Coverage‐based treatment planning to accommodate delineation uncertainties in prostate cancer treatment

Xu, Huijun; Gordon, J; Siebers, Jeffrey V.

doi:10.1118/1.4928490

Cited by 8 publications

(20 citation statements)

References 39 publications

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“…For a comparison, the obtained CTV to PTV margins were compared to the results of previous studies. [18][19][20] The overall uncertainties of the displacements determination are less than 2% and they are in respect to limits recommended by IAEA. 11 Figure 1.…”

Section: Ctv To Ptv Margin Determinationmentioning

confidence: 99%

RETRACTED – Determination of geometrical margins in external beam radiotherapy for prostate cancer

et al. 2018

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IntroductionThe focus of this study is to find the optimal clinical tumour volume (CTV) to planning tumour volume (PTV) margins for precise radiotherapy treatment of prostate cancer. The geometrical shape of the target volume posses challenges in accurately identifying the CTV to PTV margins, especially when the organ affected by cancer demonstrates anatomical variations and the surrounding organs have high radio-sensitivity, in comparison to the organ of origin of the cancer.Materials and methodsThe geometrical margins of CTV to PTV are investigated using portal imaging, in three directions. This study is carried out on 20 patients treated by the external photon beam radiotherapy of prostate cancer using standard accelerator without stereotaxic and without prostate markers.Results and discussionBased on previous studies and the findings of our work, we propose CTV to PTV margin of 5·84 mm in the lateral direction, of 5·1 mm in the cranio-spinal direction and of 7·3 mm in the antero-posterior direction for external photon beam radiotherapy of prostate cancer.ConclusionThe proposed CTV to PTV margins ensure high radiotherapy treatment precision of prostate cancer.

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Section: Ctv To Ptv Margin Determinationmentioning

confidence: 99%

RETRACTED – Determination of geometrical margins in external beam radiotherapy for prostate cancer

et al. 2018

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“…To account for the patient‐/contour‐specific plan and resulting dose distribution, we evaluate CP on a per‐patient/contour set basis. While our CP estimates account for rigid body motions, our method can be extended to include the effects of organ deformations, delineation uncertainties, and other inherent uncertainties. Inclusion of further uncertainties will likely reduce the CP deviations between the planning/evaluation scenarios.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, manual contours have interobserver delineation variability (due to different perception of observers), and intraobserver delineation variability (rooted in different interpretations/perception of the same observer in different trials). Observer variability is one of the dominant geometric uncertainties in radiation therapy, nonetheless, manual contours are considered the gold standard. While similarity metrics between manual physician‐contoured ROIs and autocontoured ROIs are progressively improving, the similarity metric threshold or other contour adequacy measure required to safely employ autocontouring in radiation therapy procedures is unclear.…”

Section: Introductionmentioning

confidence: 99%

Clinical adequacy assessment of autocontours for prostate IMRT with meaningful endpoints

et al. 2017

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Purpose: To determine if radiation treatment plans created based on autosegmented (AS) regionsof-interest (ROI)s are clinically equivalent to plans created based on manually segmented ROIs, where equivalence is evaluated using probabilistic dosimetric metrics and probabilistic biological endpoints for prostate IMRT. Method and materials: Manually drawn contours and autosegmented ROIs were created for 167 CT image sets acquired from 19 prostate patients. Autosegmentation was performed utilizing Pinnacle's Smart Probabilistic Image Contouring Engine. For each CT set, 78 Gy/39 fraction 7-beam IMRT treatment plans with 1 cm CTV-to-PTV margins were created for each of the three contour scenarios; P MD using manually delineated (MD) ROIs, P AS using autosegmented ROIs, and P AM using autosegmented organ-at-risks (OAR)s and the manually drawn target. For each plan, 1000 virtual treatment simulations with different systematic errors for each simulation and a different random error for each fraction were performed. The statistical probability of achieving dose-volume metrics (coverage probability (CP)), expectation values for normal tissue complication probability (NTCP), and tumor control probability (TCP) metrics for all possible cross-evaluation pairs of ROI types and planning scenarios were reported. In evaluation scenarios, the root mean square loss (RMSL) and maximum absolute loss (MAL) of coverage probability of dose-volume objectives, E[TCP], and E [NTCP] were compared with respect to the base plan created and evaluated with manually drawn contours. Results: Femoral head dose objectives were satisfied in all situations, as well as the maximum dose objectives for all ROIs. Bladder metrics were within the clinical coverage tolerances except D 35Gy for the autosegmented plan evaluated with the manual contours. Dosimetric indices for CTV and rectum could be highly compromised when the definition of the ROIs switched from manually delineated to autosegmented. Seventy-two percent of CT image sets satisfied the worst-case CP thresholds for all dosimetric objectives in all scenarios, the percentage dropped to 50% if biological indices were taken into account. Among evaluation scenarios, (MD,P AM ) bore the highest resemblance to (MD,P MD ) where 99% and 88% of cases met all CP thresholds for bladder and rectum, respectively. Conclusions: When including daily setup variations in prostate IMRT, the dose-volume metric CP, and biological indices of ROIs were approximately equivalent for the plans created based on manually drawn targets and autosegmented OARs in 88% of cases. The accuracy of autosegmented prostates and rectums are impediment to attain statistically equivalent plans created based on manually drawn ROIs.

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“…DV can stem from multiple sources, including inter-observer variability (i.e. multiple delineators will not generate precisely the same structures) (Bhardwaj et al 2008, Caravatta et al 2014, Xu et al 2016, intra-observer variability (i.e. the same delineator will not generate precisely the same structures in two different sessions) (Fiorino et al 1998, Petric et al 2008, Xu et al 2016, and methodological variability (i.e.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the dosimetric impact of organ-at-risk delineation variability in head and neck radiation therapy in the context of patient setup uncertainty

Aliotta¹,

Nourzadeh²,

Siebers³

2019

Phys. Med. Biol.

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The purpose of this study was to quantify the potential dosimetric impact of delineation variability (DV) in head and neck radiation therapy (RT) when inherent patient setup variability (SV) is also considered.The impact of DV was assessed by generating plans with multiple structure sets, cross-evaluating them, including SV, across sets, and determining P PQM : the probability of achieving organ-specific plan quality metrics (PQM). DV was incorporated by: (1) using multiple organ at risk (OAR) structure sets delineated by independent manual observers; and (2) randomly perturbing manually generated OARs to generate alternatives with varying levels of uncertainty (low, medium, and high DV). For each structure set, independent VMAT plans were auto-generated to meet clinical PQMs. Each plan was cross-evaluated using OARs from multiple structure sets with simulated SV including per-fraction random (σ s ) and per-treatment-course systematic (Σ s ) setup errors. The dosimetric impact of DV was assessed by examining P PQM with and without SV/DV. Clinically significant differences were defined by those that exceeded differences caused by a +2% output variation.Without including SV, simulated DV at the medium level reduced P PQM by an average of 5.5% for all OARs with D max PQMs. This reduction decreased to 2.8% for SV = 2 mm and 2.4% for SV = 4 mm (the average P PQM reduction due to 2% output errors was 2.7%). For OARs with D mean PQMs, the average P PQM reduction was 0.9% for SV = 0 and ⩽0.1% for SV ⩾ 2 mm. The effect of DV was larger for OARs that directly abutted a target volume than for those that did not. These trends were also observed with real DV from multi-observer delineations.The dosimetric impact of DV appeared to decrease when random and systematic SV was considered. Sensitivity to DV was affected by OAR objective type (i.e. D mean versus D max objectives) as well as distance from the target volume.

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Coverage‐based treatment planning to accommodate delineation uncertainties in prostate cancer treatment

Abstract: When the delineation uncertainties need to be considered for prostate patients, CP techniques can produce more desirable plans than FM plans for most patients. The relative advantages between CPCOP and CPOM techniques are patient specific.

Cited by 8 publications

References 39 publications

RETRACTED – Determination of geometrical margins in external beam radiotherapy for prostate cancer

RETRACTED – Determination of geometrical margins in external beam radiotherapy for prostate cancer

Clinical adequacy assessment of autocontours for prostate IMRT with meaningful endpoints

Quantifying the dosimetric impact of organ-at-risk delineation variability in head and neck radiation therapy in the context of patient setup uncertainty

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