Defining and assessing an anisotropic delineation margin for modern radiotherapy

New target volume delineation and PTV strategies to further personalise radiotherapy

Target volume delineation uncertainty (DU) is arguably one of the largest geometric uncertainties in radiotherapy that are accounted for using planning target volume (PTV) margins. Geometrical uncertainties are typically derived from a limited sample of patients. Consequently, the resultant margins are not tailored to individual patients. Furthermore, standard PTVs cannot account for arbitrary anisotropic extensions of the target volume originating from DU. We address these limitations by developing a method to measure DU for each patient by a single clinician. This information is then used to produce PTVs that account for each patient's unique DU, including any required anisotropic component. We do so using a two-step uncertainty evaluation strategy that does not rely on multiple samples of data to capture the DU of a patient's gross tumour volume (GTV) or clinical target volume. For simplicity, we will just refer to the GTV in the following. First, the clinician delineates two contour sets; one which bounds all voxels believed to have a probability of belonging to the GTV of 1, while the second includes all voxels with a probability greater than 0. Next, one specifies a probability density function for the true GTV boundary position within the boundaries of the two contours. Finally, a patient-specific PTV, designed to account for all systematic errors, is created using this information along with measurements of the other systematic errors. Clinical examples indicate that our margin strategy can produce significantly smaller PTVs than the van Herk margin recipe. Our new radiotherapy target delineation concept allows DUs to be quantified by the clinician for each patient, leading to PTV margins that are tailored to each unique patient, thus paving the way to a greater personalisation of radiotherapy.

Defining and assessing an anisotropic delineation margin for modern radiotherapy

PURPOSE

Uncertainty in target volume delineation for modern radiotherapy impacts dosimetry and patient outcomes. Delineation uncertainty is generally overlooked in practice as a source of error, potentially since historically, other uncertainties have been the main focus. This work defined and assessed an anisotropic delineation margin in both polar and spherical coordinate systems in order to account for the spatially varying nature of this uncertainty using a whole breast radiotherapy cohort as a proof of concept.

METHODS

A cohort of 21 whole breast radiotherapy patient datasets with clinical target volumes delineated by eight independent observers was utilized. Patients were divided into categories based on target volume and laterality. An anisotropic delineation margin for each category was determined by multiplying the average standard deviation in observer contours in each category by a factor of two. Standard deviation was determined in both polar and spherical coordinates at angular increments. This anisotropic approach was compared to a conventional clinical approach, where the delineation margin was applied in the cardinal directions only. The assessment of the delineation margin was undertaken by comparing the encompassment of the observer volumes by the target volume with added margin. The extra, presumed healthy tissue included in the margin and the malignant tissue missed by the margin were determined.

RESULTS

The proposed delineation margin is effective at accounting for inter-observer variation, producing >95% coverage of all CTVs for polar, spherical, and Cartesian margins in 82%, 79%, and 92% of cases, respectively. Additionally, <1% malignant tissue was missed for 65%, 70%, and 91% of cases and <37% healthy tissue was included in 95%, 89%, and 97% of cases. A conventional delineation margin approach is most appropriate for small and gold standard target volumes. However, for large target volumes, an anisotropic margin is necessary, producing significantly greater coverage of CTVs, including significantly less presumed healthy tissue and missing significantly less malignant tissue.

CONCLUSIONS

All delineation margin methods that account for target volume and laterality proved to be adequate, with appropriate encompassment of interobserver variation and minimal inclusion of extra excess healthy tissue and exclusion of possible malignant tissue. The anisotropic approach was found to be superior to a conventional approach for target volumes >1400 cm³ only with significantly greater encompassment of interobserver variation, less missed malignant tissue and less included healthy tissue. This methodology has been validated for a whole breast radiotherapy cohort as a proof of concept, however could be applied to other anatomical sites.