Effects of model size and composition on quality of head-and-neck knowledge-based plans.

PURPOSE: Knowledge-based planning (KBP) aims to automate and standardize treatment planning. New KBP users are faced with many questions: How much does model size matter, and are multiple models needed to accommodate specific physician preferences? In this study, six head-and-neck KBP models were trained to address these questions. METHODS: The six models differed in training size and plan composition: The KBPFull (n = 203 plans), KBP101 (n = 101), KBP50 (n = 50), and KBP25 (n = 25) were trained with plans from two head-and-neck physicians. KBPA and KBPB each contained n = 101 plans from only one physician, respectively. An independent set of 39 patients treated to 6000-7000 cGy by a third physician was re-planned with all KBP models for validation. Standard head-and-neck dosimetric parameters were used to compare resulting plans. KBPFull plans were compared to the clinical plans to evaluate overall model quality. Additionally, clinical and KBPFull plans were presented to another physician for blind review. Dosimetric comparison of KBPFull against KBP101 , KBP50 , and KBP25 investigated the effect of model size. Finally, KBPA versus KBPB tested whether training KBP models on plans from one physician only influences the resulting output. Dosimetric differences were tested for significance using a paired t-test (p < 0.05). RESULTS: Compared to manual plans, KBPFull significantly increased PTV Low D95% and left parotid mean dose but decreased dose cochlea, constrictors, and larynx. The physician preferred the KBPFull plan over the manual plan in 20/39 cases. Dosimetric differences between KBPFull , KBP101 , KBP50 , and KBP25 plans did not exceed 187 cGy on aggregate, except for the cochlea. Further, average differences between KBPA and KBPB were below 110 cGy. CONCLUSIONS: Overall, all models were shown to produce high-quality plans. Differences between model outputs were small compared to the prescription. This indicates only small improvements when increasing model size and minimal influence of the physician when choosing treatment plans for training head-and-neck KBP models.

Assessment of specific versus combined purpose knowledge based models in prostate radiotherapy.

Knowledge-based planning (KBP) can be used to improve plan quality, planning speed, and reduce the inter-patient plan variability. KPB may also identify and reduce systematic variations in VMAT plans, something very important in multi-institutional clinical trials. Training of a KBP library is a complex and difficult process, and models must be validated prior to their clinical use. The purpose of this work is to assess the quality of the treatment plans generated using a specific versus combined purpose model KBP library for prostate cancer. Seven KBP model libraries were created from a set of patients treated on various Institutional Review Board (IRB) approved protocols. All KBP libraries were validated using an independent set of twenty patients (half treated Pr: Prostate alone half treated PLN: prostate plus pelvic lymph nodes). Two models were tested on the Pr patients only, four tested on PLN patients only, and one tested on all patients. All plans were normalized such that at least 95% of the prostate planning target volume received 100% of the planned dose. The plans based on different model libraries were compared to each other and the expert clinical plan. For Pr plans there were almost no statistically significant differences (P < 0.008) between the plans types except conformity index (CI) with library plans better than the expert. For PLN plans, all model libraries in generally showed femur doses and CI better than the expert plans (P < 0.003). This study demonstrated that no large differences were observed between specific versus combined KBP model libraries in dosimetry of prostate cancer patients. This would allow for a fewer specific plans to be needed to create a model library. Further studies are needed to evaluate benefits of combined purpose model libraries for planning of complex sites such as head and neck cancer.

Validation of a deformable MRI to CT registration algorithm employing same day planning MRI for surrogate analysis.

PURPOSE: Validating deformable multimodality image registrations is challenging due to intrinsic differences in signal characteristics and their spatial intensity distributions. Evaluating multimodality registrations using these spatial intensity distributions is also complicated by the fact that these metrics are often employed in the registration optimization process. This work evaluates rigid and deformable image registrations of the prostate in between diagnostic-MRI and radiation treatment planning-CT by utilizing a planning-MRI after fiducial marker placement as a surrogate. The surrogate allows for the direct quantitative analysis that can be difficult in the multimodality domain. METHODS: For thirteen prostate patients, T2 images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day as the planning-CT (planning-MRI). The diagnostic-MRI was deformed to the planning-CT utilizing a commercially available algorithm which synthesizes a deformable image registration (DIR) algorithm from local rigid registrations. The planning-MRI provided an independent surrogate for the planning-CT for assessing registration accuracy using image similarity metrics, including Pearson correlation and normalized mutual information (NMI). A local analysis was performed by looking only within the prostate, proximal seminal vesicles, penile bulb, and combined areas. RESULTS: The planning-MRI provided an excellent surrogate for the planning-CT with residual error in fiducial alignment between the two datasets being submillimeter, 0.78 mm. DIR was superior to the rigid registration in 11 of 13 cases demonstrating a 27.37% improvement in NMI (P < 0.009) within a regional area surrounding the prostate and associated critical organs. Pearson correlations showed similar results, demonstrating a 13.02% improvement (P < 0.013). CONCLUSION: By utilizing the planning-MRI as a surrogate for the planning-CT, an independent evaluation of registration accuracy is possible. This population provides an ideal testing ground for MRI to CT DIR by obviating the need for multimodality comparisons which are inherently more challenging.

Evaluation of the tool "Reg Refine" for user-guided deformable image registration.

"Reg Refine" is a tool available in the MIM Maestro v6.4.5 platform (www.mim-software.com) that allows the user to actively participate in the deformable image registration process. The purpose of this work was to evaluate the efficacy of this tool and investigate strategies for how to apply it effectively. This was done by performing DIR on two publicly available ground-truth models, the Pixel-based Breathing Thorax Model (POPI) for lung, and the Deformable Image Registration Evaluation Project (DIREP) for head and neck. Image noise matched in both magnitude and texture to clinical CBCT scans was also added to each model to simulate the use case of CBCT-CT alignment. For lung, the results showed Reg Refine effective at improving registration accuracy when controlled by an expert user within the context of large lung deformation. CBCT noise was also shown to have no effect on DIR performance while using the MIM algorithm for this site. For head and neck, the results showed CBCT noise to have a large effect on the accuracy of registration, specifically for low-contrast structures such as the brain-stem and parotid glands. In these cases, the Reg Refine tool was able to improve the registration accuracy when controlled by an expert user. Several strategies for how to achieve these results have been outlined to assist other users and provide feedback for developers of similar tools.

Quantification of the margin required for treating intraprostatic lesions.

Advances in magnetic resonance imaging (MRI) sequences allow physicians to define the dominant intraprostatic lesion (IPL) in prostate radiation therapy treat-ments allowing for dose escalation and potentially increased tumor control. This work quantifies the margin required around the MRI-defined IPL accounting for both prostate motion and deformation. Ten patients treated with a simultaneous integrated intraprostatic boost (SIIB) were retrospectively selected and replanned with incremental 1 mm margins from 0-5 mm around the IPL to determine if there were any significant differences in dosimetric parameters. Sensitivity analysis was then performed accounting for random and systematic uncertainties in both prostate motion and deformation to ensure adequate dose was delivered to the IPL. Prostate deformation was assessed using daily CBCT imaging and implanted fiducial markers. The average IPL volume without margin was 2.3% of the PTV volume and increased to 11.8% with a 5 mm margin. Despite these changes in vol-ume, the only statistically significant dosimetric difference was found for the PTV maximum dose, which increased with increasing margin. The sensitivity analysis demonstrated that a 3.0 mm margin ensures > 95% IPL coverage accounting for both motion and deformation. We found that a margin of 3.0 mm around the MRI defined IPL is sufficient to account for random and systematic errors in IPL posi-tion for the majority of cases.

Increasing the efficiency of cone-beam CT based delta-radiomics using automated contours to predict radiotherapy-related toxicities in prostate cancer.

Extracting longitudinal image quantitative data, known as delta-radiomics, has the potential to capture changes in a patient's anatomy throughout the course of radiation treatment for prostate cancer. Some of the major challenges of delta-radiomics studies are contouring the structures for individual fractions and accruing patients' data in an efficient manner. The manual contouring process is often time consuming and would limit the efficiency of accruing larger sample sizes for future studies. The problem is amplified because the contours are often made by highly trained radiation oncologists with limited time to dedicate to research studies of this nature. This work compares the use of automated prostate contours generated using a deformable image-based algorithm to make predictive models of genitourinary and changes in total international prostate symptom score in comparison to manually contours for a cohort of fifty patients. Area under the curve of manual and automated models were compared using the Delong test. This study demonstrated that the delta-radiomics models were similar for both automated and manual delta-radiomics models.

Cone beam CT-based adaptive intensity modulated proton therapy assessment using automated planning for head-and-neck cancer.

BACKGROUND: To assess the feasibility of CBCT-based adaptive intensity modulated proton therapy (IMPT) using automated planning for treatment of head and neck (HN) cancers. METHODS: Twenty HN cancer patients who received radiotherapy and had pretreatment CBCTs were included in this study. Initial IMPT plans were created using automated planning software for all patients. Synthetic CTs (sCT) were then created by deforming the planning CT (pCT) to the pretreatment CBCTs. To assess dose calculation accuracy on sCTs, repeat CTs (rCTs) were deformed to the pretreatment CBCT obtained on the same day to create deformed rCT (rCTdef), serving as gold standard. The dose recalculated on sCT and on rCTdef were compared by using Gamma analysis. The accuracy of DIR generated contours was also assessed. To explore the potential benefits of adaptive IMPT, two sets of plans were created for each patient, a non-adapted IMPT plan and an adapted IMPT plan calculated on weekly sCT images. The weekly doses for non-adaptive and adaptive IMPT plans were accumulated on the pCT, and the accumulated dosimetric parameters of two sets were compared. RESULTS: Gamma analysis of the dose recalculated on sCT and rCTdef resulted in a passing rate of 97.9% ± 1.7% using 3 mm/3% criteria. With the physician-corrected contours on the sCT, the dose deviation range of using sCT to estimate mean dose for the most organ at risk (OARs) can be reduced to (- 2.37%, 2.19%) as compared to rCTdef, while for V95 of primary or secondary CTVs, the deviation can be controlled within (- 1.09%, 0.29%). Comparison of the accumulated doses from the adaptive planning against the non-adaptive plans reduced mean dose to constrictors (- 1.42 Gy ± 2.79 Gy) and larynx (- 2.58 Gy ± 3.09 Gy). The reductions result in statistically significant reductions in the normal tissue complication probability (NTCP) of larynx edema by 7.52% ± 13.59%. 4.5% of primary CTVs, 4.1% of secondary CTVs, and 26.8% tertiary CTVs didn't meet the V95 > 95% constraint on non-adapted IMPT plans. All adaptive plans were able to meet the coverage constraint. CONCLUSION: sCTs can be a useful tool for accurate proton dose calculation. Adaptive IMPT resulted in better CTV coverage, OAR sparing and lower NTCP for some OARs as compared with non-adaptive IMPT.

In vivo active-targeting fluorescence molecular imaging with adaptive background fluorescence subtraction.

Using active tumor-targeting nanoparticles, fluorescence imaging can provide highly sensitive and specific tumor detection, and precisely guide radiation in translational radiotherapy study. However, the inevitable presence of non-specific nanoparticle uptake throughout the body can result in high levels of heterogeneous background fluorescence, which limits the detection sensitivity of fluorescence imaging and further complicates the early detection of small cancers. In this study, background fluorescence emanating from the baseline fluorophores was estimated from the distribution of excitation light transmitting through tissues, by using linear mean square error estimation. An adaptive masked-based background subtraction strategy was then implemented to selectively refine the background fluorescence subtraction. First, an in vivo experiment was performed on a mouse intratumorally injected with passively targeted fluorescent nanoparticles, to validate the reliability and robustness of the proposed method in a stringent situation wherein the target fluorescence was overlapped with the strong background. Then, we conducted in vivo studies on 10 mice which were inoculated with orthotopic breast tumors and intravenously injected with actively targeted fluorescent nanoparticles. Results demonstrated that active targeting combined with the proposed background subtraction method synergistically increased the accuracy of fluorescence molecular imaging, affording sensitive tumor detection.

AAPM Task Group Report 307: Use of EPIDs for Patient-Specific IMRT and VMAT QA.

PURPOSE: Electronic portal imaging devices (EPIDs) have been widely utilized for patient-specific quality assurance (PSQA) and their use for transit dosimetry applications is emerging. Yet there are no specific guidelines on the potential uses, limitations, and correct utilization of EPIDs for these purposes. The American Association of Physicists in Medicine (AAPM) Task Group 307 (TG-307) provides a comprehensive review of the physics, modeling, algorithms and clinical experience with EPID-based pre-treatment and transit dosimetry techniques. This review also includes the limitations and challenges in the clinical implementation of EPIDs, including recommendations for commissioning, calibration and validation, routine QA, tolerance levels for gamma analysis and risk-based analysis. METHODS: Characteristics of the currently available EPID systems and EPID-based PSQA techniques are reviewed. The details of the physics, modeling, and algorithms for both pre-treatment and transit dosimetry methods are discussed, including clinical experience with different EPID dosimetry systems. Commissioning, calibration, and validation, tolerance levels and recommended tests, are reviewed, and analyzed. Risk-based analysis for EPID dosimetry is also addressed. RESULTS: Clinical experience, commissioning methods and tolerances for EPID-based PSQA system are described for pre-treatment and transit dosimetry applications. The sensitivity, specificity, and clinical results for EPID dosimetry techniques are presented as well as examples of patient-related and machine-related error detection by these dosimetry solutions. Limitations and challenges in clinical implementation of EPIDs for dosimetric purposes are discussed and acceptance and rejection criteria are outlined. Potential causes of and evaluations of pre-treatment and transit dosimetry failures are discussed. Guidelines and recommendations developed in this report are based on the extensive published data on EPID QA along with the clinical experience of the TG-307 members. CONCLUSION: TG-307 focused on the commercially available EPID-based dosimetric tools and provides guidance for medical physicists in the clinical implementation of EPID-based patient-specific pre-treatment and transit dosimetry QA solutions including intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) treatments.

A protocol to extend the longitudinal coverage of on-board cone-beam CT.

The longitudinal coverage of a LINAC-mounted CBCT scan is limited to the corresponding dimensional limits of its flat panel detector, which is often shorter than the length of the treatment field. These limits become apparent when fields are designed to encompass wide regions, as when providing nodal coverage. Therefore, we developed a novel protocol to acquire double orbit CBCT images using a commercial system, and combine the images to extend the longitudinal coverage for image-guided adaptive radiotherapy (IGART). The protocol acquires two CBCT scans with a couch shift similar to the "step-and-shoot" cine CT acquisition, allowing a small longitudinal overlap of the two reconstructed volumes. An in-house DICOM reading/writing software was developed to combine the two image sets into one. Three different approaches were explored to handle the possible misalignment between the two image subsets: simple stacking, averaging the overlapped volumes, and a 3D-3D image registration with the three translational degrees of freedom. Using thermoluminescent dosimeters and custom-designed holders for a CTDI phantom set, dose measurements were carried out to assess the resultant imaging dose of the technique and its geometric distribution. Deformable registration was tested on patient images generated with the double-orbit protocol, using both the planning FBCT and the artificially deformed CBCT as source images. The protocol was validated on phantoms and has been employed clinically for IRB-approved IGART studies for head and neck and prostate cancer patients.

A novel edge gradient distance metric for automated evaluation of deformable image registration quality.

PURPOSE: To develop a new registration quality metric, based on the distance between image edges, for automated evaluation and comparison of DIR algorithms. METHODS: Canny filter is used to create binary gradient images from input images to be compared. A small subregion of one binary image is translated relative to the other. The translational distance maximizing overlap of edges in the subregion is the local edge gradient distance to agreement (EGDTA); repeating over all subregions provides an EGDTA map. The method was tested on phantom and pelvic CT images, by applying a known deformable vector field (DVF). The method was then applied to evaluate two DIR algorithms (SICLE and Demons) for pelvic CTs from five patients. Three SICLE variants were used: Grayscale-driven (G), Contour-driven (C), and Grayscale + Contour-driven (G + C). For each patient, a planning CT was registered to three repeat CTs using the above DIR algorithms. Mean EGDTA values in concentric ring regions of interest close to and far away from the pelvic organ contours were compared. RESULTS: EGDTA maps and imposed DVF deformations on phantom and CT images demonstrated agreement. In comparison of the three variants of SICLE: C had lower EGDTA values close to the pelvic organs, while G showed much better performance in the regions distant from the organs compared to C; and G + C registration exhibited the lowest or comparable EGDTA value among three variants. Demons achieved the lowest EGDTA values. CONCLUSIONS: The EGDTA metric shows potential as an automated means of evaluating and comparing DIR algorithms.

Assessment of IMPT versus VMAT plans using different uncertainty scenarios for prostate cancer.

BACKGROUND: To assess the impact of systematic setup and range uncertainties for robustly optimized (RO) intensity modulated proton therapy (IMPT) and volumetric modulated arc therapy (VMAT) plans in patients with localized prostate cancer. METHODS: Twenty-six localized prostate patients previously treated with VMAT (CTV to PTV expansion of 3-5 mm) were re-planned with RO-IMPT with 3 mm and 5 mm geometrical uncertainties coupled with 3% range uncertainties. Robust evaluations (RE) accounting for the geometrical uncertainties of 3 and 5 mm were evaluated for the IMPT and VMAT plans. Clinical target volume (CTV), anorectum, and bladder dose metrics were analyzed between the nominal plans and their uncertainty perturbations. RESULTS: With geometric uncertainties of 5 mm and accounting for potential inter-fractional perturbations, RO-IMPT provided statistically significant (p < 0.05) sparing at intermediate doses (V4000cGy) to the anorectum and bladder and high dose sparring (V8000cGy) to the bladder compared to VMAT. Decreasing the RO and RE parameters to 3 mm improved IMPT sparing over VMAT at all OAR dose levels investigated while maintaining equivalent coverage to the CTV. CONCLUSIONS: For localized prostate treatments, if geometric uncertainties can be maintained at or below 3 mm, RO-IMPT provides clear dosimetric advantages in anorectum and bladder sparing compared to VMAT. This advantage remains even under uncertainty scenarios. As geometric uncertainties increase to 5 mm, RO-IMPT still provides dosimetric advantages, but to a smaller magnitude.

Boosted Radiation Bystander Effect of PSMA-Targeted Gold Nanoparticles in Prostate Cancer Radiosensitization.

Metal nanoparticles are effective radiosensitizers that locally enhance radiation doses in targeted cancer cells. Compared with other metal nanoparticles, gold nanoparticles (GNPs) exhibit high biocompatibility, low toxicity, and they increase secondary electron scatter. Herein, we investigated the effects of active-targeting GNPs on the radiation-induced bystander effect (RIBE) in prostate cancer cells. The impact of GNPs on the RIBE presents implications for secondary cancers or spatially fractionated radiotherapy treatments. Anti-prostate-specific membrane antigen (PSMA) antibodies were conjugated with PEGylated GNPs through EDC-NHS chemistry. The media transfer technique was performed to induce the RIBE on the non-irradiated bystander cells. This study focused on the LNCaP cell line, because it can model a wide range of stages relating to prostate cancer progression, including the transition from androgen dependence to castration resistance and bone metastasis. First, LNCaP cells were pretreated with phosphate buffered saline (PBS) or PSMA-targeted GNPs (PGNPs) for 24 h and irradiated with 160 kVp X-rays (0-8 Gy). Following that, the collected culture media were filtered (sterile 0.45 µm polyethersulfone) in order to acquire PBS- and PGNP- conditioned media (CM). Then, PBS- and PGNP-CM were transferred to the bystander cells that were loaded with/without PGNPs. MTT, γ-H2AX, clonogenic assays and reactive oxygen species assessments were performed to compare RIBE responses under different treatments. Compared with 2 Gy-PBS-CM, 8 Gy-PBS-CM demonstrated a much higher RIBE response, thus validating the dose dependence of RIBE in LNCaP cells. Compared with PBS-CM, PGNP-CM exhibited lower cell viability, higher DNA damage, and a smaller survival fraction. In the presence of PBS-CM, bystander cells loaded with PGNPs showed increased cell death compared with cells that did not have PGNPs. These results demonstrate the PGNP-boosted expression and sensitivity of RIBE in prostate cancer cells.

Quantifying Radiosensitization of PSMA-Targeted Gold Nanoparticles on Prostate Cancer Cells at Megavoltage Radiation Energies by Monte Carlo Simulation and Local Effect Model.

Active targeting gold nanoparticles (AuNPs) are a very promising avenue for cancer treatment with many publications on AuNP mediated radiosensitization at kilovoltage (kV) photon energies. However, uncertainty on the effectiveness of AuNPs under clinically relevant megavoltage (MV) radiation energies hinders the clinical translation of AuNP-assisted radiation therapy (RT) paradigm. The aim of this study was to investigate radiosensitization mediated by PSMA-targeted AuNPs irradiated by a 6 MV radiation beam at different depths to explore feasibility of AuNP-assisted prostate cancer RT under clinically relevant conditions. PSMA-targeted AuNPs (PSMA-AuNPs) were synthesized by conjugating PSMA antibodies onto PEGylated AuNPs through EDC/NHS chemistry. Confocal fluorescence microscopy was used to verify the active targeting of the developed PSMA-AuNPs. Transmission electron microscopy (TEM) was used to demonstrate the intracellular biodistribution of PSMA-AuNPs. LNCaP prostate cancer cells treated with PSMA-AuNPs were irradiated on a Varian 6 MV LINAC under varying depths (2.5 cm, 10 cm, 20 cm, 30 cm) of solid water. Clonogenic assays were carried out to determine the in vitro cell survival fractions. A Monte Carlo (MC) model developed on TOPAS platform was then employed to determine the nano-scale radial dose distribution around AuNPs, which was subsequently used to predict the radiation dose response of LNCaP cells treated with AuNPs. Two different cell models, with AuNPs located within the whole cell or only in the cytoplasm, were used to assess how the intracellular PSMA-AuNP biodistribution impacts the prostate cancer radiosensitization. Then, MC-based microdosimetry was combined with the local effect model (LEM) to calculate cell survival fraction, which was benchmarked against the in vitro clonogenic assays at different depths. In vitro clonogenic assay of LNCaP cells demonstrated the depth dependence of AuNP radiosensitization under clinical megavoltage beams, with sensitization enhancement ratio (SER) of 1.14 ± 0.03 and 1.55 ± 0.05 at 2.5 cm depth and 30 cm depth, respectively. The MC microdosimetry model showed the elevated percent of low-energy photons in the MV beams at greater depth, consequently resulting in increased dose enhancement ratio (DER) of AuNPs with depth. The AuNP-induced DER reached ~5.7 and ~8.1 at depths of 2.5 cm and 30 cm, respectively. Microdosimetry based LEM accurately predicted the cell survival under 6 MV beams at different depths, for the cell model with AuNPs placed only in the cell cytoplasm. TEM results demonstrated the distribution of PSMA-AuNPs in the cytoplasm, confirming the accuracy of MC microdosimetry based LEM with modelled AuNPs distributed within the cytoplasm. We conclude that AuNP radiosensitization can be achieved under megavoltage clinical radiotherapy energies with a dependence on tumor depth. Furthermore, the combination of Monte Carlo microdosimetry and LEM will be a valuable tool to assist with developing AuNP-aided radiotherapy paradigm and drive clinical translation.

MRI-based delta-radiomic features for prediction of local control in liver lesions treated with stereotactic body radiation therapy.

Real-time magnetic resonance image guided stereotactic ablative radiotherapy (MRgSBRT) is used to treat abdominal tumors. Longitudinal data is generated from daily setup images. Our study aimed to identify delta radiomic texture features extracted from these images to predict for local control in patients with liver tumors treated with MRgSBRT. Retrospective analysis of an IRB-approved database identified patients treated with MRgSBRT for primary liver and secondary metastasis histologies. Daily low field strength (0.35 T) images were retrieved, and the gross tumor volume was identified on each image. Next, images' gray levels were equalized, and 39 s-order texture features were extracted. Delta-radiomics were calculated as the difference between feature values on the initial scan and after delivered biological effective doses (BED, α/ß = 10) of 20 Gy and 40 Gy. Then, features were ranked by the Gini Index during training of a random forest model. Finally, the area under the receiver operating characteristic curve (AUC) was estimated using a bootstrapped logistic regression with the top two features. We identified 22 patients for analysis. The median dose delivered was 50 Gy in 5 fractions. The top two features identified after delivery of BED 20 Gy were gray level co-occurrence matrix features energy and gray level size zone matrix based large zone emphasis. The model generated an AUC = 0.9011 (0.752-1.0) during bootstrapped logistic regression. The same two features were selected after delivery of a BED 40 Gy, with an AUC = 0.716 (0.600-0.786). Delta-radiomic features after a single fraction of SBRT predicted local control in this exploratory cohort. If confirmed in larger studies, these features may identify patients with radioresistant disease and provide an opportunity for physicians to alter management much sooner than standard restaging after 3 months. Expansion of the patient database is warranted for further analysis of delta-radiomic features.

Predictive Value of Delta-Radiomics Texture Features in 0.35 Tesla Magnetic Resonance Setup Images Acquired During Stereotactic Ablative Radiotherapy of Pancreatic Cancer.

Purpose: The purpose of this work is to explore delta-radiomics texture features for predicting response using setup images of pancreatic cancer patients treated with magnetic resonance image guided (MRI-guided) stereotactic ablative radiotherapy (SBRT). Methods: The total biological effective dose (BED) was calculated for 30 patients treated with MRI-guided SBRT that delivered physical doses of 30-60 Gy in three to five fractions. Texture features were then binned into groups based upon BED per fraction by dividing BED by the number of fractions. Delta-radiomics texture features were calculated after delivery of 20 Gy BED (BED20 features) and 40 Gy BED (BED40 features). A random forest (RF) model was constructed using BED20 and then BED40 features to predict binary outcome. During model training, the Gini Index, a measure of a variable's importance for accurate prediction, was calculated for all features, and the two features that ranked the highest were selected for internal validation. The two features selected from each bin were used in a bootstrapped logistic regression model to predict response and performance quantified using the area under the receiver operating characteristic curve (AUC). This process was an internal validation analysis. Results: After RF model training, the Gini Index was highest for gray-level co-occurrence matrix-based (GLCM) sum average, and neighborhood gray tone difference matrix-based (NGTDM) busyness for BED20 features and gray-level size zone matrix-based (GLSZM) large zones low gray-level emphasis and gray-level run length matrix-based (GLRLM) run percentage was selected from the BED40-based features. The mean AUC obtained using the two BED20 features was AUC = 0.845 with the 2.5 percentile and 97.5 percentile values ranging from 0.794 to 0.856. Internal validation of the BED40 delta-radiomics features resulted in a mean AUC = 0.567 with a 2.5 and 97.5 percentile range of 0.502-0.675. Conclusion: Early changes in treatment quantified with the BED20 delta-radiomics texture features in low field images acquired during MRI-guided SBRT demonstrated better performance in internal validation than features calculated later in treatment. Further analysis of delta-radiomics texture analysis in low field MRI is warranted.

Cone-beam CT delta-radiomics to predict genitourinary toxicities and international prostate symptom of prostate cancer patients: a pilot study.

For prostate cancer (PCa) patients treated with definitive radiotherapy (RT), acute and late RT-related genitourinary (GU) toxicities adversely impact disease-specific quality of life. Early warning of potential RT toxicities can prompt interventions that may prevent or mitigate future adverse events. During intensity modulated RT (IMRT) of PCa, daily cone-beam computed tomography (CBCT) images are used to improve treatment accuracy through image guidance. This work investigated the performance of CBCT-based delta-radiomic features (DRF) models to predict acute and sub-acute International Prostate Symptom Scores (IPSS) and Common Terminology Criteria for Adverse Events (CTCAE) version 5 GU toxicity grades for 50 PCa patients treated with definitive RT. Delta-radiomics models were built using logistic regression, random forest for feature selection, and a 1000 iteration bootstrapping leave one analysis for cross validation. To our knowledge, no prior studies of PCa have used DRF models based on daily CBCT images. AUC of 0.83 for IPSS and greater than 0.7 for CTCAE grades were achieved as early as week 1 of treatment. DRF extracted from CBCT images showed promise for the development of models predictive of RT outcomes. Future studies will include using artificial intelligence and machine learning to expand CBCT sample sizes available for radiomics analysis.

Assessment of single isocenter linear accelerator radiosurgery for metastases and base of skull lesions.

BACKGROUND: Newer technology for stereotactic radiosurgery (SRS) should be assessed for different multi-leaf collimators (MLC). OBJECTIVE: Assess plan quality of an automated, frameless, linear accelerator based (linac) planning and delivery system (HyperArc) for SRS using both standard MLC (SMLC) and high definition MLC (HDMLC) compared to a cobalt-60 based SRS system (Gamma Knife, GK). METHODS: We re-planned twenty GK Perfexion-treated SRS patients (27 lesions) for HyperArc using SMLC and HDMLC. We assessed plan quality using the following metrics: gradient index (GI), Paddick and RTOG conformity indices (CIPaddick, CIRTOG), volume receiving half of prescription isodose (PIVhalf) and maximum dose to 0.03 cc for brainstem, optic chiasm and optic nerves, and V12Gy for brain-GTV. RESULTS: Linac plans had better conformity with HDMLC being most conformal. GK exhibited better GI. PIVhalf demonstrated no statistically significant difference between HDMLC and GK, and SMLC was nominally worse than GK. Mean PIVhalf was generally 0.85 cc larger for SMLC than HDMLC. For TV > 1.0 cc, the relative differences in CIRTOG, GI, and PIVhalf for SMLC vs. HDMLC were less than 21%. For TV less than < 1.0 cc, there were more obvious relative differences for SMLC vs. HDMLC in CIRTOG (mean 146%, max 700%), GI (mean 49%, max 162%), and PIVhalf (mean 77%, max 522%). Organ at risk doses were met in all plans. CONCLUSIONS: New linac-based plans positively compare to GK plans overall. HDMLC should be strongly considered for treatment of lesions < 1.0 cc given the significant improvements in conformity and PIVhalf over SMLC.

Knowledge-Based Planning for Robustly Optimized Intensity-Modulated Proton Therapy of Head and Neck Cancer Patients.

PURPOSE: To assess the performance of a proton-specific knowledge-based planning (KBP) model in the creation of robustly optimized intensity-modulated proton therapy (IMPT) plans for treatment of advanced head and neck (HN) cancer patients. METHODS: Seventy-three patients diagnosed with advanced HN cancer previously treated with volumetric modulated arc therapy (VMAT) were selected and replanned with robustly optimized IMPT. A proton-specific KBP model, RapidPlanPT (RPP), was generated using 53 patients (20 unilateral cases and 33 bilateral cases). The remaining 20 patients (10 unilateral and 10 bilateral cases) were used for model validation. The model was validated by comparing the target coverage and organ at risk (OAR) sparing in the RPP-generated IMPT plans with those in the expert plans. To account for the robustness of the plan, all uncertainty scenarios were included in the analysis. RESULTS: All the RPP plans generated were clinically acceptable. For unilateral cases, RPP plans had higher CTV_primary V100 (1.59% ± 1.24%) but higher homogeneity index (HI) (0.7 ± 0.73) than had the expert plans. In addition, the RPP plans had better ipsilateral cochlea Dmean (-5.76 ± 6.11 Gy), with marginal to no significant difference between RPP plans and expert plans for all other OAR dosimetric indices. For the bilateral cases, the V100 for all clinical target volumes (CTVs) was higher for the RPP plans than for the expert plans, especially the CTV_primary V100 (5.08% ± 3.02%), with no significant difference in the HI. With respect to OAR sparing, RPP plans had a lower spinal cord Dmax (-5.74 ± 5.72 Gy), lower cochlea Dmean (left, -6.05 ± 4.33 Gy; right, -4.84 ± 4.66 Gy), lower left and right parotid V20Gy (left, -6.45% ± 5.32%; right, -6.92% ± 3.45%), and a lower integral dose (-0.19 ± 0.19 Gy). However, RPP plans increased the Dmax in the body outside of CTV (body-CTV) (1.2 ± 1.43 Gy), indicating a slightly higher hotspot produced by the RPP plans. CONCLUSION: IMPT plans generated by a broad-scope RPP model have a quality that is, at minimum, comparable with, and at times superior to, that of the expert plans. The RPP plans demonstrated a greater robustness for CTV coverage and better sparing for several OARs.

Assessment of intra-fraction motion during automated linac-based SRS treatment delivery with an open face mask system.

PURPOSE/OBJECTIVE: To evaluate intra-fraction target shift during automated mono-isocentric linac-based stereotactic radiosurgery with open-face mask system and optical real-time tracking. MATERIALS/METHODS: Ninety-five patients were treated using automated linac-based stereotactic radiosurgery in 1-5 fractions with single isocenter for a total of 195 fractions. During treatment, patient positioning was tracked real-time with optical surface guidance and immobilized with a rigid open-face mask. Patients were re-positioned if optical surface guidance error exceeded 1 mm magnitude or 1°. Translational and rotational intra-fractional changes were determined by post-treatment CBCT matched to the planning CT. Target specific error was calculated by translation and rotation matrices applied to isocenter and target spatial coordinates. RESULTS: For 132 fractions with isocenter within a single target, the median shift magnitude was 0.40 mm with a maximum shift of 1.17 mm. A total of 398 targets treated for plans having multiple or single targets that lied outside isocenter, resulted in a median shift magnitude of 0.46 mm, with median translational shifts of 0.20 mm and 0.20° rotational shifts. A 1 mm PTV margin was insufficient in 18% of targets at a distance greater than 6 cm away from isocenter, but sufficient for 96% of targets within 6 cm. CONCLUSIONS: The findings of this study support 1 mm PTV expansion due to intra-fraction motion to ensure target coverage for plans with isocenter placement less than 6 cm away from the targets.