Fully automated planning and delivery of hippocampal-sparing whole brain irradiation

Current dilemma and future directions over prophylactic cranial irradiation in SCLC: a systematic review in MRI and immunotherapy era

Small cell lung cancer (SCLC) is the most malignant pathological type of lung cancer with the highest mortality, and the incidence of brain metastasis (BM) is in high frequency. So far, prophylactic cranial irradiation (PCI) has been suggested as an effective treatment for preventing brain metastasis of SCLC. PCI has long been applied to limited-stage SCLC (LS-SCLC) patients who have achieved complete remission after radiotherapy and chemotherapy as a standard treatment. However, the neurocognitive decline is a major concern surrounding PCI. New therapeutic approaches targeting PCI-induced neurotoxicity, including hippocampal protection or memantine, have been increasingly incorporated into the therapeutic interventions of PCI. Helical tomotherapy, RapidArc, and Volumetric-modulated arc therapy (VMAT) with a head-tilting baseplate are recommended for hippocampal protection. Besides, in the MRI and immunotherapy era, the significance of PCI in SCLC patients is controversial. SCLC patients with PCI should be recruited in clinical trials since this is the only way to improve the existing standard of care. This review summarizes the current therapeutic strategy and dilemma over PCI for SCLC, providing a theoretical basis for clinical decision-making and suggestions for PCI practice in clinical.

Dosimetric comparison of hippocampal-sparing technologies in patients with low-grade glioma

Background

Radiotherapy (RT) plays an integral role in the management of low-grade gliomas (LGG). Late toxicity from RT can cause progressive neurocognitive dysfunction. Radiation-induced damage to the hippocampus (HCP) plays a considerable role in memory decline. Advancements in photon planning software have resulted in the development of multi-criteria optimization (MCO) and HyperArc technologies which may improve HCP sparing while maintaining planning target volume (PTV) target coverage.

Methods

Three planning methods for hippocampal sparing (HS) were compared, volumetric modulated arc therapy (VMAT) without HS (VMAT_noHS), VMAT with HS (VMAT_HS), MCO with HS (MCO_HS), and HyperArc with HS (HyperArc_HS).

Results

Twenty-five patients were identified. The contralateral HCP was spared in 16 patients and bilateral HCP in 9 patients with superiorly located tumors. All 3 HS planning techniques showed significant reductions in dose to the spared HCP in contralateral cases but only VMAT_HS and MCO_HS achieved this in bilateral cases (P < .008). Only MCO_HS was superior to VMAT_HS in lowering the dose to both contralateral HCP and bilateral HCP in all measured metrics (P < .008). PTV and OAR (organ at risk) dose constraints were achieved for all plans.

Conclusions

This retrospective dosimetric study demonstrated the feasibility of HS for low-grade glioma. All 3 HS planning techniques achieved significant dose reductions to the spared contralateral hippocampus, but only MCO_HS and VMAT_HS achieved this in bilateral cases. MCO was superior to other planning techniques for sparing both bilateral and contralateral hippocampi.

Dosimetric comparison of coplanar and noncoplanar volumetric modulated arc therapy for hippocampal-sparing whole-brain radiation therapy

Whole brain radiation therapy with hippocampal-sparing (HS-WBRT) is a novel treatment of brain metastases, which can relieve symptoms reduce recurrence in the central nervous system, and spare the hippocampus without compromising target coverage. This study aims to find out the superior combination of the treatment planning system and linear accelerator between Eclipse (version 15.6) with TrueBeam and uRT-TPOIS (vision R001.4) with uRT-linac 506c in HS-WBRT. The coplanar and noncoplanar volumetric modulated arc therapy (VMAT) for HS-WBRT plans were evaluated and compared on both combinations, respectively. Twenty patients for HS-WBRT were retrospectively selected at Peking Union Medical College Hospital (PUMCH) from 2021 to 2022. The coplanar and noncoplanar HS-WBRT treatment plans were designed by Eclipse and uRT-TPOIS referring to RTOG 0933 dose criteria, and their dosimetry parameters were compared. In addition, the plan complexity, monitor units, and beam-on time were recorded for Eclipse plans delivered on TrueBeam and uRT-TPOIS plans delivered on uRT-linac 506c. The results demonstrated that the dosimetric criteria of 4 types of HS-WBRT plans could meet the requirements of RTOG 0933. In terms of target coverage, dosimetric indexes of Eclipse plans and uRT-TPOIS plans were comparable, and the former is slightly better. As for metrics of organs-at-risk protection, coplanar and noncoplanar plans conducted by uRT-TPOIS were greatly superior to those by Eclipse. For coplanar and noncoplanar plans designed by the same treatment planning system, most of the dosimetric indexes had no significant difference. The monitor units of uRT-TPOIS plans was higher than that of Eclipse plans, but the modulation complexity of them were close, and uRT-TPOIS with uRT-linac 506c significantly reduced beam-on-time consumption by 9% on average for coplanar plans and 26% for noncoplanar plans compared to Eclipse with TrueBeam. This study firstly compared the coplanar and noncoplanar HS-WBRT treatment plans between Eclipse with TrueBeam and uRT-TPOIS with uRT-linac 506c in terms of dosimetry indexes, modulation complexity, and time consumption. It is shown that the radiation treatment solution of uRT-TPOIS with uRT-linac 506c is comparable with Eclipse with TrueBeam in terms of planning design, and significantly reduced the delivery time, which can be applied in clinical practice and promoted as a treatment format.

Improved planning efficiency in multiple brain lesion SRS VMAT cases using Eclipse scripting

Though dosimetry has a multitude of treatment modalities, software, and workflows to aid in the treatment planning process, treatment planners are still responsible for several tedious and monotonous tasks that could decrease their planning efficiency. The purpose of this study was to determine if scripting could improve treatment planning efficiency for multiple brain lesion stereotactic radiosurgery (SRS) volumetric arc therapy cases by reducing planning time commitment. A script was developed for multiple brain lesion SRS cases using Eclipse scripting application programming interface with the intention of improving treatment planning efficiency by creating optimization structures and importing prescription and suggested OS dose metrics to the optimizer. Nine treatment planners were each provided with 3 different multiple brain lesion, single-isocenter SRS cases. Each planner created 2 plans for each case. One of these 2 plans used the SRS script, and the other did not. There were 54 treatment plans developed, totaling 27 plan comparisons. Each of the 54 treatment plans were considered clinically acceptable based on the participating institution's plan quality guidelines. Statistical analyses of planning time commitment with and without the SRS script were performed using RStudio. The mean and median planning times with and without the SRS script were compared using a paired T-test and Wilcoxon Signed Rank test, respectively, and effect size was evaluated using Cohen's classification. Using the SRS script resulted in statistically significant reduction in total contouring time (11.3 vs 2.8 minutes, p < 0.001), optimizer preparation time (7.7 vs 2.1 minutes, p < 0.001), and overall planning time (105.1 vs 77.9 minutes, p < 0.001). This study concluded that scripts developed using Eclipse scripting application programming interface offer an opportunity to improve treatment planning efficiency by reducing the planning time commitment for treatment planners.

Knowledge-based plan optimization for prostate SBRT delivered with CyberKnife according to RTOG0938 protocol

PURPOSE

To extend the knowledge-based (KB) automatic planning approach to CyberKnife in the case of Stereotactic Body Radiation Therapy (SBRT) for prostate cancer.

METHODS

Seventy-two clinical plans of patients treated according to the RTOG0938 protocol (36.25 Gy/5fr) with CyberKnife were exported from the CyberKnife system to Eclipse to train a KB-model using the Rapid Plan tool. The KB approach provided dose-volume objectives for specific OARs only and not PTV. Bladder, rectum and femoral heads were considered in the model. The KB-model was successfully trained on 51 plans and then validated on 20 new patients. A KB-based template was tuned in the Precision system for both sequential optimization (SO) and VOLO optimization algorithms. Plans of the validation group were re-optimized (KB-TP) using both algorithms without any operator intervention and compared against the original plans (TP) in terms of OARs/PTV dose-volume parameters. Paired Wilcoxon signed-rank tests were performed to assess statistically significant differences (p < 0.05).

RESULTS

Regarding SO, automatic KB-TP plans were generally better than or equivalent to TP plans. PTVs V95% was slightly worse while OARs sparing for KB-TP was significantly improved. Regarding VOLO optimization, the PTVs coverage was significantly better for KB-TP while there was a limited worsening in the rectum. A significant improvement was observed in the bladder in the range of low-intermediate doses.

CONCLUSIONS

An extension of the KB optimization approach to the CyberKnife system has been successfully developed and validated in the case of SBRT prostate cancer.

Developing an AI-assisted planning pipeline for hippocampal avoidance whole brain radiotherapy

BACKGROUND AND PURPOSE

Hippocampal avoidance whole brain radiotherapy (HA-WBRT) is effective for controlling disease and preserving neuro-cognitive function for brain metastases. However, contouring and planning of HA-WBRT is complex and time-consuming. We designed and evaluated a pipeline using deep learning tools for a fully automated treatment planning workflow to generate HA-WBRT radiotherapy plans.

MATERIALS AND METHODS

We retrospectively collected 50 adult patients who received HA-WBRT. Using RTOG- 0933 clinical trial protocol guidelines, all organs-at-risk (OARs) and the clinical target volume (CTV) were contoured by experienced radiation oncologists. A deep-learning segmentation model was designed and trained. Next, we developed a volumetric-modulated arc therapy (VMAT) auto-planning algorithm for 30 Gy in 10 fractions. Automated segmentations were evaluated using the Dice similarity coefficient (DSC) and 95th-percentile Hausdorff distance (95 % HD). Auto-plans were evaluated by the percentage of PTV volume that receives 30 Gy (V_30Gy), conformity index (CI), and homogeneity index (HI) of planning target volume (PTV) and the minimum dose (D_100%) and maximum dose (D_max) for the hippocampus, D_max for the lens, eyes, optic nerve, brain stem, and chiasm.

RESULTS

We developed a deep-learning segmentation model and an auto-planning script. For the 10 cases in the independent test set, the overall average DSC and 95 % HD of contours were greater than 0.8 and less than 7 mm, respectively. All auto-plans met the RTOG- 0933 criteria. The HA-WBRT plan automatically created time was about 10 min.

CONCLUSIONS

An artificial intelligence (AI)-assisted pipeline using deep learning tools can rapidly and accurately generate clinically acceptable HA-WBRT plans with minimal manual intervention and increase efficiency of this treatment for brain metastases.

Plan Quality Comparison Between Hippocampus-Sparing Whole-Brain Radiotherapy Treated With Halcyon and Tomotherapy Intensity-Modulated Radiotherapy

Objective: Hippocampus-sparing whole-brain radiotherapy using Halcyon, an instrument dedicated to volumetric modulated arc therapy, has not been studied till date; hence, we aimed to examine whether it can meet the RTOG0933 criteria. Based on this, we compared Halcyon to Tomotherapy, which also uses an O-ring-type linear accelerator. Methods: This exploratory, experimental, and retrospective study used 5 sets of computed tomography images in the head area to investigate the planning target volume, hippocampal doses, and irradiation time. Calculations were performed from 1 to 4 arcs to determine the optimal number of arcs in the Halcyon plan, which were compared to those of Tomotherapy. Results: The Radiation Therapy Oncology Group 0933 criteria could not be satisfied in Halcyon with 1 arc. With 2 arcs, the condition D_max<16 Gy was not satisfied for 1 case in the hippocampus. Since there were no significant differences between 3 and 4 arcs, including the irradiation time, 3 arcs were considered the best. We compared Halcyon at 3 arcs with tomotherapy and found that tomotherapy was inferior to Halcyon at D_98%; however, it was superior to Halcyon in other dose parameters. In contrast, the irradiation time in Halcyon was overwhelmingly superior, with the irradiation time for Halcyon being 1/ninth the time for Tomotherapy. Conclusion: Halcyon was effective in handling hippocampus-sparing whole-brain radiotherapy. We believe that 3-arc radiation is best suited for this procedure. Although Halcyon was inferior to Tomotherapy in terms of dose distribution excluding D_98%, it was overwhelmingly superior in terms of irradiation time.