Background
Mechanical accuracy should be verified before implementing a proton stereotactic radiosurgery (SRS) program. Linear accelerator (Linac)‐based SRS systems often use electronic portal ...imaging devices (EPIDs) to verify beam isocentricity. Because proton therapy systems do not have EPID, beam isocentricity tests of proton SRS may still rely on films, which are not efficient.
Purpose
To validate that our proton SRS system meets mechanical precision requirements and to present an efficient method to evaluate the couch and gantry's rotational isocentricity for our proton SRS system.
Methods
A dedicated applicator to hold brass aperture for proton SRS system was designed. The mechanical precision of the system was tested using a metal ball and film for 11 combinations of gantry and couch angles. A more efficient quality assurance (QA) procedure was developed, which used a scintillator device to replace the film. The couch rotational isocentricity tests were performed using orthogonal kV x‐rays with the couch rotated isocentrically to five positions (0°, 315°, 270°, 225°, and 180°). At each couch position, the distance between the metal ball in kV images and the imaging isocenter was measured. The gantry isocentricity tests were performed using a cone‐shaped scintillator and proton beams at five gantry angles (0°, 45°, 90°, 135°, and 180°), and the isocenter position and the distance of each beam path to the isocenter were obtained. Daily QA procedure was performed for 1 month to test the robustness and reproducibility of the procedure.
Results
The gantry and couch rotational isocentricity exhibited sub‐mm precision, with most measurements within ±0.5 mm. The 1‐month QA results showed that the procedure was robust and highly reproducible to within ±0.2 mm. The gantry isocentricity test using the cone‐shaped scintillator was accurate and sensitive to variations of ±0.2 mm. The QA procedure was efficient enough to be completed within 30 min. The 1‐month isocentricity position variations were within 0.5 mm, which demonstrating that the overall proton SRS system was stable and precise.
Conclusion
The proton SRS Winston–Lutz QA procedure using a cone‐shaped scintillator was efficient and robust. We were able to verify radiation delivery could be performed with sub‐mm mechanical precision.
To analyze clinical characteristics and survival of patients with primary vaginal cancer.
Retrospective analysis of patients with primary squamous, adenocarcinoma and adenosquamous cell carcinoma of ...the vagina identified from the Mayo Clinic Cancer Registry between 1998 and 2018.
A total of 124 patients were identified: stage I, 39 patients; stage II, 44, stage III, 20 and stage IV, 21. Patients with stage III and IV were older as compared to stage I and II. (mean ages 61 vs 67) (p = 0.024). Squamous cell carcinoma made up 71% of tumors. History of other malignancy was present in 24% patients. Median follow-up time was 60 months (range 1–240). Five-year PFS in stage I, II, III and IV was 58.7%, 59.4%, 67.3% and 31.8%, respectively (p = 0.039). Five-year DSS was 84.3%, 73.7%, 78.7% and 26.5% respectively (p < 0.001). Advanced stage, tumor size >4 cm, entire vaginal involvement, and lymph node (LN) metastasis were poor prognosticators in univariate analysis. Primary surgery in stage I/II patients had similar survival outcomes as compared to primary radiation, but post-operative RT rate was 55%. Brachytherapy alone was associated with a high local recurrence (80%) in stage I/II patients. The addition of brachytherapy had improved 5-year PFS and DSS than EBRT alone in patients with stage III/IVA. (p < 0.001).
Surgery or radiation is effective treatment for vaginal cancer stage I and II. The addition of brachytherapy to external pelvic radiation increases survival in stages III-IV.
•Brachytherapy alone has a high local failure rate in stage I/II vaginal cancer.•Patients with stage I/II disease with primary surgery had a high post-operative radiation rate of 55%.•The addition of brachytherapy to external beam radiation improves survival in Stage III/IVA vaginal cancer.•Vaginal endometrioid adenocarcinoma is associated with deep infiltrating endometriosis.•Pelvic surveillance is important since 27% patients were diagnosed during routine exam without symptoms.
Almost one third of cancer patients in the United States will develop brain metastases on an annual basis. Surgical resection is indicated in the setting of brain metastases for reasons, such as ...maximizing local control in select patients, decompression of mass effect, and/or tissue diagnosis. The current standard of care following resection of a brain metastasis has shifted from whole brain radiation therapy to post-operative stereotactic radiosurgery (SRS). However, there is a significant rate of local recurrence within one year of postoperative SRS. Emerging retrospective and prospective data suggest pre-operative SRS is a safe and potentially effective treatment paradigm for surgical brain metastases. This trial intends to determine, for patients with an indication for resection of a brain metastasis, whether there is an increase in the time to a composite endpoint of adverse outcomes; including the first occurrence of either: local recurrence, leptomeningeal disease, or symptomatic radiation brain necrosis - in patients who receive pre-operative SRS as compared to patients who receive post-operative SRS.
This randomized phase III clinical trial compares pre-operative with post-operative SRS for brain metastases. A dynamic random allocation procedure will allocate an equal number of patients to each arm: pre-operative SRS followed by surgery or surgery followed by post-operative SRS.
If pre-operative SRS improves outcomes relative to post-operative SRS, this will establish pre-operative SRS as superior. If post-operative SRS proves superior to pre-operative SRS, it will remain a standard of care and halt the increasing utilization of pre-operative SRS. If there is no difference in pre- versus post-operative SRS, then pre-operative SRS may still be preferred, given patient convenience and the potential for a condensed timeline.
Emerging retrospective and prospective data have demonstrated some benefits of pre-op SRS vs. post-op SRS. This study will show whether there is an increase in the time to the composite endpoint. Additionally, the study will compare overall survival; patient-reported outcomes; morbidity; completion of planned therapies; time to systemic therapy; time to regional progression; time to CNS progression; time to subsequent treatment; rate of radiation necrosis; rate of local recurrence; and rate of leptomeningeal disease.
NCT03750227 (Registration date: 21/11/2018).
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background
Efficient and accurate delineation of organs at risk (OARs) is a critical procedure for treatment planning and dose evaluation. Deep learning‐based auto‐segmentation of OARs has shown ...promising results and is increasingly being used in radiation therapy. However, existing deep learning‐based auto‐segmentation approaches face two challenges in clinical practice: generalizability and human‐AI interaction. A generalizable and promptable auto‐segmentation model, which segments OARs of multiple disease sites simultaneously and supports on‐the‐fly human‐AI interaction, can significantly enhance the efficiency of radiation therapy treatment planning.
Purpose
Meta's segment anything model (SAM) was proposed as a generalizable and promptable model for next‐generation natural image segmentation. We further evaluated the performance of SAM in radiotherapy segmentation.
Methods
Computed tomography (CT) images of clinical cases from four disease sites at our institute were collected: prostate, lung, gastrointestinal, and head & neck. For each case, we selected the OARs important in radiotherapy treatment planning. We then compared both the Dice coefficients and Jaccard indices derived from three distinct methods: manual delineation (ground truth), automatic segmentation using SAM's ’segment anything’ mode, and automatic segmentation using SAM's ‘box prompt’ mode that implements manual interaction via live prompts during segmentation.
Results
Our results indicate that SAM's segment anything mode can achieve clinically acceptable segmentation results in most OARs with Dice scores higher than 0.7. SAM's box prompt mode further improves Dice scores by 0.1∼0.5. Similar results were observed for Jaccard indices. The results show that SAM performs better for prostate and lung, but worse for gastrointestinal and head & neck. When considering the size of organs and the distinctiveness of their boundaries, SAM shows better performance for large organs with distinct boundaries, such as lung and liver, and worse for smaller organs with less distinct boundaries, like parotid and cochlea.
Conclusions
Our results demonstrate SAM's robust generalizability with consistent accuracy in automatic segmentation for radiotherapy. Furthermore, the advanced box‐prompt method enables the users to augment auto‐segmentation interactively and dynamically, leading to patient‐specific auto‐segmentation in radiation therapy. SAM's generalizability across different disease sites and different modalities makes it feasible to develop a generic auto‐segmentation model in radiotherapy.
Background
Accurate and efficient dose calculation is essential for on‐line adaptive planning in proton therapy. Deep learning (DL) has shown promising dose prediction results in photon therapy. ...However, there is a scarcity of DL‐based dose prediction methods specifically designed for proton therapy. Successful dose prediction method for proton therapy should account for more challenging dose prediction problems in pencil beam scanning proton therapy (PBSPT) due to its sensitivity to heterogeneities.
Purpose
To develop a DL‐based PBSPT dose prediction workflow with high accuracy and balanced complexity to support on‐line adaptive proton therapy clinical decision and subsequent replanning.
Methods
PBSPT plans of 103 prostate cancer patients (93 for training and the other 10 for independent testing) and 83 lung cancer patients (73 for training and the other 10 for independent testing) previously treated at our institution were included in the study, each with computed tomography scans (CTs), structure sets, and plan doses calculated by the in‐house developed Monte‐Carlo dose engine (considered as the ground truth in the model training and testing). For the ablation study, we designed three experiments corresponding to the following three methods: (1) Experiment 1, the conventional region of interest (ROI) (composed of targets and organs‐at‐risk OARs) method. (2) Experiment 2, the beam mask (generated by raytracing of proton beams) method to improve proton dose prediction. (3) Experiment 3, the sliding window method for the model to focus on local details to further improve proton dose prediction. A fully connected 3D‐Unet was adopted as the backbone. Dose volume histogram (DVH) indices, 3D Gamma passing rates with a criterion of 3%/3 mm/10%, and dice coefficients for the structures enclosed by the iso‐dose lines between the predicted and the ground truth doses were used as the evaluation metrics. The calculation time for each proton dose prediction was recorded to evaluate the method's efficiency.
Results
Compared to the conventional ROI method, the beam mask method improved the agreement of DVH indices for both targets and OARs and the sliding window method further improved the agreement of the DVH indices (for lung cancer, CTV D98 absolute deviation: 0.74 ± 0.18 vs. 0.57 ± 0.21 vs. 0.54 ± 0.15 GyRBE, ROI vs. beam mask vs. sliding window methods, respectively). For the 3D Gamma passing rates in the target, OARs, and BODY (outside target and OARs), the beam mask method improved the passing rates in these regions and the sliding window method further improved them (for prostate cancer, targets: 96.93% ± 0.53% vs. 98.88% ± 0.49% vs. 99.97% ± 0.07%, BODY: 86.88% ± 0.74% vs. 93.21% ± 0.56% vs. 95.17% ± 0.59%). A similar trend was also observed for the dice coefficients. This trend was especially remarkable for relatively low prescription isodose lines (for lung cancer, 10% isodose line dice: 0.871 ± 0.027 vs. 0.911 ± 0.023 vs. 0.927 ± 0.017). The dose predictions for all the testing cases were completed within 0.25 s.
Conclusions
An accurate and efficient deep learning‐augmented proton dose prediction framework has been developed for PBSPT, which can predict accurate dose distributions not only inside but also outside ROI efficiently. The framework can potentially further reduce the initial planning and adaptive replanning workload in PBSPT.
. To enhance an in-house graphic-processing-unit accelerated virtual particle (VP)-based Monte Carlo (MC) proton dose engine (VPMC) to model aperture blocks in both dose calculation and optimization ...for pencil beam scanning proton therapy (PBSPT)-based stereotactic radiosurgery (SRS).
. A module to simulate VPs passing through patient-specific aperture blocks was developed and integrated in VPMC based on simulation results of realistic particles (primary protons and their secondaries). To validate the aperture block module, VPMC was first validated by an opensource MC code, MCsquare, in eight water phantom simulations with 3 cm thick brass apertures: four were with aperture openings of 1, 2, 3, and 4 cm without a range shifter, while the other four were with same aperture opening configurations with a range shifter of 45 mm water equivalent thickness. Then, VPMC was benchmarked with MCsquare and RayStation MC for 10 patients with small targets (average volume 8.4 c.c. with range of 0.4-43.3 c.c.). Finally, 3 typical patients were selected for robust optimization with aperture blocks using VPMC.
. In the water phantoms, 3D gamma passing rate (2%/2 mm/10%) between VPMC and MCsquare was 99.71 ± 0.23%. In the patient geometries, 3D gamma passing rates (3%/2 mm/10%) between VPMC/MCsquare and RayStation MC were 97.79 ± 2.21%/97.78 ± 1.97%, respectively. Meanwhile, the calculation time was drastically decreased from 112.45 ± 114.08 s (MCsquare) to 8.20 ± 6.42 s (VPMC) with the same statistical uncertainties of ~0.5%. The robustly optimized plans met all the dose-volume-constraints (DVCs) for the targets and OARs per our institutional protocols. The mean calculation time for 13 influence matrices in robust optimization by VPMC was 41.6 s and the subsequent on-the-fly 'trial-and-error' optimization procedure took only 71.4 s on average for the selected three patients.
. VPMC has been successfully enhanced to model aperture blocks in dose calculation and optimization for the PBSPT-based SRS.
Purpose/objectives
This retrospective study demonstrates the long-term outcomes of treating prostate cancer using intensity modulated (IMRT) with incorporation of MRI-directed boost.
...Materials/methods
From February 2009 to February 2013, 78 men received image-guided IMRT delivering 77.4 Gy in 44 fractions with simultaneously integrated boost to 81–83 Gy to an MRI-identified lesion. Patients with intermediate-risk or high-risk prostate cancer were recommended to receive 6 and 24–36 months of adjuvant hormonal therapy, respectively.
Results
Median follow-up was 113 months (11–147). There were 18 low-risk, 43 intermediate-risk, and 17 high-risk patients per NCCN risk stratification included in this study. Adjuvant hormonal therapy was utilized in 32 patients (41%). The 10-year biochemical control rate for all patients was 77%. The 10-year biochemical control rates for low-risk, intermediate-risk, and high-risk diseases were 94%, 81%, and 88%, respectively (p = 0.35). The 10-year rates of local control, distant control, and survival were 99%, 88%, and 66%, respectively. Of 25 patients who died, only four (5%) died of prostate cancer. On univariate analysis, T-category and pretreatment PSA level were associated with distant failure rate (p = 0.02). There was no grade =3 genitourinary and gastrointestinal toxicities that persisted at the last follow-up.
Conclusions
This study demonstrated the long-term efficacy of using MRI to define an intra-prostatic lesion for SIB to 81–83Gy while treating the entire prostate gland to 77.4 Gy with IMRT. Our study confirms that modern MRI can be used to locally intensify dose to prostate tumors providing high long-term disease control while maintaining favorable long-term toxicity.
Abstract Background Radium-223 improves survival in patients with metastatic castration-resistant prostate cancer (mCRPC). This retrospective analysis was performed to better understand its efficacy ...in routine clinical practice and identify factors associated with survival. Materials and Methods Sixty-four patients with mCRPC who received radium-223 between 2013 and 2015 were the basis of this retrospective study. Clinical outcomes and patient characteristics were obtained. Potential prognostic factors for survival were evaluated by univariate analysis using the log-rank test and multivariate analysis using the Cox proportional hazard method. Results The median survival was 12.9 months. Twenty-one patients (33%) developed a skeletal event and the median time to first skeletal event was 4.4 months. In univariate analysis, factors significantly associated with survival included: no prior chemotherapy, < 5 bone metastases, baseline PSA < 36ng/ml, baseline alkaline phosphatase (ALP) <115U/L, baseline hemoglobin >12g/dl, ALP response after radium-223 treatment, PSA decrease during Ra-223 treatment, and absence of >25% PSA increase during Ra-223 treatment. In multivariate analysis, 4 factors remained significant: no prior chemotherapy, < 5 bone metastases, baseline ALP <115U/L, and ALP response after radium-223 treatment. Conclusion When radium-223 is administered in routine clinical practice, clinical outcomes can be more variable than those reported in the randomized study due to patient heterogeneity. Four factors were identified to be significantly associated with survival after radium-223 treatment. These pre-treatment factors may be used as stratification factors in future studies to investigate whether radium-223 would be more effective for patients with newly diagnosed metastatic disease that is sensitive to androgen deprivation therapy.
•This series is the largest multicenter evaluation on outcomes of protons for chordoma.•2- and 3-year rates of local control for the entire cohort were 97% and 94%.•Acute Grade 3 toxicity limited to ...8%, with no grade > 4 acute toxicities.•No grade ≥ 3 late toxicities despite delivery of high dose proton therapy.
We present efficacy and toxicity outcomes among patients with chordoma treated on the Proton Collaborative Group prospective registry.
Consecutive chordoma patients treated between 2010–2018 were evaluated. One hundred fifty patients were identified, 100 had adequate follow-up information. Locations included base of skull (61%), spine (23%), and sacrum (16%). Patients had a performance status of ECOG 0–1 (82%) and median age of 58 years. Eighty-five percent of patients underwent surgical resection. The median proton RT dose was 74 Gy (RBE) (range 21–86 Gy (RBE)) using passive scatter proton RT (PS-PBT) (13%), uniform scanning proton RT (US-PBT) (54%) and pencil beam scanning proton RT (PBS-PBT) (33%). Rates of local control (LC), progression-free survival (PFS), overall survival (OS) and acute and late toxicities were assessed.
2/3-year LC, PFS, and OS rates are 97%/94%, 89%/74%, and 89%/83%, respectively. LC did not differ based on surgical resection (p = 0.61), though this is likely limited by most patients having undergone a prior resection. Eight patients experienced acute grade 3 toxicities, most commonly pain (n = 3), radiation dermatitis (n = 2), fatigue (n = 1), insomnia (n = 1) and dizziness (n = 1). No grade ≥ 4 acute toxicities were reported. No grade ≥ 3 late toxicities were reported, and most common grade 2 toxicities were fatigue (n = 5), headache (n = 2), CNS necrosis (n = 1), and pain (n = 1).
In our series, PBT achieved excellent safety and efficacy outcomes with very low rates of treatment failure. CNS necrosis is exceedingly low (<1%) despite the high doses of PBT delivered. Further maturation of data and larger patient numbers are necessary to optimize therapy in chordoma.
Introduction
Glioblastomas (GBMs) are highly aggressive tumors. A common clinical challenge after standard of care treatment is differentiating tumor progression from treatment-related changes, also ...known as pseudoprogression (PsP). Usually, PsP resolves or stabilizes without further treatment or a course of steroids, whereas true progression (TP) requires more aggressive management. Differentiating PsP from TP will affect the patient's outcome. This study investigated using deep learning to distinguish PsP MRI features from progressive disease.
Method
We included GBM patients with a new or increasingly enhancing lesion within the original radiation field. We labeled those who subsequently were stable or improved on imaging and clinically as PsP and those with clinical and imaging deterioration as TP. A subset of subjects underwent a second resection. We labeled these subjects as PsP, or TP based on the histological diagnosis. We coregistered contrast-enhanced T1 MRIs with T2-weighted images for each patient and used them as input to a 3-D Densenet121 model and using five-fold cross-validation to predict TP vs PsP.
Result
We included 124 patients who met the criteria, and of those, 63 were PsP and 61 were TP. We trained a deep learning model that achieved 76.4% (range 70–84%, SD 5.122) mean accuracy over the 5 folds, 0.7560 (range 0.6553–0.8535, SD 0.069) mean AUROCC, 88.72% (SD 6.86) mean sensitivity, and 62.05% (SD 9.11) mean specificity.
Conclusion
We report the development of a deep learning model that distinguishes PsP from TP in GBM patients treated per the Stupp protocol. Further refinement and external validation are required prior to widespread adoption in clinical practice.
