Employing the therapeutic operating characteristic (TOC) graph for individualised dose prescription

Hoffmann, Aswin L.; Huizenga, H.; Kaanders, J.H.A.M.

doi:10.1186/1748-717x-8-55

Cited by 8 publications

(10 citation statements)

References 22 publications

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“…Dose scaling is reasonable at least for evaluating the effects of motion. Moreover, in emerging research of personalized‐dose prescription, there is a renewed interest in changing the overall dose after a treatment plan has been generated . If such a treatment regimen is used, a TOC curve, with the overall dose as the hidden variable, provides a full picture of the trade‐offs between the risks and the benefits, independent of the dose level.…”

Section: Discussionmentioning

confidence: 99%

“…Since then, TOC has been applied to optimize the radiation dose in several disease sites . More recently, the area under the TOC curve (AUTOC) has been employed as a figure of merit to evaluate segmentation algorithms, to assess image quality in radiation therapy, to prescribe radiation dose on a per‐patient basis, and to study treatment efficacy in the field of precision chemotherapy . More specifically, the theory of applying TOC to the study of tumor motion was laid out by Barrett et al …”

Section: Introductionmentioning

confidence: 99%

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Objective assessment of the effects of tumor motion in radiation therapy

et al. 2019

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Purpose: Internal organ motion reduces the accuracy and efficacy of radiation therapy. However, there is a lack of tools to objectively (based on a medical or scientific task) assess the dosimetric consequences of motion, especially on an individual basis. We propose to use therapy operating characteristic (TOC) analysis to quantify the effects of motion on treatment efficacy for individual patients. We demonstrate the application of this tool with pancreatic stereotactic body radiation therapy (SBRT) clinical data and explore the origin of motion sensitivity. Methods: The technique is described as follows. (a) Use tumor-motion data measured from patients to calculate the motion-convolved dose of the gross tumor volume (GTV) and the organs at risk (OARs). (b) Calculate tumor control probability (TCP) and normal tissue complication probability (NTCP) from the motion-convolved dose-volume histograms. (c) Construct TOC curves from TCP and NTCP models. (d) Calculate the area under the TOC curve (AUTOC) and use it as a figure of merit for treatment efficacy. We used tumor motion data measured from patients to calculate the relation between AUTOC and motion magnitude for 25 pancreatic SBRT treatment plans. Furthermore, to explore the driving factor of motion sensitivity of a given plan, we compared the dose distribution of motion-sensitive plans and motion-robust plans and studied the dependence of motion sensitivity to motion directions. Results: Our technique is able to recognize treatment plans that are sensitive to motion. Under the presence of motion, the treatment efficacy of some plans changes from providing high tumor control and low risks of complications to providing no tumor control and high risks of side effects. Several treatment plans experience falloffs in AUTOC at a smaller magnitude of motion than other plans. In our dataset, a potential indicator of a motion-sensitive treatment plan is that the duodenum is in proximity to the tumor in the SI direction. Conclusions: The TOC framework can serve as a tool to quantify the effects of internal organ motion in radiation therapy. With pancreatic SBRT clinical data, we applied this tool to study the change in treatment efficacy induced by motion for individual treatment plans. This framework could potentially be used clinically to understand the effects of motion in an individual patient and to design a patient-specific motion management plan. This framework could also be used in research to evaluate different components of the treatment process, such as motion-management techniques, treatment-planning algorithms, and treatment margins.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Objective assessment of the effects of tumor motion in radiation therapy

et al. 2019

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“…Furthermore, the extensive research into this area in the latter half of the 20th century indicates that dose escalation of 50% or so above conventional doses may be sufficient to overcome hypoxic radio-resistance in fractionated regimens [81,82]. There is also more recent evidence that dose de-escalation may be possible, thereby encouraging a DPBN approach [83].…”

Section: Hypoxiamentioning

confidence: 98%

Functional Radiotherapy Targeting using Focused Dose Escalation

Alonzi

2015

Clinical Oncology

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“…As a major cancer treatment procedure, radiation therapy (RT) is carried out on over half of the total number of cancer patients (Jaffray DA 2015). Optimal RT treatments seek to optimize tumor control while reducing damage to the surrounding healthy organs-atrisk (OARs), and ultimately to improve cancer patient survival rate and quality of life (Hoffmann et al 2013, Deasy et al 2015, Njeh et al 2015.…”

Section: Introductionmentioning

confidence: 99%

Task-based image quality assessment in radiation therapy: initial characterization and demonstration with computer-simulation study

et al. 2019

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In the majority of current radiation therapy (RT) applications, image quality is still assessed subjectively or by utilizing physical measures. A novel theory that applies objective task-based image quality assessment in radiation therapy (IQA-in-RT) was recently proposed, in which the area under the therapeutic operating characteristic curve (AUTOC) was employed as the figure-ofmerit (FOM) for evaluating RT effectiveness. Although theoretically more appealing than conventional subjective or physical measures, a comprehensive implementation and evaluation of this novel task-based IQA-in-RT theory is required for its further application in improving clinical RT. In this work, a practical and modular IQA-in-RT framework is presented for implementing this theory for the assessment of imaging components on the basis of RT treatment outcomes. Computer-simulation studies are conducted to demonstrate the feasibility and utility of the proposed IQA-in-RT framework in optimizing x-ray computed tomography (CT) pre-treatment imaging, including the optimization of CT imaging dose and image reconstruction parameters. The potential advantages of optimizing imaging components in the RT workflow by use of the AUTOC as the FOM are also compared against those of other physical measures. The results demonstrate that optimization using the AUTOC leads to selecting different parameters from those indicated by physical measures, potentially improving RT performance. The sources of systemic randomness and bias that affect the determination of the AUTOC are also analyzed. The presented work provides a practical solution for the further investigation and analysis of the task-based IQAin-RT theory and advances its applications in improving RT clinical practice and cancer patient care.

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Employing the therapeutic operating characteristic (TOC) graph for individualised dose prescription

Cited by 8 publications

References 22 publications

Objective assessment of the effects of tumor motion in radiation therapy

Objective assessment of the effects of tumor motion in radiation therapy

Functional Radiotherapy Targeting using Focused Dose Escalation

Task-based image quality assessment in radiation therapy: initial characterization and demonstration with computer-simulation study

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