scholarly journals Automated contouring and planning pipeline for hippocampal-avoidant whole-brain radiotherapy

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Christine H. Feng ◽  
Mariel Cornell ◽  
Kevin L. Moore ◽  
Roshan Karunamuni ◽  
Tyler M. Seibert
Keyword(s):  
Artificial Intelligence ◽  
Treatment Planning ◽  
Whole Brain Radiotherapy ◽  
Planning System ◽  
Whole Brain ◽  
Knowledge Based ◽  
Brain Radiotherapy ◽  
Manual Intervention ◽  
Dose Volume ◽  
Knowledge Based Planning

Abstract Background Whole-brain radiotherapy (WBRT) remains an important treatment for over 200,000 cancer patients in the United States annually. Hippocampal-avoidant WBRT (HA-WBRT) reduces neurocognitive toxicity compared to standard WBRT, but HA-WBRT contouring and planning are more complex and time-consuming than standard WBRT. We designed and evaluated a workflow using commercially available artificial intelligence tools for automated hippocampal segmentation and treatment planning to efficiently generate clinically acceptable HA-WBRT radiotherapy plans. Methods We retrospectively identified 100 consecutive adult patients treated for brain metastases outside the hippocampal region. Each patient’s T1 post-contrast brain MRI was processed using NeuroQuant, an FDA-approved software that provides segmentations of brain structures in less than 8 min. Automated hippocampal segmentations were reviewed for accuracy, then converted to files compatible with a commercial treatment planning system, where hippocampal avoidance regions and planning target volumes (PTV) were generated. Other organs-at-risk (OARs) were previously contoured per clinical routine. A RapidPlan knowledge-based planning routine was applied for a prescription of 30 Gy in 10 fractions using volumetric modulated arc therapy (VMAT) delivery. Plans were evaluated based on NRG CC001 dose-volume objectives (Brown et al. in J Clin Oncol, 2020). Results Of the 100 cases, 99 (99%) had acceptable automated hippocampi segmentations without manual intervention. Knowledge-based planning was applied to all cases; the median processing time was 9 min 59 s (range 6:53–13:31). All plans met per-protocol dose-volume objectives for PTV per the NRG CC001 protocol. For comparison, only 65.5% of plans on NRG CC001 met PTV goals per protocol, with 26.1% within acceptable variation. In this study, 43 plans (43%) met OAR constraints, and the remaining 57 (57%) were within acceptable variation, compared to 42.5% and 48.3% on NRG CC001, respectively. No plans in this study had unacceptable dose to OARs, compared to 0.8% of manually generated plans from NRG CC001. 8.4% of plans from NRG CC001 were not scored or unable to be evaluated. Conclusions An automated pipeline harnessing the efficiency of commercially available artificial intelligence tools can generate clinically acceptable VMAT HA-WBRT plans with minimal manual intervention. This process could improve clinical efficiency for a treatment established to improve patient outcomes over standard WBRT.

scholarly journals Automated Contouring and Planning for Hippocampal-Avoidant Whole-Brain Radiotherapy

2020 ◽  
Author(s):  
Christine H. Feng ◽  
Mariel Cornell ◽  
Kevin L. Moore ◽  
Roshan Karunamuni ◽  
Tyler M. Seibert
Keyword(s):  
Artificial Intelligence ◽  
Treatment Planning ◽  
Planning System ◽  
Treatment Planning System ◽  
Post Contrast ◽  
Whole Brain ◽  
Knowledge Based ◽  
Manual Intervention ◽  
Dose Volume ◽  
Knowledge Based Planning

AbstractPurposeDesign and evaluate a workflow using commercially available artificial intelligence tools for automated hippocampal segmentation and treatment planning to efficiently generate clinically acceptable hippocampal-avoidant whole brain (HA-WBRT) radiotherapy plans.Methods and MaterialsWe retrospectively identified 100 consecutive adult patients treated for brain metastases outside the hippocampal region. Each patient’s T1 post-contrast brain MRI was processed using FDA-approved software that provides segmentations of brain structures in 5-7 minutes. Automated hippocampal segmentations were reviewed for accuracy and edited manually if necessary, then converted to files compatible with a commercial treatment planning system, where hippocampal avoidance regions and planning target volumes (PTV) were generated. Other organs-at-risk (OARs) were previously contoured per clinical routine. A RapidPlan knowledge-based planning routine was applied for a prescription of 30 Gy in 10 fractions using volumetric modulated arc therapy (VMAT) delivery. Plans were evaluated based on NRG CC001 dose-volume objectives.ResultsOf the 100 cases, 99 (99%) had acceptable automated hippocampi segmentations without manual intervention. Knowledge-based planning was applied to all cases; the median processing time was 9 minutes 59 seconds (range 6:53 – 13:31). All plans met per-protocol dose-volume objectives for PTV per the NRG CC001 protocol. For comparison, only 66.0% of plans on NRG CC001 met PTV goals per protocol, with 26.3% within acceptable variation. In this study, 43 plans (43%) met OAR constraints, and the remaining 57 (57%) were within acceptable variation, compared to 42.9% and 48.6% on NRG CC001, respectively. No plans in this study had unacceptable dose to OARs, compared to 0.8% of manually generated plans from NRG CC001.ConclusionAn automated pipeline harnessing the efficiency of commercially available artificial intelligence tools can generate clinically acceptable VMAT HA-WBRT plans with minimal manual intervention. This process could improve clinical efficiency for a treatment established to improve patient outcomes over standard WBRT.

Improvement of dose homogeneity with irregular surface compensator in whole brain radiotherapy

2016 ◽  
Vol 15 (3) ◽  
pp. 269-275
Author(s):  
H. Fujita ◽  
N. Kuwahata ◽  
H. Hattori ◽  
H. Kinoshita ◽  
H. Fukuda
Keyword(s):  
Maximum Dose ◽  
Treatment Plan ◽  
Whole Brain Radiotherapy ◽  
Planning System ◽  
Treatment Planning System ◽  
Irregular Surface ◽  
Medical Systems ◽  
Whole Brain ◽  
Brain Radiotherapy ◽  
Dose Homogeneity

AbstractPurposeThe aim of this study was to evaluate the dosimetric aspects of whole brain radiotherapy (WBRT) using an irregular surface compensator (ISC) in contrast to conventional radiotherapy techniques.MethodsTreatment plans were devised for 20 patients. The Eclipse treatment planning system (Varian Medical Systems) was used for dose calculation. For the ISC, a fluence editor application was used to extend the range of optimal fluence. The treatment plan with the ISC was compared with the conventional technique in terms of doses in the planning target volume (PTV), dose homogeneity index (DHI), three-dimensional (3D) maximum dose, eye and lens doses and monitor unit (MU) counts required for treatment.ResultsCompared with conventional WBRT, the ISC significantly reduced the DHI, 3D maximum dose and volumes receiving 105% of the prescription dose, in addition to reducing both eye and lens doses (p<0·05 for all comparisons). In contrast, MU counts were higher for the ISC technique than for conventional WBRT (828 versus 328, p<0·01).ConclusionThe ISC technique for WBRT considerably improved the dose homogeneity in the PTV. As patients who receive WBRT have improved survival, the long-term side effects of radiotherapy are highly important.

Knowledge-based planning for oesophageal cancers using a model trained with plans from a different treatment planning system

2019 ◽  
Vol 59 (3) ◽  
pp. 274-283 ◽  
Author(s):  
Yoshihiro Ueda ◽  
Masayoshi Miyazaki ◽  
Iori Sumida ◽  
Shingo Ohira ◽  
Mikoto Tamura ◽  
...  
Keyword(s):  
Treatment Planning ◽  
Planning System ◽  
Treatment Planning System ◽  
Knowledge Based ◽  
Knowledge Based Planning

scholarly journals Knowledge-based Planning using Pseudo-structures for Volumetric Modulated arc Therapy (VMAT) of Postoperative Uterine Cervical Cancer: A Multi-Institutional Study

2020 ◽  
Author(s):  
Tatsuya Kamima ◽  
Yoshihiro Ueda ◽  
Jun-ichi Fukunaga ◽  
Mikoto Tamura ◽  
Yumiko Shimizu ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Treatment Planning ◽  
Planning Process ◽  
Volumetric Modulated Arc Therapy ◽  
Uterine Cervical Cancer ◽  
Planning System ◽  
Treatment Planning System ◽  
Knowledge Based ◽  
Arc Therapy ◽  
Knowledge Based Planning

Abstract Background: The aim of this study was to investigate the performance of the RapidPlan knowledge-based treatment planning system using models including registered pseudo-structures, and to determine how many structures are required for automatic optimization of volumetric modulated arc therapy (VMAT) for postoperative uterine cervical cancer. Methods: Pseudo-structures were retrospectively contoured for patients who had completed treatment at one of five institutions. For 22 patients, RPs were generated with a single optimization for models with two (RP_2), four (RP_4), or five (RP_5) registered structures, and the dosimetric parameters of these models were compared with a clinical plan with several optimizations. The total times for pseudo-structure creation and optimization were also measured.Results: Most dosimetric parameters showed no major differences between each RP. In particular, the rectum Dmax, V50Gy, and V40Gy with RP_2, RP_4, and RP_5 were not significantly different, and were lower than those of the clinical plan. In addition, the average proportions of plans achieving acceptable criteria for all dosimetric parameters were 98%, 99%, 98%, and 98% for the clinical plan, RP_2, RP_4, and RP_5, respectively. The average times for the creation and optimization of pseudo-structures were 105, 17, 21, and 29 minutes, for the clinical plan, RP_2, RP_4, and RP_5, respectively. Conclusions: The RapidPlan model with two registered pseudo-structures could generate clinically acceptable plans while saving time. This modeling approach using pseudo-structures could possibility be used for the VMAT planning process.

scholarly journals Biological implications of whole-brain radiotherapy versus stereotactic radiosurgery of multiple brain metastases

2014 ◽  
Vol 121 (Suppl_2) ◽  
pp. 60-68 ◽  
Author(s):  
Jinyu Xue ◽  
Gregory J. Kubicek ◽  
Jimm Grimm ◽  
Tamara LaCouture ◽  
Yan Chen ◽  
...  
Keyword(s):  
Brain Metastases ◽  
Stereotactic Radiosurgery ◽  
Whole Brain Radiotherapy ◽  
Biological Information ◽  
Normal Brain ◽  
Whole Brain ◽  
Multiple Brain Metastases ◽  
Brain Radiotherapy ◽  
Dose Volume ◽  
The Mean

ObjectThe efficacy and safety of treatment with whole-brain radiotherapy (WBRT) or with stereotactic radiosurgery (SRS) for multiple brain metastases (> 10) are topics of ongoing debate. This study presents detailed dosimetric and biological information to investigate the possible clinical outcomes of these 2 modalities.MethodsFive patients with multiple brain metastases (n = 11–23) underwent SRS. Whole-brain radiotherapy plans were retrospectively designed with the same MR image set and the same structure set for each patient, using the standard opposing lateral beams and fractionation (3 Gy × 10).Physical radiation doses and biologically effective doses (BEDs) in WBRT and SRS were calculated for each lesion target and for the normal brain tissues for comparison of the 2 modalities in the context of clinical efficacy and published toxicities.ResultsThe BEDs targeted to the tumor were higher in SRS than in WBRT by factors ranging from 2.4- to 3.0- fold for the mean dose and from 3.2- to 5.3-fold for the maximum dose. In the 5 patients, mean BEDs in SRS (calculated as percentages of BEDs in WBRT) were 1.3%–34.3% for normal brain tissue, 0.7%–31.6% for the brainstem, 0.5%–5.7% for the chiasm, 0.2%–5.7% for optic nerves, and 0.6%–18.1% for the hippocampus.ConclusionsThe dose-volume metrics presented in this study were essential to understanding the safety and efficacy of WBRT and SRS for multiple brain metastases. Whole-brain radiotherapy results in a higher incidence of radiation-related toxicities than SRS. Even in patients with > 10 brain metastases, the normal CNS tissues receive significantly lower doses in SRS. The mean normal brain dose in SRS correlated with the total volume of the lesions rather than with the number of lesions treated.

scholarly journals A hybrid automated treatment planning solution for esophageal cancer

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Chifang Ling ◽  
Xu Han ◽  
Peng Zhai ◽  
Hao Xu ◽  
Jiayan Chen ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Treatment Planning ◽  
Treatment Plan ◽  
Estimation Model ◽  
Knowledge Based ◽  
Plan Optimization ◽  
Dose Volume ◽  
Knowledge Based Planning ◽  
Planning Methods ◽  
Planning Strategies

Abstract Objective This study aims to investigate a hybrid automated treatment planning (HAP) solution that combines knowledge-based planning (KBP) and script-based planning for esophageal cancer. Methods In order to fully investigate the advantages of HAP, three planning strategies were implemented in the present study: HAP, KBP, and full manual planning. Each method was applied to 20 patients. For HAP and KBP, the objective functions for plan optimization were generated from a dose–volume histogram (DVH) estimation model, which was based on 70 esophageal patients. Script-based automated planning was used for HAP, while the regular IMRT inverse planning method was used for KBP. For full manual planning, clinical standards were applied to create the plans. Paired t-tests were performed to compare the differences in dose-volume indices among the three planning methods. Results Among the three planning strategies, HAP exhibited the best performance in all dose-volume indices, except for PTV dose homogeneity and lung V5. PTV conformity and spinal cord sparing were significantly improved in HAP (P < 0.001). Compared to KBP, HAP improved all indices, except for lung V5. Furthermore, the OAR sparing and target coverage between HAP and full manual planning were similar. Moreover, HAP had the shortest average planning time (57 min), when compared to KBP (63 min) and full manual planning (118 min). Conclusion HAP is an effective planning strategy for obtaining a high quality treatment plan for esophageal cancer.

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