs the best among all the algorithms. The best performing model in the thorax (pelvis) site achieves a precision of 0.56 (0.54), recall of 1.0 (1.0), and F1-score of 0.72 (0.70) when using the 2%/2 mm (2%/1 mm) criterion. CONCLUSION: The model will help the planner to identify an out-of-tolerance plan early so that they can refine the plan further during the planning stage without risking late discovery during measurement.

Repurposing DailyQA3 for an efficient and spot position sensitive daily quality assurance tool for proton therapy.

INTRODUCTION: Daily quality assurance is an integral part of a radiotherapy workflow to ensure the dose is delivered safely and accurately to the patient. It is performed before the first treatment of the day and needs to be time and cost efficient for a multiple gantries proton center. In this study, we introduced an efficient method to perform QA for output constancy, range verification, spot positioning accuracy and imaging and proton beam isocenter coincidence with DailyQA3. METHODS: A stepped acrylic block of specific dimensions is fabricated and placed on top of the DailyQA3 device. Treatment plans comprising of two different spread-out Bragg peaks and five individual spots of 1.0 MU each are designed to be delivered to the device. A mathematical framework to measure the 2D distance between the detectors and individual spot is introduced and play an important role in realizing the spot positioning and centering QA. Lastly, a 5 months trends of the QA for two gantries are presented. RESULTS: The outputs are monitored by two ion chambers in the DailyQA3 and a tolerance of ± 3 % $ \pm 3\% $ are used. The range of the SOBPs are monitored by the ratio of ion chamber signals and a tolerance of ± 1 mm $ \pm 1\ {\mathrm{mm}}$ is used. Four diodes at ± 10 cm $ \pm 10\ {\mathrm{cm}}$ from the central ion chambers are used for spot positioning QA, while the central ion chamber is used for imaging and proton beam isocenter coincidence QA. Using the framework, we determined the absolute signal threshold corresponding to the offset tolerance between the individual proton spot and the detector. A 1.5 mm $1.5\ {\mathrm{mm}}$ tolerances are used for both the positioning and centering QA. No violation of the tolerances is observed in the 5 months trends for both gantries. CONCLUSION: With the proposed approach, we can perform four QA items in the TG224 within 10 min.

A transit portal dosimetry method for respiratory gating quality assurance with a dynamic 3D printed tumor phantom.

BACKGROUNDS: Respiratory gating is one of the motion management techniques that is used to deliver radiation dose to a tumor at a specific position under free breathing. However, due to the dynamic feedback process of this approach, regular equipment quality assurance (QA) and patient-specific QA checks need to be performed. This work proposes a new QA methodology using electronic portal imaging detector (EPID) to determine the target localization accuracy of phase gating. METHODS: QA tools comprising 3D printed spherical tumor phantoms, programmable stages, and an EPID detector are characterized and assembled. Algorithms for predicting portal dose (PD) through moving phantoms are developed and verified using gamma analysis for two spherical tumor phantoms (2 cm and 4 cm), two different 6 MV volumetric modulated arc therapy plans, and two different gating windows (30%-70% and 40%-60%). Comparison between the two gating windows is then performed using the Wilcoxon signed-rank test. An optimizer routine, which is used to determine the optimal window, based on maximal gamma passing rate (GPR), was applied to an actual breathing curve and breathing plan. This was done to ascertain if our method yielded a similar result with the actual gating window. RESULTS: High GPRs of more than 97% and 91% were observed when comparing the predicted PD with the measured PD in moving phantom at 2 mm/2% and 1 mm/1% levels, respectively. Analysis of gamma heatmaps shows an excellent agreement with the tumor phantom. The GPR of 40%-60% PD was significantly lower than that of the 30%-70% PD at the 1 mm/1% level (p = 0.0064). At the 2 mm/2% level, no significant differences were observed. The optimizer routine could accurately predict the center of the gating window to within a 10% range. CONCLUSION: We have successfully performed and verified a new method for QA with the use of a moving phantom with EPID for phase gating with real-time position management.

Evaluation of inter- and intra-observer variations in prostate gland delineation using CT-alone versus CT/TPUS.

Background: This study aims to explore the role of four-dimensional (4D) transperineal ultrasound (TPUS) in the contouring of prostate gland with planning computed tomography (CT) images, in the absence of magnetic resonance imaging (MRI). Materials and methods: Five radiation oncologists (ROs) performed two rounds of prostate gland contouring (single-blinded) on CT-alone and CT/TPUS datasets obtained from 10 patients who underwent TPUS-guided external beam radiotherapy. Parameters include prostate volume, DICE similarity coefficient (DSC) and centroid position. Wilcoxon signed-rank test assessed the significance of inter-modality differences, and the intraclass correlation coefficient (ICC ) reflected inter- and intra-observer reliability of parameters. Results: Inter-modality analysis revealed high agreement (based on DSC and centroid position) of prostate gland contours between CT-alone and CT/TPUS. Statistical significant difference was observed in the superior-inferior direction of the prostate centroid position (p = 0.011). All modalities yielded excellent inter-observer reliability of delineated prostate volume with ICC > 0.9, mean DSC > 0.8 and centroid position: CT-alone (ICC = 1.000) and CT/TPUS (ICC = 0.999) left-right (L/R); CT-alone (ICC = 0.999) and CT/TPUS (ICC = 0.998) anterior-posterior (A/P); CT-alone (ICC = 0.999) and CT/TPUS (ICC = 1.000) superior-inferior (S/I). Similarly, all modalities yielded excellent intra-observer reliability of delineated prostate volume, ICC > 0.9 and mean DSC > 0.8. Lastly, intra-observer reliability was excellent on both imaging modalities for the prostate centroid position, ICC > 0.9. Conclusion: TPUS does not add significantly to the amount of anatomical information provided by CT images. However, TPUS can supplement planning CT to achieve a higher positional accuracy in the S/I direction if access to CT/MRI fusion is limited.

Cluster-based radiomics reveal spatial heterogeneity of bevacizumab response for treatment of radiotherapy-induced cerebral necrosis.

Background: Bevacizumab is used in the treatment of radiation necrosis (RN), which is a debilitating toxicity following head and neck radiotherapy. However, there is no biomarker to predict if a patient would respond to bevacizumab. Purpose: We aimed to develop a cluster-based radiomics approach to characterize the spatial heterogeneity of RN and map their responses to bevacizumab. Methods: 118 consecutive nasopharyngeal carcinoma patients diagnosed with RN were enrolled. We divided 152 lesions from the patients into 101 for training, and 51 for validation. We extracted voxel-level radiomics features from each lesion segmented on T1-weighted+contrast and T2 FLAIR sequences of pre- and post-bevacizumab magnetic resonance images, followed by a three-step analysis involving individual- and population-level clustering, before delta-radiomics to derive five radiomics clusters within the lesions. We tested the association of each cluster with response to bevacizumab and developed a clinico-radiomics model using clinical predictors and cluster-specific features. Results: 71 (70.3%) and 34 (66.7%) lesions had responded to bevacizumab in the training and validation datasets, respectively. Two radiomics clusters were spatially mapped to the edema region, and the volume changes were significantly associated with bevacizumab response (OR:11.12 [95% CI: 2.54-73.47], P = 0.004; and 1.63[1.07-2.78], P = 0.042). The combined clinico-radiomics model based on textural features extracted from the most significant cluster improved the prediction of bevacizumab response, compared with a clinical-only model (AUC:0.755 [0.645-0.865] to 0.852 [0.764-0.940], training; 0.708 [0.554-0.861] to 0.816 [0.699-0.933], validation). Conclusion: Our radiomics approach yielded intralesional resolution, enabling a more refined feature selection for predicting bevacizumab efficacy in the treatment of RN.

Investigation of dosimetric effect of beam current fluctuations in synchrotron-based proton PBS continuous scanning.

Objective.In proton pencil beam scanning (PBS) continuous delivery, the beam is continuously delivered without interruptions between spots. For synchrotron-based systems, the extracted beam current exhibits a spill structure, and recent publications on beam current measurements have demonstrated significant fluctuations around the nominal values. These fluctuations potentially lead to dose deviations from those calculated assuming a stable beam current. This study investigated the dosimetric implications of such beam current fluctuations during proton PBS continuous scanning.Approach.Using representative clinical proton PBS plans, we performed simulations to mimic a worst-case clinical delivery environment with beam current varies from 50% to 250% of the nominal values. The simulations used the beam delivery parameters optimized for the best beam delivery efficiency of the upcoming particle therapy system at Mayo Clinic Florida. We reconstructed the simulated delivered dose distributions and evaluated the dosimetric impact of beam current fluctuations.Main results.Despite significant beam current fluctuations resulting in deviations at each spot level, the overall dose distributions were nearly identical to those assuming a stable beam current. The 1 mm/1% Gamma passing rate was 100% for all plans. Less than 0.2% root mean square error was observed in the planning target volume dose-volume histogram. Minimal differences were observed in all dosimetric evaluation metrics.Significance.Our findings demonstrate that with our beam delivery system and clinical planning practice, while significant beam current fluctuations may result in large local move monitor unit deviations at each spot level, the overall impact on the dose distribution is minimal.

Effects of modern aesthetic dental fillings on proton therapy.

Background and purpose: High-density dental fillings pose a non-negligible impact on head and neck cancer treatment. For proton therapy, stopping power ratio (SPR) prediction will be significantly impaired by the associated image artifacts. Dose perturbation is also inevitable, compromising the treatment plan quality. While plenty of work has been done on metal or amalgam fillings, none has touched on composite resin (CR) and glass ionomer cement (GIC) which have seen an increasing usage. Hence, this work aims to provide a detailed characterisation of SPR and dose perturbation in proton therapy caused by CR and GIC. Materials and methods: Four types of fillings were used: CR, Fuji Bulk (FB), Fuji II (FII) and Fuji IX (FIX). The latter three belong to GIC category. Measured SPR were compared with SPR predicted using single-energy computed tomography (SECT) and dual-energy computed tomography (DECT). Dose perturbation of proton beams with lower- and higher-energy levels was also quantified using Gafchromic films. Results: The measured SPR for CR, FB, FII and FIX were 1.68, 1.77, 1.77 and 1.76, respectively. Overall, DECT could predict SPR better than SECT. The lowest percentage error achieved by DECT was 19.7 %, demonstrating the challenge in estimating SPR, even for fillings with relatively lower densities. For both proton beam energies and all four fillings of about 4.5 mm thickness, the maximum dose perturbation was 3 %. Conclusion: This study showed that dose perturbation by CR and GIC was comparatively small. We have measured and recommended the SPR values for overriding the fillings in TPS.

Real-time gated proton therapy with a reduced source to imager distance: Commissioning and quality assurance.

INTRODUCTION: Real-time gated proton therapy (RGPT) is a motion management technique unique to the Hitachi particle therapy system. It uses pulsed fluoroscopy to track an implanted fiducial marker. There are currently no published guidelines on how to conduct the commissioning and quality assurance. In this work we reported on our centre's commissioning workflow and our daily and monthly QA procedures. METHODS: Six commissioning measurements were designed for RGPT. The measurements include imaging qualities, fluoroscopic exposures, RGPT marker tracking accuracy, temporal gating latency, fiducial marker tracking fidelity and an end-to-end proton dosimetry measurement. Daily QA consists of one measurement on marker localization accuracy. Four months daily QA trends are presented. Monthly QA consists of three measurementson the gating latency, fluoroscopy imaging quality and dosimetry verification of gating operation with RGPT. RESULTS: The RGPT was successfully commissioned in our centre. The air kerma rates were within 15 % from specifications and the marker tracking accuracies were within 0.245 mm. The gating latencies for turning the proton beam on and off were 119.5 and 50.0 ms respectively. The 0.4x10.0 mm2 Gold AnchorTM gave the best tracking results with visibility up to 30 g/cm2. Gamma analysis showed that dose distribution of a moving and static detectors had a passing rate of more than 95 % at 3 %/3mm. The daily marker localization QA results were all less than 0.2 mm. CONCLUSION: This work could serve as a good reference for other upcoming Hitachi particle therapy centres who are interested to use RGPT as their motion management solution.

First clinical experience following the consensus guide for calibrating a proton stopping power ratio curve in a new proton centre.

BACKGROUND AND PURPOSE: This work introduces the first assessment of CT calibration following the ESTRO's consensus guidelines and validating the HLUT through the irradiation of biological material. METHODS: Two electron density phantoms were scanned with two CT scanners using two CT scan energies. The stopping power ratio (SPR) and mass density (MD) HLUTs for different CT scan energies were derived using Schneider's and ESTRO's methods. The comparison metric in this work is based on the Water-Equivalent Thickness (WET) difference between the treatment planning system and biological irradiation measurement. The SPR HLUTs were compared between the two calibration methods. To assess the accuracy of using MD HLUT for dose calculation in the treatment planning system, MD vs SPR HLUT was compared. Lastly, the feasibility of using a single SPR HLUT to replace two different energy CT scans was explored. RESULTS: The results show a WET difference of less than 3.5% except for the result in the Bone region between Schneider's and ESTRO's methods. Comparing MD and SPR HLUT, the results from MD HLUT show less than a 3.5% difference except for the Bone region. However, the SPR HLUT shows a lower mean absolute percentage difference as compared to MD HLUT between the measured and calculated WET difference. Lastly, it is possible to use a single SPR HLUT for two different CT scan energies since both WET differences are within 3.5%. CONCLUSION: This is the first report on calibrating an HLUT following the ESTRO's guidelines. While our result shows incremental improvement in range uncertainty using the ESTRO's guideline, the prescriptional approach of the guideline does promote harmonization of CT calibration protocols between different centres.

Deformable anthropomorphic pelvis phantom for dose accumulation verification.

Objective.The validation of deformable image registration (DIR) for contour propagation is often done using contour-based metrics. Meanwhile, dose accumulation requires evaluation of voxel mapping accuracy, which might not be accurately represented by contour-based metrics. By fabricating a deformable anthropomorphic pelvis phantom, we aim to (1) quantify the voxel mapping accuracy for various deformation scenarios, in high- and low-contrast regions, and (2) identify any correlation between dice similarity coefficient (DSC), a commonly used contour-based metric, and the voxel mapping accuracy for each organ.Approach. Four organs, i.e. pelvic bone, prostate, bladder and rectum (PBR), were 3D printed using PLA and a Polyjet digital material, and assembled. The latter three were implanted with glass bead and CT markers within or on their surfaces. Four deformation scenarios were simulated by varying the bladder and rectum volumes. For each scenario, nine DIRs with different parameters were performed on RayStation v10B. The voxel mapping accuracy was quantified by finding the discrepancy between true and mapped marker positions, termed the target registration error (TRE). Pearson correlation test was done between the DSC and mean TRE for each organ.Main results. For the first time, we fabricated a deformable phantom purely from 3D printing, which successfully reproduced realistic anatomical deformations. Overall, the voxel mapping accuracy dropped with increasing deformation magnitude, but improved when more organs were used to guide the DIR or limit the registration region. DSC was found to be a good indicator of voxel mapping accuracy for prostate and rectum, but a comparatively poorer one for bladder. DSC > 0.85/0.90 was established as the threshold of mean TRE ⩽ 0.3 cm for rectum/prostate. For bladder, extra metrics in addition to DSC should be considered.Significance. This work presented a 3D printed phantom, which enabled quantification of voxel mapping accuracy and evaluation of correlation between DSC and voxel mapping accuracy.

A measurement validation of improved plan deliverability with monitor unit objective tool for spine stereotactic ablative radiotherapy.

Spine stereotactic body radiation therapy (SBRT) uses high dose per fraction for palliative pain control. The treatment plans are often heavily modulated due to close proximity to spinal cord and this can lead to poor plan quality which are susceptible to dose delivery discrepancy. Therefore, we aim to assess the effectiveness of the monitor unit (MU) objective tool in Eclipse treatment planning systems in modulating the plan complexity to improve the plan quality in spine SBRT. Seven retrospective spine SBRT plans are re-optimized using the MU objective tool in Eclipse TPS v13.6 and were compared with the original plans. The dose metrics of the tumor PTV were compared using D1cc. D99%, D95%, D0.03cc, D0.1cc, D0.35cc and D1cc, and that of cord PRV were compared using D0.03cc, D0.1cc, D0.35cc. Four different plan complexities were also calculated for the original and re-optimized plans to quantify the impact of the tool on the modulation. Patient specific quality assurance measurements were performed with Stereophan and SRS MapCheck, and analyzed using the 1%/1-mm and 2%/2-mm criteria with gamma analysis. The dose metrics of the PTV and cord PRV of the re-optimized and original plans are similar and still meet the planning dose constraints. In particular, the PTV dose coverage has a small percentage difference of (0.15 ± 1.33)% and (0.01 ± 1.04)% for D99% and D95%, respectively. The 4 calculated plan complexity metrics consistently show that the re-optimized plans are quantitatively less complex than the original plan. The gamma passing rate of the re-optimized plans improved from (92.2 ± 2.0)% to (94.2 ± 1.6)% with the 1%/1-mm criterion, and (98.7 ± 1.0)% to (99.5 ± 0.3)% with the 2%/2-mm criterion. Overall, the re-optimized plans achieve at least a 10% MU reduction (11.7% to 24.6%). Our study shows that optimization with the MU objective tool can reduce plan complexity and improves dose delivery accuracy, while not compromising the dose distribution.

The effect of spill change on reliable absolute dosimetry in a synchrotron proton spot scanning system.

BACKGROUND: Absolute dosimetry measurement is an integral part of Treatment Planning System (TPS) commissioning and it involves measuring the integrated absorbed dose to water for all energies in a pencil beam scanning delivery system. During the commissioning of Singapore's first proton therapy center, a uniform scanned field with an Advanced Markus chamber method was employed for this measurement, and a large dose fluctuation of at least 5% was observed for 10% of the energy layers during repeated measurements. PURPOSE: This study aims to understand the root cause of this fluctuation by relating the actual delivered spot information in the log file with the charge measurement by the ion chambers. METHODS: A dedicated pencil beam dose algorithm was developed, taking into account the log file parameters, to calculate the dose for a single energy layer in a homogeneous water phantom. Three energies, 70.2, 182.7, and 228.7 MeV were used in this study, with the 182.7 MeV energy exhibiting large dose fluctuation. The dose fluctuation was investigated as a function of detector's sizes (pinpoint 3D, Advanced Markus, PTW 34070, and PTW 34089) and water depth (2 , 6, and 20 cm). Twelve ion chambers measurements were performed for each chamber and depth. The comparison of the theoretically predicted integrated dose and the charge measurement served as a validation of the algorithm. RESULTS: About 5.9% and 9.6% dose fluctuation were observed in Advanced Markus and pinpoint 3D measurements at 2 cm depth for 182.7 MeV, while fluctuation of 1.6% and 1.1% were observed in Advanced Markus with 228.7 and 70.2 MeV at similar depth. Fluctuation of less than 0.1% was observed for PTW34070 and PTW 34089 for all energies. The fluctuation was found to diminish with larger spot size at 20 cm depth to 1.3% for 182.7 MeV. The theoretical and measured charge comparison showed a high linear correlation of R 2 > 0.80 ${R^2} > 0.80$ for all datasets, indicating the fluctuation originated from the delivered spot characteristics. The cause of fluctuation was identified to be due to the spill change occurring close to the detector, and since the spot positional deviation profiles were different between two spills, this resulted in local hot spots between columns of spots. The actual position of spill change varies randomly during measurement, which led to a random occurrence of hot spot within the detector's sensitive volume and a fluctuating dose measurement. CONCLUSION: This is the first report of a dose fluctuation greater than 5% in absolute dosimetry measurement with a uniform scanned field and the cause of the fluctuation has been conclusively determined. It is important to choose the MU and scanning pattern carefully to avoid spill change happening when the spot delivery is near the detector.

A Review of the Current Clinical Evidence for Loco-Regional Moderate Hyperthermia in the Adjunct Management of Cancers.

Regional hyperthermia therapy (RHT) is a treatment that applies moderate heat to tumours in an attempt to potentiate the effects of oncological treatments and improve responses. Although it has been used for many years, the mechanisms of action are not fully understood. Heterogenous practices, poor quality assurance, conflicting clinical evidence and lack of familiarity have hindered its use. Despite this, several centres recognise its potential and have adopted it in their standard treatment protocols. In recent times, significant technical improvements have been made and there is an increasing pool of evidence that could revolutionise its use. Our narrative review aims to summarise the recently published prospective trial evidence and present the clinical effects of RHT when added to standard cancer treatments. In total, 31 studies with higher-quality evidence across various subsites are discussed herein. Although not all of these studies are level 1 evidence, benefits of moderate RHT in improving local tumour control, survival outcomes and quality of life scores were observed across the different cancer subsites with minimal increase in toxicities. This paper may serve as a reference when considering this technique for specific indications.

Proton versus photon therapy for high-risk prostate cancer with dose escalation of dominant intraprostatic lesions: a preliminary planning study.

Background and purpose: This study aimed to investigate the feasibility of safe-dose escalation to dominant intraprostatic lesions (DILs) and assess the clinical impact using dose-volume (DV) and biological metrics in photon and proton therapy. Biological parameters defined as late grade ≥ 2 gastrointestinal (GI) and genitourinary (GU) derived from planned (D P) and accumulated dose (D A) were utilized. Materials and methods: In total, 10 patients with high-risk prostate cancer with multiparametric MRI-defined DILs were investigated. Each patient had two plans with a focal boost to the DILs using intensity-modulated proton therapy (IMPT) and volumetric-modulated arc therapy (VMAT). Plans were optimized to obtain DIL coverage while respecting the mandatory organ-at-risk constraints. For the planning evaluation, DV metrics, tumor control probability (TCP) for the DILs and whole prostate excluding the DILs (prostate-DILs), and normal tissue complication probability (NTCP) for the rectum and bladder were calculated. Wilcoxon signed-rank test was used for analyzing TCP and NTCP data. Results: IMPT achieved a higher Dmean for the DILs compared to VMAT (IMPT: 68.1 GyRBE vs. VMAT: 66.6 Gy, p < 0.05). Intermediate-high rectal and bladder doses were lower for IMPT (p < 0.05), while the high-dose region (V60 Gy) remained comparable. IMPT-TCP for prostate-DIL were higher compared to VMAT (IMPT: 86%; α/ß = 3, 94.3%; α/ß = 1.5 vs. VMAT: 84.7%; α/ß = 3, 93.9%; α/ß = 1.5, p < 0.05). Likewise, IMPT obtained a moderately higher DIL TCP (IMPT: 97%; α/ß = 3, 99.3%; α/ß = 1.5 vs. VMAT: 95.9%; α/ß = 3, 98.9%; α/ß = 1.5, p < 0.05). Rectal D A-NTCP displayed the highest GI toxicity risk at 5.6%, and IMPT has a lower GI toxicity risk compared to VMAT-predicted Quantec-NTCP (p < 0.05). Bladder D P-NTCP projected a higher GU toxicity than D A-NTCP, with VMAT having the highest risk (p < 0.05). Conclusion: Dose escalation using IMPT is able to achieve a high TCP for the DILs, with the lowest rectal and bladder DV doses at the intermediate-high-dose range. The reduction in physical dose was translated into a lower NTCP (p < 0.05) for the bladder, although rectal toxicity remained equivalent.

Predicting dice similarity coefficient of deformably registered contours using Siamese neural network.

Objective. Automatic deformable image registration (DIR) is a critical step in adaptive radiotherapy. Manually delineated organs-at-risk (OARs) contours on planning CT (pCT) scans are deformably registered onto daily cone-beam CT (CBCT) scans for delivered dose accumulation. However, evaluation of registered contours requires human assessment, which is time-consuming and subjects to high inter-observer variability. This work proposes a deep learning model that allows accurate prediction of Dice similarity coefficients (DSC) of registered contours in prostate radiotherapy.Approach. Our dataset comprises 20 prostate cancer patients with 37-39 daily CBCT scans each. The pCT scans and planning contours were deformably registered to each corresponding CBCT scan to generate virtual CT (vCT) scans and registered contours. The DSC score, which is a common contour-based validation metric for registration quality, between the registered and manual contours were computed. A Siamese neural network was trained on the vCT-CBCT image pairs to predict DSC. To assess the performance of the model, the root mean squared error (RMSE) between the actual and predicted DSC were computed.Main results. The model showed promising results for predicting DSC, giving RMSE of 0.070, 0.079 and 0.118 for rectum, prostate, and bladder respectively on the holdout test set. Clinically, a low RMSE implies that the predicted DSC can be reliably used to determine if further DIR assessment from physicians is required. Considering the event where a registered contour is classified as poor if its DSC is below 0.6 and good otherwise, the model achieves an accuracy of 92% for the rectum. A sensitivity of 0.97 suggests that the model can correctly identify 97% of poorly registered contours, allowing manual assessment of DIR to be triggered.Significance. We propose a neural network capable of accurately predicting DSC of deformably registered OAR contours, which can be used to evaluate eligibility for plan adaptation.

A review on fetal dose in Radiotherapy: A historical to contemporary perspective.

This paper aims to review on fetal dose in radiotherapy and extends and updates on a previous work1 to include proton therapy. Out-of-field doses, which are the doses received by regions outside of the treatment field, are unavoidable regardless of the treatment modalities used during radiotherapy. In the case of pregnant patients, fetal dose is a major concern as it has long been recognized that fetuses exposed to radiation have a higher probability of suffering from adverse effects such as anatomical malformations and even fetal death, especially when the 0.1Gy threshold is exceeded. In spite of the low occurrence of cancer during pregnancy, the radiotherapy team should be equipped with the necessary knowledge to deal with fetal dose. This is crucial so as to ensure that the fetus is adequately protected while not compromising the patient treatment outcomes. In this review paper, various aspects of fetal dose will be discussed ranging from biological, clinical to the physics aspects. Other than fetal dose resulting from conventional photon therapy, this paper will also extend the discussion to modern treatment modalities and techniques, namely proton therapy and image-guided radiotherapy, all of which have seen a significant increase in use in current radiotherapy. This review is expected to provide readers with a comprehensive understanding of fetal dose in radiotherapy, and to be fully aware of the steps to be taken in providing radiotherapy for pregnant patients.

Implementing dispersion measurement as part of scanning proton therapy commissioning and quality assurance.

Introduction. Dispersion in an accelerator quantifies the deviation of the proton trajectory when there is a momentum deviation. We present for the first time a safe method of measuring dispersion in the clinic, using a scintillator detector and the momentum deviations within a spill. This is an important accelerator quantity as we found that this is the reason behind the large dose fluctuation in our absolute dosimetry measurement.Methods. Dispersions are measured for nine energies in a Hitachi ProBeat system at three locations (isocenter and at two profile monitors) and at two gantry angles (0 and 90 degrees) by first measuring the spot position and momentum drift within a spill. The spot position drift is measured by the XRV-4000 at the isocenter, and by the two profile monitors located at 0.57 and 2.27 m from the isocenter. The momentum drift is calculated from the intra-spill range drift which is measured using the Ranger accessory. The dispersion at isocenter and its gradient are calculated using the weighted least square regression on the measured dispersions at the three locations. A constraint is formulated on the dispersion and its gradient to ensure minimal intra-spill spot position deviation around the isocenter.Results. The measured intra-spill range and spot positional drift at isocenter are less than0.25mmand0.7mmrespectively. The momentum spread calculated from the range drift are less than 0.08%. The dispersion at the isocenter ranged from0.50to4.30mand the zero-crossing happens upstream of isocenter for all energies. 2 of the 9 energies (168.0 and 187.5 MeV) violated the constraint and has an intra-spill spot positional deviation greater than1.0within5cmfrom the isocenter.Conclusion. This measurement is recommended as part of commissioning and annual quality assurance for accelerator monitoring and to ensure intra-spill spot deviations remain low.

Inferring cancer disease response from radiology reports using large language models with data augmentation and prompting.

OBJECTIVE: To assess large language models on their ability to accurately infer cancer disease response from free-text radiology reports. MATERIALS AND METHODS: We assembled 10 602 computed tomography reports from cancer patients seen at a single institution. All reports were classified into: no evidence of disease, partial response, stable disease, or progressive disease. We applied transformer models, a bidirectional long short-term memory model, a convolutional neural network model, and conventional machine learning methods to this task. Data augmentation using sentence permutation with consistency loss as well as prompt-based fine-tuning were used on the best-performing models. Models were validated on a hold-out test set and an external validation set based on Response Evaluation Criteria in Solid Tumors (RECIST) classifications. RESULTS: The best-performing model was the GatorTron transformer which achieved an accuracy of 0.8916 on the test set and 0.8919 on the RECIST validation set. Data augmentation further improved the accuracy to 0.8976. Prompt-based fine-tuning did not further improve accuracy but was able to reduce the number of training reports to 500 while still achieving good performance. DISCUSSION: These models could be used by researchers to derive progression-free survival in large datasets. It may also serve as a decision support tool by providing clinicians an automated second opinion of disease response. CONCLUSIONS: Large clinical language models demonstrate potential to infer cancer disease response from radiology reports at scale. Data augmentation techniques are useful to further improve performance. Prompt-based fine-tuning can significantly reduce the size of the training dataset.

Dose-volume analysis of planned versus accumulated dose as a predictor for late gastrointestinal toxicity in men receiving radiotherapy for high-risk prostate cancer.

Background and purpose: Significant dose deviations have been reported between planned (DP) and accumulated (DA) dose in prostate radiotherapy. This study aimed to develop multivariate analysis (MVA) models associating Grade 1 and 2 gastrointestinal (GI) toxicity with clinical and DP or DA dosimetric variables separately. Materials and methods: Dose volume (DV) metrics were compared between DA and DP for 150 high-risk prostate cancer patients. MV models were generated from significant clinical and dosimetric variables (p < 0.05) at univariate level. Dose-based-region of interest (DB-ROI) metrics were included. Model performance was measured, and additional subgroup analysis were performed. Results: Rectal DA demonstrated a higher intermediate-high dose (V30-65 Gy and DB-ROI at 15-50 mm) compared to DP. Conversely, at the very high dose region, rectal DA (V75 Gy and DB-ROI at 5-10 mm) were significantly lower. In MVA, rectal DB-ROI at 10 mm was predictive for Grade ≥ 1 GI toxicity for DA and DP. Age, rectal DA for D0.03 cc, and rectal DP for DB-ROI 10 mm were predictors for Grade 2 GI toxicity. Subgroup analysis revealed that patients ≥ 72 years old and a rectal DA of ≥ 78.2 Gy were highly predictive of Grade 2 GI toxicity. Conclusions: The dosimetric impact of a higher dose rectal dose in DA due to volumetric changes was minimal and was not predictive of detrimental clinical toxicity apart from rectal D0.03 cc ≥ 78.2 Gy for Grade 2 GI toxicity. The use of the DB-ROI method can provide equivalent predictive power as the DV method in toxicity prediction.