Can Maximum Cancer Core Length Involvement on Template
Transperineal Prostate Mapping Biopsies Rule-in and Rule-out Clinically
Significant Prostate Cancers?
Yipeng Hu1, Hashim Uddin Ahmed2, Nimalan Arumainayagam2, Alex Freeman3, David J Hawkes 1,
Mark Emberton2, Dean C Barratt1
1 Centre for Medical Image Computing, University College London, London, UK
2 Department
D
t
t off Urology,
U l
Division
Di i i
off S
Surgical
i l and
d IInterventional
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l Sciences,
S i
University
U i
it College
C ll
London,
L d
London,
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UK
3 Department of Histopathology, University College London Hospital, London, UK
Introduction
Transperineal prostate mapping (TPM) using a 5mm grid may have a role in a) accurate risk stratification of men advised to have
active surveillance and b) disease localization for focal therapy and as an alternative reference standard to whole-mount
histology for evaluation of non-invasive diagnostic tests. However, although TPM is likely to have high accuracy for detection of
clinically significant foci it will also detect small low grade foci. At present, it is difficult to determine which foci are significant
based on the TPM. The objective of this work is to a) investigate the relationship between maximum cancer core length (MCCL)
and volume of the index (largest) cancer and b) determine the MCCL threshold to be used in identifying clinically significant
cancers.
Methods
126 consecutive whole-mount radical prostatectomy cases were evaluated from 1999 to 2001. Each whole-mount slice had
individual cancer foci delineated (by a pathologist) and scanned/digitised. 3D models of each gland were reconstructed by
aligning adjacent slices into a common space, using image registration and a shape-based interpolation technique (see figure 1).
Fi ti
Fixation
related
l t d ti
tissue shrinkage
h i k
was accounted
t d ffor. TPM was simulated
i
l t d on the
th reconstructed
t
t d data.
d t The
Th simulator
i
l t incorporated
i
t d
both inter-patient variance (e.g. gland geometry and cancer distribution) and inter-operator variance (e.g. needle orientation and
localization error) – see figure 2. Several hundred simulations were run for each case to compute the detection accuracy, for each
pre-defined MCCL threshold (1 to 10 mm).
Figure 1. An example of the process to reconstruct the histological data, Row (a):
original digitised histological slices with marked pathological lesions; Row (b):
segmented prostate gland (shown in gray level intensity) and lesions (shown in
pinkish colour); Row (c): Aligned slices after registration; and right Column (d): three
views of reconstructed gland with lesions shown in yellow.
Figure 2. illustrates the extent of the simulated positions and orientations of the
template grid relative to the gland after reorientation so that the base-apex axis is
horizontal. Reference base-apex axis is shown as black dotted line with relative
positions of the template, from left, transverse view and 3 sagital views with different
templates’ positions.
Results
A total of 781 foci were reconstructed, with mean index volume 2.32cc (range 0.02-17.24cc) and mean number of lesions per
specimen 6.2 (range 1 – 37). Overall, increasing the threshold of MCCL from 1mm to 10mm increased both sensitivity and
negative predictive value (NPV) whilst specificity and positive predictive value (PPV) decreased, all in a non-linear fashion. A
threshold MCCL of ≥ 6mm and ≥ 4mm were found to best rule-in and rule-out the presence of lesions of volume ≥ 0.5cc and ≥
0.2cc.
Lesion MCCL Sensitivity Specificity PPV NPV
Volume (mm)
(%)
(%)
(%) (%)
(cc)
≥ 0.2cc
≥4
97.3
64.6
95.7 75.1
≥ 0.5cc
≥6
95.1
53.8
83.2
82.1
Table 1 summarising the accuracy values for MCCL thresholds
4 & 6 mm.
Figure 3: Accuracy values for ≥
0.2cc lesion detection for increasing
cancer core length (CCL) thresholds
Figure 4: Accuracy values for ≥ 0.5cc
lesion detection for increasing cancer
core length (CCL) thresholds
Conclusions
Using two MCCL thresholds within individual biopsies from a TPM provides accurate information by which to predict whether a
particular lesion is clinically significant with respect to two volumes, 0.2cc and 0.5cc. Therefore, TPM is accurate to a) risk stratify
cancer into low and high risk, b) deliver focal therapy to only clinically significant foci with surveillance of untreated areas and c)
evaluate novel diagnostic tests in men with a raised PSA with a histology gold standard that is both accurate and appropriate.