Knowledge-based treatment planning and its potential role in the transition between treatment planning systems

Masi, Kathryn; Archer, Paul; Jackson, Will; Sun, Yilun; Schipper, Matthew J.; Hamstra, Daniel A.; Matuszak, Martha M.

doi:10.1016/j.meddos.2017.10.001

Cited by 9 publications

(11 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This group of methods aims to predict the entire DVH curve for a new patient and then frequently uses the predicted DVHs to guide the plan optimization process …”

Section: Resultsmentioning

confidence: 99%

“…This group of methods learns from prior clinical plans to predict the quality of a new plan . Note that a number of quality assurance methods are based on DVH or dose‐volume parameter prediction models …”

Section: Resultsmentioning

confidence: 99%

“…For prostate cancer, we have found four KBP studies that reported statistically significant reduction in mean dose to rectum and bladder after cases were re‐planned using the KBP methods. The pooled mean of reduction is 2.6 and 2.0 Gy for rectum and bladder, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…79 To gain further understanding of the overall performance of KBP in prostate cancer planning, we have developed a visualization scheme to provide a summary view of nine KBP prostate studies that compared re-planned results with original clinically approved values. 20,25,27,34,35,56,57,60,63 As mentioned previously, the challenge of summarizing results across all studies lie in two aspects: (a) the results are based on different sample points of the DVH curve and measure changes along different directions (e.g., one study may use D35 while another use V65); (b) some of the studies report only the differences in DVH point metrics (e.g., D35 is reduced by 1.5) without providing the original clinically approved values. The first issue makes it difficult to quantitatively compare results from different studies even though many DVH point metrics assess performance in similar areas of the DVH curve.…”

Section: C Performance Of Kbpmentioning

confidence: 99%

See 3 more Smart Citations

Knowledge‐based planning for intensity‐modulated radiation therapy: A review of data‐driven approaches

2019

Medical Physics

169

150

View full text Add to dashboard Cite

Purpose Intensity‐Modulated Radiation Therapy ( IMRT ), including its variations (including IMRT , Volumetric Arc Therapy ( VMAT ), and Tomotherapy), is a widely used and critically important technology for cancer treatment. It is a knowledge‐intensive technology due not only to its own technical complexity, but also to the inherently conflicting nature of maximizing tumor control while minimizing normal organ damage. As IMRT experience and especially the carefully designed clinical plan data are accumulated during the past two decades, a new set of methods commonly termed knowledge‐based planning ( KBP ) have been developed that aim to improve the quality and efficiency of IMRT planning by learning from the database of past clinical plans. Some of this development has led to commercial products recently that allowed the investigation of KBP in numerous clinical applications. In this literature review, we will attempt to present a summary of published methods of knowledge‐based approaches in IMRT and recent clinical validation results. Methods In March 2018, a literature search was conducted in the NIH Medline database using the PubMed interface to identify publications that describe methods and validations related to KBP in IMRT including variations such as VMAT and Tomotherapy. The search criteria were designed to have a broad scope to capture relevant results with high sensitivity. The authors filtered down the search results according to a predefined selection criteria by reviewing the titles and abstracts first and then by reviewing the full text. A few papers were added to the list based on the references of the reviewed papers. The final set of papers was reviewed and summarized here. Results The initial search yielded a total of 740 articles. A careful review of the titles, abstracts, and eventually the full text and then adding relevant articles from reviewing the references resulted in a final list of 73 articles published between 2011 and early 2018. These articles described methods for developing knowledge models for predicting such parameters as dosimetric and dose‐volume points, voxel‐level doses, and objective function weights that improve or automate IMRT planning for various cancer sites, addressing different clinical and quality assurance needs, and using a variety of machine learning approaches. A number of articles reported carefully designed clinical studies that assessed the performance of KBP models in realistic clinical applications. Overwhelming majority of the studies demonstrated the benefits of KBP in achieving comparable and often improve...

show abstract

“…This group of methods aims to predict the entire DVH curve for a new patient and then frequently uses the predicted DVHs to guide the plan optimization process …”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: C Performance Of Kbpmentioning

confidence: 99%

See 2 more Smart Citations

Knowledge‐based planning for intensity‐modulated radiation therapy: A review of data‐driven approaches

2019

Medical Physics

169

150

View full text Add to dashboard Cite

show abstract

“…It is necessary to share information about the treatment plan with multiple planners before using the treatment planning method obtained in this study in a clinical setting. Furthermore, to minimize the degree of variability in the treatment plan when multiple planners are involved, the use of a knowledge‐based planning tool 20–22 and re‐creation of the treatment plan template based on the empirical results obtained from the re‐planning of this study should be considered.…”

Section: Discussionmentioning

confidence: 99%

Analysis of prostate intensity‐ and volumetric‐modulated arc radiation therapy planning quality with PlanIQ^TM

Sasaki

Nakaguuchi

Kamomae

et al. 2021

J Applied Clin Med Phys

View full text Add to dashboard Cite

Purpose The purpose of this study was to assess the quality of treatment planning using the PlanIQTM software and to investigate whether it is possible to improve the quality of treatment planning using the “Feasibility dose‐volume histogram (DVH)TM” implemented in the PlanIQTM software. Methods Using the PlanIQTM software, we retrospectively analyzed the learning curve regarding the quality of the treatment plans for 148 patients of prostate intensity‐modulated radiation therapy and volumetric‐modulated radiation therapy performed at our institution over the past eight years. We also sought to examine the possibility of improving treatment planning quality by re‐planning in 47 patients where the quality of the target dose and the dose limits for organs at risk (OARs) were inadequate. The re‐planning treatment plans referred to the Feasibility DVHTM implemented in the PlanIQTM software and modified the treatment planning system based on the target dose and OAR constraints. Results Analysis of the learning curve of the treatment plans quality using PlanIQTM software retrospectively showed a trend of improvement in the treatment plan quality from year to year. The improvement in the treatment plans quality was more influenced by dose reduction in the OARs than by target coverage. In all cases where re‐planning was performed, the improvement in the treatment plan's quality resulted in a better treatment plan than the one adopted for delivery to patients in the clinical plan. Conclusions The PlanIQTM provided insights into the quality of the treatment plans at our institution and identified problems and areas for improvement in the treatment plans, allowing for the development of appropriate treatment plans for specific patients.

show abstract

Knowledge‐based radiation treatment planning: A data‐driven method survey

Momin

Lei

et al. 2021

J Applied Clin Med Phys

View full text Add to dashboard Cite

show abstract

Knowledge-based treatment planning and its potential role in the transition between treatment planning systems

Cited by 9 publications

References 19 publications

Knowledge‐based planning for intensity‐modulated radiation therapy: A review of data‐driven approaches

Knowledge‐based planning for intensity‐modulated radiation therapy: A review of data‐driven approaches

Analysis of prostate intensity‐ and volumetric‐modulated arc radiation therapy planning quality with PlanIQ^TM

Knowledge‐based radiation treatment planning: A data‐driven method survey

Contact Info

Product

Resources

About

Knowledge-based treatment planning and its potential role in the transition between treatment planning systems

Cited by 9 publications

References 19 publications

Knowledge‐based planning for intensity‐modulated radiation therapy: A review of data‐driven approaches

Knowledge‐based planning for intensity‐modulated radiation therapy: A review of data‐driven approaches

Analysis of prostate intensity‐ and volumetric‐modulated arc radiation therapy planning quality with PlanIQTM

Knowledge‐based radiation treatment planning: A data‐driven method survey

Contact Info

Product

Resources

About

Analysis of prostate intensity‐ and volumetric‐modulated arc radiation therapy planning quality with PlanIQ^TM