Purpose Accurate dose prediction is essential for automating radiotherapy planning. In spot scanning proton therapy (SSPT), dose evaluation is required at both the plan and field level. Evaluating individual treatment fields is critical to ensuring optimal beam angles are chosen to ensure target coverage and maximum organ-at-risk (OAR) sparing. Currently, however, no knowledge-based tools exist for predicting field-level doses for head and neck cancer (HNC) treated with SSPT. In this work, we aim to develop the first deep learning-based dose prediction model capable of field-level dose prediction for HNC treated with SSPT. Methods A cohort of 62 HNC patients treated with SSPT was compiled for model development and evaluation. Collected patient data included treatment planning CTs, OAR masks, signed distance maps (SDMs), generated beam masks, and dose distributions. An encoder-decoder architecture enhanced with a cross-attention transformer bottleneck was used as the field prediction model. Comparison and ablation studies evaluated the model's performance and determined the benefits of individual model components. Evaluation imaging metrics included mean absolute error, structural similarity index measure, and peak signal-to-noise ratio. Clinical performance was evaluated using dose-volume histogram metrics. Results The best performing model from the ablation study was the full model using OAR masks, SDMs, generated beam masks and four-field dose prediction. The model outperformed the Distance Guided Dose Prediction (DGDP) and DeepLabV3 comparison models. The DGDP and DeepLabV3 comparison models had a mean validation set MAE performance of 1.268 Gy and 1.325 Gy, respectively, compared to our model's mean validation set MAE performance of 0.949 Gy. The model's final mean test set performance was MAE 1.024 Gy, SSIM 0.913, and PSNR 28.495 dB. Conclusions We developed a cross-attention transformer-enhanced deep learning model that accurately predicts per-field dose for HNC treated with SSPT, demonstrating superior performance over state-of-the-art models limited to plan-level dose prediction. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by 2022 Lawrence and Marilyn Matteson Award. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Department of Radiation Oncology, Mayo Clinic, Institutional Review Board determined that this work with study ID 22-005097 was waived from the IRB review board approval requirement (45 CFR 46.104d, category 4) on 6/2/2022. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Research data is subject to patient data privacy laws that protect data from being published externally.

In this study, we investigated whether radiomics features from pre-treatment positron emission tomography (PET) images could be used to predict disease progression in patients with HPV-positive oropharyngeal cancer treated with definitive proton or x-ray radiotherapy. Machine learning models were built using a dataset from Mayo Clinic, Rochester, Minnesota (n = 72) and tested on a dataset from Mayo Clinic, Phoenix, Arizona (n = 22). A total of 71 clinical and radiomics features were considered. The Mann-Whitney U test was used to identify the top 2 clinical and top 20 radiomics features that were significantly different between progression and progression-free patients. Two dimensionality reduction methods were used to define two feature sets (manually filtered or machine-driven). A forward feature selection scheme was conducted on each feature set to build models of increased complexity (number of input features from 1 to 6) and evaluate model robustness and overfitting. The machine-driven features had superior performance and were less prone to overfitting compared to the manually filtered features. The four-variable Gaussian Naïve Bayes model using the 'Radiation Type' clinical feature and three machine-driven features achieved a training accuracy of 79% and testing accuracy of 77%. These results demonstrate that radiomics features can provide risk stratification beyond HPV-status to formulate individualized treatment and follow-up strategies.

Abstract Purpose The Leksell Gamma Knife Icon unit (IU) was introduced recently as an upgrade to the Perfexion unit (PU) at our Gamma Knife practice. In the current study, we sought mainly to characterize dosimetry and targeting accuracy of the IU treatment deliveries using both invasive frame and frameless treatment workflows. Methods Relative output factors were measured by delivering single‐shot 4, 8 and 16 mm radiation profiles in the manufacturer's acrylonitrile butadiene styrene spherical phantom in coronal and sagittal planes using EBT3 film. Resultant dosimetry was compared with the manufacturer's dose calculation and derived output factors were compared with the manufacturer's published value. Geometric consistency of stereotactic coordinates based on cone‐beam computed tomography (CBCT) versus the traditional conventional CT‐based method was characterized using a rigid phantom containing nine fiducial indicators over four separate trials. End‐to‐end (E2E) testing using EBT3 film was designed to evaluate both dosimetric and geometric accuracy for hypothetical framed and frameless workflows. Results Relative output factors as measured by the manufacturer were independently confirmed using EBT3 film measurements to within 2%. The mean 3D radial discrepancy in stereotactic space between CBCT and CT‐based definition over the sampled locations in our rigid geometry phantom was demonstrated to be between 0.40 mm and 0.56 mm over the set of trials, larger than prior reported values. E2E performed in 2D demonstrates sub‐mm (and typically < 0.5 mm) accuracy for framed and frameless workflows; geometric accuracy of framed treatments using CBCT‐defined stereotactic coordinates was shown to be slightly improved in comparison with those defined using conventional CT. Furthermore, in phantom, frameless workflows exhibited better accuracy than framed workflows for fractionated treatments, despite large magnitudes of introduced interfraction setup error. Accuracy of dosimetric delivery was confirmed in terms of qualitative comparisons of dose profiles and in terms of 2D gamma pass rates based on 1%/1 mm criteria. Conclusion The IU was commissioned for clinical use of frameless and framed treatment protocols. The present study outlines an extensive E2E methodology for confirmation of dosimetric and geometric treatment accuracy.

PURPOSE:SABR has demonstrated clinical benefit in oligometastatic prostate cancer. However, the risk of developing new distant metastatic lesions remains high, and only a minority of patients experience durable progression-free response. Therefore, there is a critical need to identify which patients will benefit from SABR alone versus combination SABR and systemic agents. Herein we provide, to our knowledge, the first proof-of-concept of circulating prostate cancer-specific extracellular vesicles (PCEVs) as a noninvasive predictor of outcomes in oligometastatic castration-resistant prostate cancer (omCRPC) treated with SABR.METHODS AND MATERIALS:We analyzed the levels and kinetics of PCEVs in the peripheral blood of 79 patients with omCRPC at baseline and days 1, 7, and 14 after SABR using nanoscale flow cytometry and compared with baseline values from cohorts with localized and widely metastatic prostate cancer. The association of omCRPC PCEV levels with oncological outcomes was determined with Cox regression models.RESULTS:Levels of PCEVs were highest in mCRPC followed by omCRPC and were lowest in localized prostate cancer. High PCEV levels at baseline predicted a shorter median time to distant recurrence (3.5 vs 6.6 months; P = .0087). After SABR, PCEV levels peaked on day 7, and median overall survival was significantly longer in patients with elevated PCEV levels (32.7 vs 27.6 months; P = .003). This suggests that pretreatment PCEV levels reflect tumor burden, whereas early changes in PCEV levels after treatment predict response to SABR. In contrast, radiomic features of 11C-choline positron emission tomography and computed tomography before and after SABR were not predictive of clinical outcomes. Interestingly, PCEV levels and peripheral tumor-reactive CD8 T cells (TTR; CD8+ CD11ahigh) were correlated.CONCLUSIONS:This original study demonstrates that circulating PCEVs can serve as prognostic and predictive markers to SABR to identify patients with "true" omCRPC. In addition, it provides novel insights into the global crosstalk, mediated by PCEVs, between tumors and immune cells that leads to systemic suppression of immunity against CRPC. This work lays the foundation for future studies to investigate the underpinnings of metastatic progression and provide new therapeutic targets (eg, PCEVs) to improve SABR efficacy and clinical outcomes in treatment-resistant CRPC.

Stereotactic ablative radiotherapy (SABR) has demonstrated clinical benefit in oligometastatic prostate cancer patients. However, the risk of developing new distant metastatic lesions remains high and only a minority of patients experience durable progression-free response. Therefore, there is a critical need to identify which subset of oligometastatic patients will benefit from SABR alone versus combination SABR and systemic agents. Herein, we provide the first proof-of-concept for the clinical value of circulating prostate cancer-specific extracellular vesicles (PCEVs) as non-invasive predictor of oncological outcomes in oligometastatic castration-refractory prostate cancer (oCRPC) patients treated with SABR. We have defined PCEVs and analyzed their kinetics in the peripheral blood of 79 oCRPC patients with nanoscale flow cytometry at baseline and days 1, 7, and 14 post-SABR. High PCEV levels at baseline was predictive of shorter time to distant recurrence (3.5 vs 6.6 months, p=0.0087). Following SABR, PCEV levels reached a peak at day 7 and median overall survival was significantly longer in patients with higher PCEV levels (32.7 vs 27.6 months, p=0.003). This suggests that pre-treatment PCEV levels can be a biomarker of tumor burden while early changes post-treatment can predict response to SABR. In contrast, radiomic analyses of 11C-choline PET/CT before and after SABR was not predictive of clinical outcomes. Interestingly, a correlation was noted between PCEV levels and peripheral tumor-reactive CD8 T cells (TTR; CD8+ CD11ahigh). This original study demonstrates that circulating PCEVs can serve as prognostic and predictive marker to SABR in order to identify true oCRPC patients. In addition, we provide novel insights in the global crosstalk mediated by PCEVs between tumors and immune cells which leads to systemic suppression of immunity against CRPC. This work lays the foundation for future studies that investigate the underpinnings of metastatic progression and providing new therapeutic targets (e.g PCEVs) to improve SABR efficacy and clinical outcomes in treatment resistant CRPC.

AbstractStereotactic ablative radiotherapy (SABR) has demonstrated clinical benefit in oligometastatic prostate cancer patients. However, the risk of developing new distant metastatic lesions remains high and only a minority of patients experience durable progression-free response. Therefore, there is a critical need to identify which subset of oligometastatic patients will benefit from SABR alone versus combination SABR and systemic agents. Herein, we provide the first proof-of-concept for the clinical value of circulating prostate cancer-specific extracellular vesicles (PCEVs) as non-invasive predictor of oncological outcomes in oligometastatic castration-refractory prostate cancer (oCRPC) patients treated with SABR.We have defined PCEVs and analyzed their kinetics in the peripheral blood of 79 oCRPC patients with nanoscale flow cytometry at baseline and days 1, 7, and 14 post-SABR. High PCEV levels at baseline was predictive of shorter time to distant recurrence (3.5 vs 6.6 months, p=0.0087). Following SABR, PCEV levels reached a peak at day 7 and median overall survival was significantly longer in patients with higher PCEV levels (32.7 vs 27.6 months, p=0.003). This suggests that pre-treatment PCEV levels can be a biomarker of tumor burden while early changes post-treatment can predict response to SABR. In contrast, radiomic analyses of11C-choline PET/CT before and after SABR was not predictive of clinical outcomes. Interestingly, a correlation was noted between PCEV levels and peripheral tumor-reactive CD8 T cells (TTR; CD8+CD11ahigh).This original study demonstrates that circulating PCEVs can serve as prognostic and predictive marker to SABR in order to identify “true” oCRPC patients. In addition, we provide novel insights in the global crosstalk mediated by PCEVs between tumors and immune cells which leads to systemic suppression of immunity against CRPC. This work lays the foundation for future studies that investigate the underpinnings of metastatic progression and providing new therapeutic targets (e.g PCEVs) to improve SABR efficacy and clinical outcomes in treatment resistant CRPC.

PURPOSE:A customized Collaborative Ocular Melanoma Study (COMS)-style eye plaque may provide superior dosimetric coverage compared with standard models for certain intraocular tumor locations and shapes. This work provides a recipe for developing and validating such customized plaques. METHODS AND MATERIALS:The concept-into-clinical treatment process for a customized COMS-style eye plaque begins with a CAD model design that meets the specifications of the radiation oncologist and surgeon based on magnetic resonance, ultrasound, and clinical measurements, as well as a TG-43 hybrid heterogeneity-corrected dose prediction to model the dose distribution. Next, a 3D printed plastic prototype is created and reviewed. After design approval, a Modulay plaque is commercially fabricated. Quality assurance (QA) is subsequently performed to verify the physical measurements of the Modulay and Silastic and also includes dosimetric measurement of the calibration, depth dose, and dose profiles. Sterilization instructions are provided by the commercial fabricator. This customization procedure and QA methodology is demonstrated with a narrow-slotted plaque that was recently constructed for the treatment of a circumpapillary (e.g., surrounding the optic disk) ocular tumor. RESULTS:The production of a customized COMS-style eye plaque is a multistep process. Dosimetric modeling is recommended to ensure that the design will meet the patient's needs, and QA is essential to confirm that the plaque has the proper dimensions and dose distribution. The customized narrow-slotted plaque presented herein was successfully implemented in the clinic, and provided superior dose coverage of juxtapapillary and circumpapillary tumors compared with standard or notched COMS-style plaques. Plaque development required approximately 30 h of physicist time and a fabrication cost of $1500. CONCLUSION:Customized eye plaques may be used to treat intraocular tumors that cannot be adequately managed with standard models. The procedure by which a customized COMS-style plaque may be designed, fabricated, and validated was presented along with a clinical example.

PURPOSE:Methylation of the O6-methylguanine methyltransferase (MGMT) gene promoter is associated with improved treatment response and survival in patients with glioblastoma (GB), but the necessary pathologic specimen can be nondiagnostic. In this study, we assessed whether radiomics features from pretreatment 18F-DOPA positron emission tomography (PET) imaging could be used to predict pathologic MGMT status. METHODS AND MATERIALS:This study included 86 patients with newly diagnosed GB, split into 3 groups (training, validating, and predicting). We performed a radiomics analysis on 18F-DOPA PET images by extracting features from 2 tumor-based contours: a "Gold" contour of all abnormal uptake per expert nuclear medicine physician and a high-grade glioma (HGG) contour based on a tumor-to-normal hemispheric ratio >2.0, representing the most aggressive components. Feature selection was performed by comparing the weighted feature importance and filtering with bivariate analysis. Optimization of model parameters was explored using grid search with selected features. The stability of the model with increasing input features was also investigated for model robustness. The model predictions were then applied by comparing the overall survival probability of the patients with GB and unknown MGMT status versus those with known MGMT status. RESULTS:A radiomics signature was constructed to predict MGMT methylation status. Using features extracted from HGG contour alone with a random forest model, we achieved 80% ± 10% accuracy for 95% confidence level in predicting MGMT status. The prediction accuracy was not improved with the addition of the Gold contour or with more input features. The model was applied to the patients with unknown MGMT methylation status. The prediction results are consistent with what is expected using overall survival as a surrogate. CONCLUSIONS:This study suggests that 3 features from radiomics modeling of 18F-DOPA PET imaging can predict MGMT methylation status with reasonable accuracy. These results could provide valuable therapeutic guidance for patients in whom MGMT testing is inconclusive or nondiagnostic.

E. A. McCutchan,1,2 R. F. Casten,1 V. Werner,1 R. J. Casperson,1 A. Heinz,1 J. Qian,1 B. Shoraka,1,3 J. R. Terry,1 E. Williams,1 and R. Winkler1 1Wright Nuclear Structure Laboratory, Yale University, New Haven, Connecticut 06520, USA 2National Nuclear Data Center, Brookhaven National Laboratory, Upton, New York 11973, USA 3University of Surrey, Guildford, Surrey GU2 7XH, United Kingdom (Received 5 April 2013; published 28 May 2013)

The Gamma-Ray Energy Tracking In-beam Nuclear Array (GRETINA) is a new generation high-resolution γ-ray spectrometer consisting of electrically segmented high-purity germanium crystals. GRETINA is capable of reconstructing the energy and position of each γ-ray interaction point inside the crystal with high resolution. This enables γ-ray energy tracking which in turn provides an array with large photopeak efficiency, high resolution and good peak-to-total ratio. GRETINA is used for nuclear structure studies with demanding γ-ray detection requirements and it is suitable for experiments with radioactive-ion beams with high recoil velocities. The GRETINA array has a 1π solid angle coverage and constitutes the first stage towards the full 4π array GRETA. We present in this paper the main parts and the performance of the GRETINA system.

Centrifugal stretching in the deformed rare-earth nucleus 170Hf is investigated using high-precision lifetime measurements, performed with the New Yale Plunger Device at Wright Nuclear Structure Laboratory, Yale University. Excited states were populated in the fusion-evaporation reaction 124Sn(50Ti,4n)170Hf at a beam energy of 195 MeV. Recoil distance doppler shift data were recorded for the ground state band through the J=16+ level. The measured B(E2) values and transition quadrupole moments improve on existing data and show increasing β deformation in the ground state band of 170Hf. The results are compared to descriptions by a rigid rotor and by the confined β-soft rotor model. © 2013 American Physical Society.

Excited states in Nd-132,Nd-134 were populated in the beta(+)/epsilon decay of Pm-132,Pm-134 and studied through off-beam gamma-ray spectroscopy. Level spins and multipole mixing ratios of transitions were determined through an angular correlation analysis. In Nd-132, a new excited 0(+) state is identified and in Nd-134 the level scheme is significantly extended. Differences in the location of the 0(2)(+) state and the gamma bandhead above and below N = 82 suggest that the lighter isotopes are much more gamma-soft than the heavier Nd and that a first-order phase transitional description is not applicable in the N < 82 region.

The $g$ factor of the ${2}_{1}^{+}$ state of ${}^{168}$Hf was measured using the perturbed angular correlation technique in a static external magnetic field. The result, $g({2}_{1}^{+})=0.17(3)$, is discussed in relation to the systematics of the previously reported $g$ factors in the Hf isotopes and compared to the predictions of several models. An interesting outcome of the analysis presented in this paper has to do with the relatively small result for the $g$ factor. This indicates that in the Hf isotopes, a minimum in the $g$(${2}_{1}^{+}$) dependence on $N$ occurs at $N\ensuremath{\le}98$ and not at midshell, as expected from IBA-2 or large-scale shell-model calculations. The pairing plus quadrupole model of Kumar and Baranger predicts a minimum at $N=98$ and gives the best description of the experimental data. The present result clearly shows the importance of $g$-factor measurements in ``fine-tuning'' among different models.