br Prostate versus prostate and
Prostate versus prostate, and GTV versus GTV feature correlations were not calculated because of highly similar contoured volumes. B = 0 s/mm2-excluded ADC maps were not considered for prostate versus GTV feature comparison, because prostate ROIs copied from T2-weighted images sometimes encompassed low signal-to-noise regions within which ADC values were set to zero by the custom fitting algo-rithm.
Patient characteristics for each arm are summarized in Table 1. Seventy-seven tumors were identified across the cohort of 59 patients. Single tumors were identified in 45 patients, and 32 tumors were identified in fourteen patients. A single patient was processed with four GTVs, two patients were processed with three GTVs, and eleven Physics and Imaging in Radiation Oncology 9 (2019) 1–6
Fig. 1. T2-weighted images and ADC maps from four patients at baseline (left) and week six (right). These images emphasize the need for deformable registra-tion, because of loss of prostate-to-tumor Lipo2000 post-EBRT and shifts in prostate orientation between time-points. Routine distortion in diffusion-weighted images compared to T2-weighted images motivates additional correction of GTVs applied to ADC maps.
Summary of patient characteristics. Age and tumor volume are presented as mean ± 2 standard deviations.
Gleason score 2 2
patients were processed with two GTVs.
3.1. Feature extraction from T2-weighted images
No significant differences in baseline or week six T2-weighted fea-tures were noted between SIB and HDRB arms. No features changed for GTVs applied to T2-weighted images, including tumor volumes (base-line: 2.2 ± 3.7 cm3; week six: 1.9 ± 3.1 cm3; p = 0.23). Seven fea-tures in T2-weighted images changed in whole prostate ROIs applied to T2-weighted images, of which only a reduction in the sphericity feature from 0.79 ± 0.05 to 0.72 ± 0.11 was highly significant.
Feature Baseline Week Six Feature Baseline Week Six
3.2. Feature extraction from GTV ADC
No significant differences in baseline or week six ADC features were noted between SIB and HDRB arms. With SIB and HDRB arms pooled, significant GTV ADC feature changes between baseline and week six are presented in Table 2. GTV ROIs presented with significant changes in 32 and 17 features for ADC without and with b = 0 s/mm 2 exclusion, but the number of highly significant features (bold-face in Table 2) reduced from 17 to four with b = 0 s/mm2 exclusion. The primary ef-fect of b = 0 s/mm2 exclusion appeared to be a decrease in absolute ADC metrics, and an increase in ADC variance metrics.
3.3. Feature extraction from prostate ADC
Prostate ROIs presented with changes in 40 and 19 features for ADC without and with b = 0 s/mm2 exclusion. Eighteen of a maximum nineteen significantly different ADC features were common between b-value sets. The predominant prostate ADC feature changes between baseline and week six are presented in Table 3.
3.4. Prostate/GTV feature correlations
A large number of correlations between GTV and prostate features in T2-weighted images and ADC maps at baseline and week 6 time-points are summarized in Table 4. The twenty strongest of the corre-lations between ADC feature changes in GTV and prostate volumes post-EBRT are summarized in Table 5, with dominant representation from first-order statistics (e.g. median and 90Percentile for prostate; 10Percentile and Mean for GTV) and textural features from the Gray Level Size Zone Matrix class (e.g. Zone Variance for Prostate; Low Gray Level Zone Emphasis for GTV). The corresponding clustergram is pre-sented in Supplementary Material.
Methodology was presented for assessing early changes in GTV and prostate radiomics features of ADC maps and T2w images for prostate
cancer patients treated with radical radiotherapy. Deformable regis-tration enabled propagation of GTV and prostate volumes from baseline and week six, when intra-prostatic image contrast is reduced and prostate shape, orientation, and volume may differ. A manual correc-tion of the GTVs applied to ADC maps was then applied as deemed necessary to compensate for routine distortion in diffusion-weighted single-shot echo-planar images , and inter-scan motion. Radiomics analysis then identified a large set of GTV and prostate features which demonstrated early changes that may inform outcomes.
Numerous changes in ADC features in prostate and GTV volumes were presented. The prostate ADC histogram showed non-significant changes to the percentile histogram features, but standard deviation metrics reduced. Consistently, our prior results presented no significant change in the prostate ADC mean . The ADC histograms of the GTV presented with a dominant increase in the 10Percentile feature, smaller increase in ADC mean, and equivalent high-percentile features. These results are consistent with consensus position that prostate tumor ADC is related inversely to cellular density [12–14]. The GTV also presented with reduced deviation/variances during treatment, as reported by features including homogeneity, entropy, and contrast. Our prior data also demonstrated that the effect of EBRT is a trend towards homo-genization of zonal and tumor mean ADC values . This finding is fully consistent with the identification of predominant variance and textural feature changes within the prostate gland post-EBRT (Tables 3 and 5).