TZ tumors remain difficult to appreciate on mpMRI studies [1], with reported sensitivity/specificity for detection of 0.53/0.83 compared with 0.80/0.97 respectively for peripheral zone (PZ) tumors [2].

Tissue heterogeneity data afforded by MR textural analysis (MRTA) could increase the diagnostic accuracy of radiologists in detecting TZ tumors with potential utility in computer aided diagnosis (CAD).

Institutional review board waived the informed consent requirement for this retrospective study.

Men with suspected prostate cancer undergoing mpMRI prior to ‘20 zone’ template prostate mapping (TPM; [3]) biopsies between 1st January 2010 to 31st December 2012 inclusive were identified (n=210). Those with peripheral zone tumor, biopsy within 6 months prior to mpMRI, previous treatment for prostate cancer, metallic hip prostheses, or incomplete mpMRI/TPM data sets were excluded (n=143).

Sixty-seven men (mean age 63.4 years) underwent 1.5T mpMRI (Fig 1) prior to TPM (median interval 56 days). Twenty-six men (39%) had significant TZ tumor.

Subjects were grouped according to a previously used definition of cancer significance [4] categorising clinically significant disease as ≥ Gleason 3+4 OR ≥4mm maximum cancer core length (MCCL); other disease (i.e. ‘low risk’ <4mm MCCL AND ≤Gleason 3+3) was classified as non-significant and grouped with benign TZ histology [5].

Two experienced radiologists in consensus matched TPM to the single axial slice best depicting tumor or the largest TZ AP diameter for those with benign histology. A third blinded radiologist contoured the entire TZ as a region of interest (ROI) on each matched ADC, T2 and early post-contrast T1 weighted slice.

Whole TZ ROIs underwent MRTA using proprietary 'TexRAD' research software (version 3.3, TexRAD Ltd, Feedback Plc, Cambridge UK) [6] first using a Laplacian of Gaussian (LoG) band-pass spatial scale filter (SSF) to highlight features ranging between 2mm (fine) and 6mm (coarse) in radius (Figure 2) to extract and enhance imaging features at different sizes and highlight intensity variation corresponding to fine, medium and coarse texture scales within the TZ. Histogram analysis quantified first-order statistics of entropy, skewness, kurtosis of the TZ prior to and following filtration.

Differences between TZ ROI textural parameters were analysed using Mann Whitney U test (statistical significance p<0.05) and diagnostic accuracy of parameters for detection of significant TZ tumor determined by receiver operating characteristic (ROC) area under curve (AUC) analysis. The combination of the most discriminatory parameters for individual mpMRI sequences was determined using multivariate ROC-AUC analysis [7].

All analyses were performed on a whole TZ basis (incorporating tumor where present). Figure 3 shows the median values, interquartile ranges and significance of differences for individual best performing textural parameters prior to/following application of incremental spatial filters for each MRI sequence.

TZ containing significant tumor compared with benign/non-significant TZ demonstrates significantly higher early post contrast T1 and T2 image homogeneity particularly when images undergo prior ‘coarse’ spatial filtration (6mm), with entropy values of 5.90 and 5.69 respectively versus 6.16 and 5.94 (p<0.001).

Analysis of unfiltered TZ ADC histogram values in TZ containing significant tumor reveals significantly less peaked distribution compared to benign/non-significant TZ, with ADC kurtosis value of -0.51 versus 0.09 (p<0.001) becoming less significant with any prior spatial filtration (Figure 4). Median ADC, T1 and T2 skewness did not demonstrate any consistent difference between the two groups.

Coarsely filtered early post contrast T1 and T2 weighted image entropy and unfiltered ADC kurtosis are the best classifiers of TZ containing significant tumor for each respective multiparametric MR (mpMRI) sequence with area under the curve of 0.82, 0.77 and 0.80 respectively and in combination 0.89 (Figure 5).

Classification of TZ tumor-containing slices by textural analysis (ROC-AUC 0.77 to 0.82) was comparable with previously reported visual detection of TZ tumor by radiologists (ROC-AUC 0.73 to 0.84) [8] and confirms utility of increased TZ homogeneity on T2 and post contrast T1 images as a good discriminator of cancer [9] and suggests less peaked ADC values in TZ containing significant tumor. Applying spatial filters to images prior to textural quantification further improves classification performance on higher resolution T2/T1 images though not on lower resolution ADC images.

To our knowledge, this study is distinct from other work as it assessed in-vivo textural features derived from each mpMRI sequence from the entire TZ which obviates inherent difficulties in small lesion pre-identification and contouring.

Assessment of TZ heterogeneity by spatially filtered textural analysis of routinely acquired mpMRI images could therefore augment radiological interpretation and may in the future facilitate CAD.