Dose-distance metric that predicts late rectal bleeding in patients receiving radical prostate external-beam radiotherapy

Abstract

The relationship between rectal dose distribution and the incidence of late rectal complications following external-beam radiotherapy has been previously studied using dose-volume histograms or dose-surface histograms. However, they do not account for the spatial dose distribution. This study proposes a metric based on both surface dose and distance that can predict the incidence of rectal bleeding in prostate cancer patients treated with radical radiotherapy. One hundred and forty-four patients treated with radical radiotherapy for prostate cancer were prospectively followed to record the incidence of grade ≥2 rectal bleeding. Radiotherapy plans were used to evaluate a dose-distance metric that accounts for the dose and its spatial distribution on the rectal surface, characterized by a logistic weighting function with slope a and inflection point d₀. This was compared to the effective dose obtained from dose-surface histograms, characterized by the parameter n which describes sensitivity to hot spots. The log-rank test was used to determine statistically significant (p < 0.05) cut-off values for the dose-distance metric and effective dose that predict for the occurrence of rectal bleeding. For the dose-distance metric, only d₀ = 25 and 30 mm combined with a > 5 led to statistical significant cut-offs. For the effective dose metric, only values of n in the range 0.07-0.35 led to statistically significant cut-offs. The proposed dose-distance metric is a predictor of rectal bleeding in prostate cancer patients treated with radiotherapy. Both the dose-distance metric and the effective dose metric indicate that the incidence of grade ≥2 rectal bleeding is sensitive to localized damage to the rectal surface.

Investigating rectal toxicity associated dosimetric features with deformable accumulated rectal surface dose maps for cervical cancer radiotherapy

“…For instance, Buettner et al presented a late rectal toxicity method based on the parameterized representation of the 3D rectal dose [ 39 ]. Lee et al proposed a metric based on both surface dose and distance to predict incidence of the rectal bleeding in prostate cancer patients treated with radical radiotherapy [ 40 ]. Drean et al identified rectal subregions at risk of rectal bleeding by performing voxel-wise analysis on the rectal dose distribution [ 7 ].…”

Patterns in ano-rectal dose maps and the risk of late toxicity after prostate IMRT

“…Many investigators have studied the risk of rectal complications from radiotherapy in terms of dose-volume histogram (DVH) data [1]. However, a limitation of a DVH is that the spatial distribution of dose is disregarded; therefore, several studies have recently considered spatial features [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17] of the three-dimensional (3D) dose distribution in order to improve the performance of predictive models. The development of ever more elaborate normal-tissue complication probability (NTCP) models is driven by the concern that a poor characterization of the dose-response relationship may unnecessarily limit the effectiveness of the treatment; a simplistic NTCP model could imply conservative dose-volume constraints to the organs-at-risk (OAR), or cause avoidable suffering through a suboptimal distribution of the dose to OAR for a given tumor dose (e.g., Ref.…”

High accumulated doses to the inferior rectum are associated with late gastro-intestinal toxicity in a case-control study of prostate cancer patients treated with radiotherapy

“…The relatively weak associations may be explained by at least two key factors: (1) inter-fractional differences in rectal filling status, which make the planned dose not representative of the accumulated dose [10]; and (2) disregarding of spatial information. Rectal dose surface maps (DSMs) have been suggested as a solution to account for spatial patterns in associations between dose distributions and GI toxicity, potentially improving doseresponse relationships [11][12][13][14][15]. Statistical simulations of motion-inclusive accumulated doses have showed potentially stronger associations to morbidity risk than the planned doses [16][17][18].…”