José A. Gómez

The University of Western Ontario, London, Ontario, Canada

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Publications (13)10.7 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Purpose: T2 weighted and diffusion weighted magnetic resonance imaging (MRI) show promise in isolating prostate tumours. Dynamic contrast enhanced (DCE)-MRI has also been employed as a component in multi-parametric tumour detection schemes. Model-based parameters such as Ktrans are conventionally used to characterize DCE images and require arterial contrast agent (CR) concentration. A robust parameter map that does not depend on arterial input may be more useful for target volume delineation. We present a dimensionless parameter (Wio) that characterizes CR wash-in and washout rates without requiring arterial CR concentration. Wio is compared to Ktrans in terms of ability to discriminate cancer in the prostate, as demonstrated via comparison with histology. Methods: Three subjects underwent DCE-MRI using gadolinium contrast and 7 s imaging temporal resolution. A pathologist identified cancer on whole-mount histology specimens, and slides were deformably registered to MR images. The ability of Wio maps to discriminate cancer was determined through receiver operating characteristic curve (ROC) analysis. Results: There is a trend that Wio shows greater area under the ROC curve (AUC) than Ktrans with median AUC values of 0.74 and 0.69 respectively, but the difference was not statistically significant based on a Wilcoxon signed-rank test (p = 0.13). Conclusions: Preliminary results indicate that Wio shows potential as a tool for Ktrans QA, showing similar ability to discriminate cancer in the prostate as Ktrans without requiring arterial CR concentration.
    SPIE Medical Imaging; 03/2014
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    ABSTRACT: Purpose: Multiparametric magnetic resonance imaging (MPMRI) supports detection and staging of prostate cancer, but the image characteristics needed for tumor boundary delineation to support focal therapy have not been widely investigated. We quantified the detectability (image contrast between tumor and non-cancerous contralateral tissue) and the localizability (image contrast between tumor and non-cancerous neighboring tissue) of Gleason score 7 (GS7) peripheral zone (PZ) tumors on MPMRI using tumor contours mapped from histology using accurate 2D-3D registration. Methods: MPMRI [comprising T2-weighted (T2W), dynamic-contrast-enhanced (DCE), apparent diffusion coefficient (ADC) and contrast transfer coefficient images] and post-prostatectomy digitized histology images were acquired for 6 subjects. Histology contouring and grading (approved by a genitourinary pathologist) identified 7 GS7 PZ tumors. Contours were mapped to MPMRI images using semi-automated registration algorithms (combined target registration error: 2 mm). For each focus, three measurements of mean +/- standard deviation of image intensity were taken on each image: tumor tissue (mT+/-sT), non-cancerous PZ tissue < 5 mm from the tumor (mN+/-sN), and non-cancerous contralateral PZ tissue (mC+/-sC). Detectability [D, defined as mT-mC normalized by sT and sC added in quadrature] and localizability [L, defined as mT-mN normalized by sT and sN added in quadrature] were quantified for each focus on each image. Results: T2W images showed the strongest detectability, although detectability |D|>=1 was observed on either ADC or DCE images, or both, for all foci. Localizability on all modalities was variable; however, ADC images showed localizability |L|>=1 for 3 foci. Conclusions: Delineation of GS7 PZ tumors on individual MPMRI images faces challenges; however, images may contain complementary information, suggesting a role for fusion of information across MPMRI images for delineation.
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    ABSTRACT: Measurement of prostate tumour volume can inform prognosis and treatment selection, including an assessment of the suitability and feasibility of focal therapy, which can potentially spare patients the deleterious side effects of radical treatment. Prostate biopsy is the clinical standard for diagnosis but provides limited information regarding tumour volume due to sparse tissue sampling. A non-invasive means for accurate determination of tumour burden could be of clinical value and an important step toward reduction of overtreatment. Multi-parametric magnetic resonance imaging (MPMRI) is showing promise for prostate cancer diagnosis. However, the accuracy and inter-observer variability of prostate tumour volume estimation based on separate expert contouring of T2-weighted (T2W), dynamic contrastenhanced (DCE), and diffusion-weighted (DW) MRI sequences acquired using an endorectal coil at 3T is currently unknown. We investigated this question using a histologic reference standard based on a highly accurate MPMRIhistology image registration and a smooth interpolation of planimetric tumour measurements on histology. Our results showed that prostate tumour volumes estimated based on MPMRI consistently overestimated histological reference tumour volumes. The variability of tumour volume estimates across the different pulse sequences exceeded interobserver variability within any sequence. Tumour volume estimates on DCE MRI provided the lowest inter-observer variability and the highest correlation with histology tumour volumes, whereas the apparent diffusion coefficient (ADC) maps provided the lowest volume estimation error. If validated on a larger data set, the observed correlations could support the development of automated prostate tumour volume segmentation algorithms as well as correction schemes for tumour burden estimation on MPMRI.
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    ABSTRACT: Accurate pathology assessment of post-prostatectomy specimens is important to determine the need for and to guide potentially life-saving adjuvant therapy. Digital pathology imaging is enabling a transition to a more objective quantification of some surgical pathology assessments, such as tumour volume, that are currently visually estimated by pathologists and subject to inter-observer variability. One challenge for tumour volume quantification is the traditional 3-5 mm spacing of images acquired from sections of radical prostatectomy specimens. Tumour volume estimates may benefit from a well-motivated approach to inter-slide tumour boundary interpolation. We implemented and tested a level set-based interpolation method and found that it produced 3D tumour surfaces that may be more biologically plausible than those produced via a simpler nearest-slide interpolation. We found that the simpler method produced larger tumour volumes, compared to the level set method, by a median factor of 2.3. For contexts where only tumour volume is of interest, we determined that the volumes produced via the simpler method can be linearly adjusted to the level setproduced volumes. The smoother surfaces from level set interpolation yielded measurable differences in tumour boundary location; this may be important in several clinical/research contexts (e.g. pathology-based imaging validation for focal therapy planning).
    Proc SPIE 03/2013;
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    ABSTRACT: Guidelines for localizing prostate cancer on imaging are ideally informed by registered post-prostatectomy histology. 3D histology reconstruction methods can support this by reintroducing 3D spatial information lost during histology processing. The need to register small, high-grade foci drives a need for high accuracy. Accurate 3D reconstruction method design is impacted by the answers to the following central questions of this work. (1) How does prostate tissue deform during histology processing? (2) What spatial misalignment of the tissue sections is induced by microtome cutting? (3) How does the choice of reconstruction model affect histology reconstruction accuracy? Histology, paraffin block face and magnetic resonance images were acquired for 18 whole mid-gland tissue slices from six prostates. 7-15 homologous landmarks were identified on each image. Tissue deformation due to histology processing was characterized using the target registration error (TRE) after landmark-based registration under four deformation models (rigid, similarity, affine and thin-plate-spline [TPS]). The misalignment of histology sections from the front faces of tissue slices was quantified using manually identified landmarks. The impact of reconstruction models on the TRE after landmark-based reconstruction was measured under eight reconstruction models comprising one of four deformation models with and without constraining histology images to the tissue slice front faces. Isotropic scaling improved the mean TRE by 0.8-1.0 mm (all results reported as 95% confidence intervals), while skew or TPS deformation improved the mean TRE by <0.1 mm. The mean misalignment was 1.1-1.9(°) (angle) and 0.9-1.3 mm (depth). Using isotropic scaling, the front face constraint raised the mean TRE by 0.6-0.8 mm. For sub-millimeter accuracy, 3D reconstruction models should not constrain histology images to the tissue slice front faces and should be flexible enough to model isotropic scaling.
    Journal of pathology informatics. 01/2013; 4:31.
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    ABSTRACT: This paper presents the results of an in vivo clinical study to accurately characterize prostate cancer using new features of ultrasound RF time series. The mean central frequency and wavelet features of ultrasound RF time series from seven patients are used along with an elaborate framework of ultrasound to histology registration to identify and verify cancer in prostate tissue regions as small as 1.7 mm x 1.7 mm. In a leave-one-patient-out cross-validation strategy, an average classification accuracy of 76% and the area under ROC curve of 0.83 are achieved using two proposed RF time series features. The results statistically significantly outperform those achieved by previously reported features in the literature. The proposed features show the clinical relevance of RF time series for in vivo characterization of cancer.
    Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 01/2013; 16(Pt 2):279-86.
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    ABSTRACT: PURPOSE: To present and evaluate a method for registration of whole-mount prostate digital histology images to ex vivo magnetic resonance (MR) images. MATERIALS AND METHODS: Nine radical prostatectomy specimens were marked with 10 strand-shaped fiducial markers per specimen, imaged with T1- and T2-weighted 3T MRI protocols, sliced at 4.4-mm intervals, processed for whole-mount histology, and the resulting histological sections (3-5 per specimen, 34 in total) were digitized. The correspondence between fiducial markers on histology and MR images yielded an initial registration, which was refined by a local optimization technique, yielding the least-squares best-fit affine transformation between corresponding fiducial points on histology and MR images. Accuracy was quantified as the postregistration 3D distance between landmarks (3-7 per section, 184 in total) on histology and MR images, and compared to a previous state-of-the-art registration method. RESULTS: The proposed method and previous method had mean (SD) target registration errors of 0.71 (0.38) mm and 1.21 (0.74) mm, respectively, requiring 3 and 11 hours of processing time, respectively. CONCLUSION: The proposed method registers digital histology to prostate MR images, yielding 70% reduced processing time and mean accuracy sufficient to achieve 85% overlap on histology and ex vivo MR images for a 0.2 cc spherical tumor. J. Magn. Reson. Imaging 2012;. © 2012 Wiley Periodicals, Inc.
    Journal of Magnetic Resonance Imaging 07/2012; · 2.57 Impact Factor
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    ABSTRACT: To develop and evaluate a technique for the registration of in vivo prostate magnetic resonance (MR) images to digital histopathologic images by using image-guided specimen slicing based on strand-shaped fiducial markers relating specimen imaging to histopathologic examination. The study was approved by the institutional review board (the University of Western Ontario Health Sciences Research Ethics Board, London, Ontario, Canada), and written informed consent was obtained from all patients. This work proposed and evaluated a technique utilizing developed fiducial markers and real-time three-dimensional visualization in support of image guidance for ex vivo prostate specimen slicing parallel to the MR imaging planes prior to digitization, simplifying the registration process. Means, standard deviations, root-mean-square errors, and 95% confidence intervals are reported for all evaluated measurements. The slicing error was within the 2.2 mm thickness of the diagnostic-quality MR imaging sections, with a tissue block thickness standard deviation of 0.2 mm. Rigid registration provided negligible postregistration overlap of the smallest clinically important tumors (0.2 cm(3)) at histologic examination and MR imaging, whereas the tested nonrigid registration method yielded a mean target registration error of 1.1 mm and provided useful coregistration of such tumors. This method for the registration of prostate digital histopathologic images to in vivo MR images acquired by using an endorectal receive coil was sufficiently accurate for coregistering the smallest clinically important lesions with 95% confidence.
    Radiology 04/2012; 263(3):856-64. · 6.21 Impact Factor
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    ABSTRACT: Methods for 3D histology reconstruction from sparse 2D digital histology images depend on knowledge about the positions, orientations, and deformations of tissue slices due to the histology process. This work quantitatively evaluates typical assumptions about the position and orientation of whole-mount prostate histology sections within coarsely sliced tissue blocks and about the deformation of tissue during histological processing and sectioning. 3-5 midgland tissue blocks from each of 7 radical prostatectomy specimens were imaged using magnetic resonance imaging before histology processing. After standard whole-mount paraffin processing and sectioning, the resulting sections were digitised. Homologous anatomic landmarks were identified on 22 midgland histology and MR images. Orientations and depths of sections relative to the front faces of the tissue blocks were measured based on the best-fit plane through the landmarks on the MR images. The mean+/-std section orientation was 1.7+/-1.1° and the mean+/-std depth of the sections was 1.0+/-0.5 mm. Deformation was assessed by using four transformation models (rigid, rigid+scale, affine and thin-plate-spline (TPS)) to align landmarks from histology and MR images, and evaluating each by measuring the target registration error (TRE) using a leave-one-out cross-validation. The rigid transformation model had higher mean TRE (p<0.001) than the other models, and the rigid+scale and affine models had higher mean TRE than the TPS model (p<0.001 and p<0.01 respectively). These results informed the design and development of a method for 3D prostate histology reconstruction based on extrinsic strand-shaped fiducial markers which yielded a 0.7+/-0.4 mm mean+/-std TRE.
    Proc SPIE 02/2012;
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    ABSTRACT: Accurate determination of cancer stage and grade from in vivo prostate imaging could improve biopsy guidance, therapy selection and, possibly, focal therapy guidance. Validating prostate cancer imaging ideally requires accurate 3D registration of in vivo imaging to histopathology, which is facilitated by intermediate histology-ex vivo imaging registration. This work introduces and evaluates a direct registration with fiducialbased local refinement of digital prostate histopathology to ex vivo magnetic resonance (MR) images that obviates three elements typical of existing methods: (1) guidance of specimen slicing, (2) imaging/photography of sliced tissue blocks, and (3) registration guidance based on anatomical image features. The mean target registration error (TRE) of 98 intrinsic landmarks across 21 histology images was calculated for the proposed direct registration (0.7 mm) and compared to existing approaches: indirect using tissue block MR images (0.8 mm) and image-guided-slicing-based (1.0 mm). The local refinement was also shown to improve existing approaches to achieve a similar mean TRE (0.7 mm).
    Prostate Cancer Imaging. Image Analysis and Image-Guided Interventions - International Workshop, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 22, 2011. Proceedings; 01/2011
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    ABSTRACT: We present a method for the registration of whole-mount digital histology images to ex vivo MR images of the prostate that relaxes the requirement for control over specimen slicing orientation. The approach uses extrinsic fiducials visible on histology and MRI, as well as block MR images of tissue slices after coarse sectioning, to support a two-stage registration approach: (1) registration of digital histology images to block MR images, and (2) registration of block MR images to whole-specimen ex vivo MR images. This work presents a preliminary quantitative validation on 4 clinical prostate specimens, yielding target registration errors of 0.6 mm and 0.5 mm, respectively, for the registration stages, measured using intrinsic fiducials.
    Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2011, March 30 - April 2, 2011, Chicago, Illinois, USA; 01/2011
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    ABSTRACT: Carcinoma cuniculatum of the penis is an extremely rare variant of squamous cell carcinoma characterized by an endophytic deeply branching and burrowing growth pattern. One documented case series demonstrated afflicted patients ranging in age from 73-83 years with the tumour located on the glans penis, coronal sulcus or foreskin. We report a case of a 55-year-old with disease located on the ventral aspect of the shaft of the penis. The tumour was invasive into the deep dermal connective tissue, comparatively superficial to all previous documented cases. He subsequently underwent a partial penectomy. The case is discussed with a brief review of the literature.
    Canadian Urological Association journal = Journal de l'Association des urologues du Canada 10/2010; 4(5):E129-32. · 1.92 Impact Factor
  • Conference Paper: Registration of
    Prostate Cancer Imaging. Computer-Aided Diagnosis, Prognosis, and Intervention - International Workshop, Held in Conjunction with MICCAI 2010, Beijing, China, September 24, 2010. Proceedings; 01/2010