Masoom A Haider

University Health Network, Toronto, Ontario, Canada

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Publications (284)

  • [Show abstract] [Hide abstract] ABSTRACT: Purpose: Following an initial negative biopsy, there is an ongoing need for strategies to improve patient selection for repeat biopsy as well as the diagnostic yield from repeat biopsies. Materials and methods: As a collaborative Initiative of the American Urological Association and the Society of Abdominal Radiology's Prostate Cancer Disease-Focused Panel, an expert panel of urologists and radiologists conducted a literature review and formed consensus statements regarding the role of prostate MRI and MRI-targeted biopsy in patients with a negative biopsy, which are summarized in this review. Results and conclusion: s: The panel recognizes that many options exist for men with a previously negative biopsy. If a biopsy is recommended, prostate MRI and subsequent MRI-targeted cores appear to facilitate the detection of CS disease over standardized repeat biopsy. Thus, when high-quality prostate MRI is available, it should be strongly considered in any patient with a prior negative biopsy who has persistent clinical suspicion for prostate cancer and who is under evaluation for a possible repeat biopsy. The decision whether to perform MRI in this setting must also take into account results of any other biomarkers, the cost of the examination, as well as availability of high quality prostate MRI interpretation. If MRI is done, it should be performed, interpreted, and reported in accordance with PI-RADS V2 guidelines. Experience by the reporting radiologist and biopsy operator are required to achieve optimal results and practices integrating prostate MRI into patient management are advised to implement quality assurance programs to monitor targeted biopsy results. Patients receiving a PI-RADS assessment category of 3-5 warrant repeat biopsy with image guided targeting. While TRUS-MRI fusion or in-bore MRI-targeting may be valuable for more reliable targeting, especially for MRI lesions that are small or in difficult locations, in the absence of such targeting technologies, cognitive (visual) targeting remains a reasonable approach in skilled hands. At least two targeted cores should be obtained from each MRI-defined target. Given a number of studies showing a proportion of missed CS cancers by MRI-targeted cores, a case-specific decision must be made whether to also perform concurrent systematic sampling. However, performing solely targeted biopsy should only should be considered once quality assurance efforts have validated the performance of prostate MRI interpretations with results consistent with the published literature. In patients with a negative or low-suspicion MRI (PI-RADS assessment category of 1 or 2, respectively), other ancillary markers (i.e., PSA, PSAD, PSAV, PCA3, PHI, 4K) may be of value to identify patients warranting repeat systematic biopsy, although further data is needed on this topic. If a repeat biopsy is deferred on the basis of the MRI findings, then continued clinical and laboratory follow-up is advised and consideration should be given to incorporating repeat MRI in this diagnostic surveillance regimen.
    Article · Jun 2016 · The Journal of urology
  • [Show abstract] [Hide abstract] ABSTRACT: Published data on prostate magnetic resonance imaging (MRI) during follow-up of men on active surveillance are lacking. Current guidelines for prostate MRI reporting concentrate on prostate cancer (PCa) detection and staging. A standardised approach to prostate MRI reporting for active surveillance will facilitate the robust collection of evidence in this newly developing area.
    Article · Jun 2016 · European Urology
  • Article · May 2016 · Brachytherapy
  • Article · Apr 2016
  • Article · Apr 2016 · European Urology
  • [Show abstract] [Hide abstract] ABSTRACT: Purpose: Defining prostate cancer (PCa) lesion clinical target volumes (CTVs) for multiparametric magnetic resonance imaging (mpMRI) could support focal boosting or treatment to improve outcomes or lower morbidity, necessitating appropriate CTV margins for mpMRI-defined gross tumor volumes (GTVs). This study aimed to identify CTV margins yielding 95% coverage of PCa tumors for prospective cases with high likelihood. Methods and materials: Twenty-five men with biopsy-confirmed clinical stage T1 or T2 PCa underwent pre-prostatectomy mpMRI, yielding T2-weighted, dynamic contrast-enhanced, and apparent diffusion coefficient images. Digitized whole-mount histology was contoured and registered to mpMRI scans (error ≤2 mm). Four observers contoured lesion GTVs on each mpMRI scan. CTVs were defined by isotropic and anisotropic expansion from these GTVs and from multiparametric (unioned) GTVs from 2 to 3 scans. Histologic coverage (proportions of tumor area on co-registered histology inside the CTV, measured for Gleason scores [GSs] ≥6 and ≥7) and prostate sparing (proportions of prostate volume outside the CTV) were measured. Nonparametric histologic-coverage prediction intervals defined minimal margins yielding 95% coverage for prospective cases with 78% to 92% likelihood. Results: On analysis of 72 true-positive tumor detections, 95% coverage margins were 9 to 11 mm (GS ≥ 6) and 8 to 10 mm (GS ≥ 7) for single-sequence GTVs and were 8 mm (GS ≥ 6) and 6 mm (GS ≥ 7) for 3-sequence GTVs, yielding CTVs that spared 47% to 81% of prostate tissue for the majority of tumors. Inclusion of T2-weighted contours increased sparing for multiparametric CTVs with 95% coverage margins for GS ≥6, and inclusion of dynamic contrast-enhanced contours increased sparing for GS ≥7. Anisotropic 95% coverage margins increased the sparing proportions to 71% to 86%. Conclusions: Multiparametric magnetic resonance imaging-defined GTVs expanded by appropriate margins may support focal boosting or treatment of PCa; however, these margins, accounting for interobserver and intertumoral variability, may preclude highly conformal CTVs. Multiparametric GTVs and anisotropic margins may reduce the required margins and improve prostate sparing.
    Article · Apr 2016 · International journal of radiation oncology, biology, physics
  • [Show abstract] [Hide abstract] ABSTRACT: Purpose: The role magnetic resonance imaging (MRI) as a first-line screening test for prostate cancer is unknown. We conducted a pilot study to evaluate the feasibility of prostate MRI as the primary screening test for prostate cancer. Materials and methods: We recruited unselected men from the general population and performed multiparametric prostate MRI and random or targeted biopsies on all patients in addition to prostate specific antigen (PSA) testing. We compared the performance of prostate MRI and PSA test results in predicting the presence of prostate cancer. Results: Among 47 patients recruited, 18 (38.3%) had cancer, while 29 (61.7%) had no evidence of cancer. The adjusted odds ratio for having prostate cancer was significantly higher for MRI score (2.7, 95% C.I.: 1.4-5.4, p=0.004) than PSA level (1.1, 95% C.I.: 0.9-1.4, p=0.21). Among the 30 patients with a normal PSA level (<4.0 ng/mL), the positive predictive value (PPV) for patients with an MRI score of 4 or more was 66.7% (6 of 9) and the negative predictive value (NPV) for patients with an MRI score of 3 or less was 85.7% (18 of 21, p=0.004). Conclusions: In this pilot study, we demonstrate the feasibility of using multiparametric prostate MRI as the primary screening test for prostate cancer. Initial results show that prostate MRI is better in predicting prostate cancer than PSA among an unselected sample of the general population.
    Article · Feb 2016 · The Journal of urology
  • [Show abstract] [Hide abstract] ABSTRACT: The prognosis for locally advanced esophageal cancer is poor despite the use of trimodality therapy. In this phase II study, we report the feasibility, tolerability and efficacy of adjuvant sunitinib. Included were patients with stage IIa, IIB or III cancer of the thoracic esophagus or gastroesophageal junction. Neoadjuvant therapy involved Irinotecan (65 mg/m(2) ) + Cisplatin (30 mg/m(2) ) on weeks 1 and 2, 4 and 5, 7 and 8 with concurrent radiation (50Gy/25 fractions) on weeks 4-8. Sunitinib was commenced 4-13 weeks after surgery and continued for one year. Sixty-one patients were included in the final analysis, 36 patients commenced adjuvant sunitinib. Fourteen patients discontinued sunitinib due to disease recurrence (39%) within the 12-month period, 12 (33%) discontinued due to toxicity, and 3 (8%) requested cessation of therapy. In the overall population, median survival was 26 months with a 2 and 3-year survival rate of 52% and 35%, respectively. The median survival for the 36 patients treated with sunitinib was 35 months and 2-year survival probability of 68%. In a historical control, a prior phase II study with the same trimodality therapy (n = 43), median survival was 36 months, with a 2-year survival of 67%. Initiation of adjuvant sunitinib is feasible, but poorly tolerated, with no signal of additional benefit over trimodality therapy for locally advanced esophageal cancer.
    Article · Jan 2016 · Diseases of the Esophagus
  • Sun Mo Kim · Masoom A. Haider · David A. Jaffray · Ivan W. T. Yeung
    [Show abstract] [Hide abstract] ABSTRACT: Purpose: A previously proposed method to reduce radiation dose to patient in dynamic contrast-enhanced (DCE) CT is enhanced by principal component analysis (PCA) filtering which improves the signal-to-noise ratio (SNR) of time-concentration curves in the DCE-CT study. The efficacy of the combined method to maintain the accuracy of kinetic parameter estimates at low temporal resolution is investigated with pixel-by-pixel kinetic analysis of DCE-CT data. Methods: The method is based on DCE-CT scanning performed with low temporal resolution to reduce the radiation dose to the patient. The arterial input function (AIF) with high temporal resolution can be generated with a coarsely sampled AIF through a previously published method of AIF estimation. To increase the SNR of time-concentration curves (tissue curves), first, a region-of-interest is segmented into squares composed of 3 × 3 pixels in size. Subsequently, the PCA filtering combined with a fraction of residual information criterion is applied to all the segmented squares for further improvement of their SNRs. The proposed method was applied to each DCE-CT data set of a cohort of 14 patients at varying levels of down-sampling. The kinetic analyses using the modified Tofts' model and singular value decomposition method, then, were carried out for each of the down-sampling schemes between the intervals from 2 to 15 s. The results were compared with analyses done with the measured data in high temporal resolution (i.e., original scanning frequency) as the reference. Results: The patients' AIFs were estimated to high accuracy based on the 11 orthonormal bases of arterial impulse responses established in the previous paper. In addition, noise in the images was effectively reduced by using five principal components of the tissue curves for filtering. Kinetic analyses using the proposed method showed superior results compared to those with down-sampling alone; they were able to maintain the accuracy in the quantitative histogram parameters of volume transfer constant [standard deviation (SD), 98th percentile, and range], rate constant (SD), blood volume fraction (mean, SD, 98th percentile, and range), and blood flow (mean, SD, median, 98th percentile, and range) for sampling intervals between 10 and 15 s. Conclusions: The proposed method of PCA filtering combined with the AIF estimation technique allows low frequency scanning for DCE-CT study to reduce patient radiation dose. The results indicate that the method is useful in pixel-by-pixel kinetic analysis of DCE-CT data for patients with cervical cancer.
    Article · Jan 2016 · Medical Physics
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    [Show abstract] [Hide abstract] ABSTRACT: Magnetic Resonance Imaging (MRI) is a crucial medical imaging technology for the screening and diagnosis of frequently occurring cancers. However image quality may suffer by long acquisition times for MRIs due to patient motion, as well as result in great patient discomfort. Reducing MRI acquisition time can reduce patient discomfort and as a result reduces motion artifacts from the acquisition process. Compressive sensing strategies, when applied to MRI, have been demonstrated to be effective at decreasing acquisition times significantly by sparsely sampling the \emph{k}-space during the acquisition process. However, such a strategy requires advanced reconstruction algorithms to produce high quality and reliable images from compressive sensing MRI. This paper proposes a new reconstruction approach based on cross-domain stochastically fully connected conditional random fields (CD-SFCRF) for compressive sensing MRI. The CD-SFCRF introduces constraints in both \emph{k}-space and spatial domains within a stochastically fully connected graphical model to produce improved MRI reconstruction. Experimental results using T2-weighted (T2w) imaging and diffusion-weighted imaging (DWI) of the prostate show strong performance in preserving fine details and tissue structures in the reconstructed images when compared to other tested methods even at low sampling rates.
    Full-text Article · Dec 2015
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    [Show abstract] [Hide abstract] ABSTRACT: Diffusion weighted magnetic resonance imaging (DW-MRI) is a powerful tool in imaging-based prostate cancer (PCa) screening and detection. Endorectal coils are commonly used in DW-MRI to improve the signal-to-noise ratio (SNR) of the acquisition, at the expense of significant intensity inhomogeneities (bias field) that worsens as we move away from the endorectal coil. The presence of bias field can have a significant negative impact on the accuracy of different image analysis tasks, as well as the accuracy of PCa tumor localization, thus leading to increased inter- and intra-observer variability. The previously proposed bias field correction methods often suffer from undesired noise amplification that can reduce the image quality of the resulting bias-corrected DW-MRI data. Here, we propose a unified data reconstruction approach that enables joint compensation of bias field as well as data noise in diffusion weighted endorectal magnetic resonance (DW-EMR) imaging. The proposed noise-compensated, bias-corrected (NCBC) data reconstruction method takes advantage of a novel stochastically fully connected joint conditional random field (SFC-JCRF) model to mitigate the effects of data noise and bias field in the reconstructed DW-EMR prostate imaging data. The proposed NCBC reconstruction method was tested on synthetic DW-EMR data, physical DW-EMR phantom, as well as real DW-EMR imaging data. Both qualitative and quantitative analysis illustrated that the proposed NCBC method can achieve improved image quality when compared to other tested bias correction methods. As such, the proposed NCBC method can have strong potential for improving the consistency of image interpretations, thus leading to more accurate PCa diagnosis.
    Full-text Article · Dec 2015 · IEEE Transactions on Medical Imaging
  • M. A. Haider · A. Vosough · F. Khalvati · [...] · G. Bjarnason
    Conference Paper · Dec 2015
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    [Show abstract] [Hide abstract] ABSTRACT: Radiomics has proven to be a powerful prognostic tool for cancer detection, and has previously been applied in lung, breast, prostate, and head-and-neck cancer studies with great success. However, these radiomics-driven methods rely on pre-defined, hand-crafted radiomic feature sets that can limit their ability to characterize unique cancer traits. In this study, we introduce a novel discovery radiomics framework where we directly discover custom radiomic features from the wealth of available medical imaging data. In particular, we leverage novel StochasticNet radiomic sequencers for extracting custom radiomic features tailored for characterizing unique cancer tissue phenotype. Using StochasticNet radiomic sequencers discovered using a wealth of lung CT data, we perform binary classification on 42,340 lung lesions obtained from the CT scans of 93 patients in the LIDC-IDRI dataset. Preliminary results show significant improvement over previous state-of-the-art methods, indicating the potential of the proposed discovery radiomics framework for improving cancer screening and diagnosis.
    Full-text Article · Nov 2015
  • F. Khalvati · A. Wong · M. A. Haider
    Conference Paper · Nov 2015
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    Alexander Wong · Audrey G. Chung · Devinder Kumar · [...] · Masoom Haider
    [Show abstract] [Hide abstract] ABSTRACT: In this paper, we describe the underlying methodology behind discoveryradiomics, where the ultimate goal is to discover customized,abstract radiomic feature models directly from the wealth of medicalimaging data to better capture highly unique tumor traits beyondwhat can be captured using hand-crafted radiomic featuremodels. We further explore the current state-of-the-art in discoveryradiomics and their application to various forms of cancer suchas prostate cancer and lung cancer, and show that discovery radiomicscan yield significant potential clinical impact.
    Full-text Article · Oct 2015
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    [Show abstract] [Hide abstract] ABSTRACT: This paper presents a novel compensated diffusion magnetic resonanceimaging (cdMRI) system for improved tissue detail and contrastfor screening and diagnosis. The proposed cdMRI systemincorporates the intrinsic properties of the MRI apparatus to compensatefor artifacts and degradation caused through the imagingprocess. Experimental results for prostate imaging show that significantimprovements in tissue detail and contrast can be obtainedcompared to current MRI systems.
    Full-text Article · Oct 2015
  • [Show abstract] [Hide abstract] ABSTRACT: Renal disease variability in autosomal dominant polycystic kidney disease (ADPKD) is strongly influenced by the gene locus (PKD1 versus PKD2). Recent studies identified nontruncating PKD1 mutations in approximately 30% of patients who underwent comprehensive mutation screening, but the clinical significance of these mutations is not well defined. We examined the genotype-renal function correlation in a prospective cohort of 220 unrelated ADPKD families ascertained through probands with serum creatinine ≤1.4 mg/dl at recruitment. We screened these families for PKD1 and PKD2 mutations and reviewed the clinical outcomes of the probands and affected family members. Height-adjusted total kidney volume (htTKV) was obtained in 161 affected subjects. Multivariate Cox proportional hazard modeling for renal and patient survival was performed in 707 affected probands and family members. Overall, we identified pathogenic mutations in 84.5% of our families, in which the prevalence of PKD1 truncating, PKD1 in-frame insertion/deletion, PKD1 nontruncating, and PKD2 mutations was 38.3%, 4.3%, 27.1%, and 30.3%, respectively. Compared with patients with PKD1 truncating mutations, patients with PKD1 in-frame insertion/deletion, PKD1 nontruncating, or PKD2 mutations have smaller htTKV and reduced risks (hazard ratio [95% confidence interval]) of ESRD (0.35 [0.14 to 0.91], 0.10 [0.05 to 0.18], and 0.03 [0.01 to 0.05], respectively) and death (0.31 [0.11 to 0.87], 0.20 [0.11 to 0.38], and 0.18 [0.11 to 0.31], respectively). Refined genotype-renal disease correlation coupled with targeted next generation sequencing of PKD1 and PKD2 may provide useful clinical prognostication for ADPKD.
    Article · Oct 2015 · Journal of the American Society of Nephrology
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    [Show abstract] [Hide abstract] ABSTRACT: The Prostate Imaging - Reporting and Data System Version 2 (PI-RADS™ v2) is the product of an international collaboration of the American College of Radiology (ACR), European Society of Uroradiology (ESUR), and AdMetech Foundation. It is designed to promote global standardization and diminish variation in the acquisition, interpretation, and reporting of prostate multiparametric magnetic resonance imaging (mpMRI) examination, and it is based on the best available evidence and expert consensus opinion. It establishes minimum acceptable technical parameters for prostate mpMRI, simplifies and standardizes terminology and content of reports, and provides assessment categories that summarize levels of suspicion or risk of clinically significant prostate cancer that can be used to assist selection of patients for biopsies and management. It is intended to be used in routine clinical practice and also to facilitate data collection and outcome monitoring for research.
    Full-text Article · Oct 2015 · European Urology
  • [Show abstract] [Hide abstract] ABSTRACT: This paper presents a quantitative radiomics feature model for performing prostate cancer detection using Multi- Parametric MRI (mpMRI). It incorporates a novel tumour candidate identification algorithm to efficiently and thoroughly identify regions of concern and constructs a comprehensive radiomics feature model to detect tumourous regions. In contrast to conventional automated classification schemes, this radiomicsbased feature model aims to ground its decisions in a way that can be interpreted and understood by the diagnostician. This is done by grouping features into high-level feature categories which are already used by radiologists to diagnose prostate cancer: Morphology, Asymmetry, Physiology, and Size (MAPS), using biomarkers inspired by the PI-RADS guidelines for performing structured reporting on prostate MRI. Clinical mpMRI data were collected from thirteen men with histology-confirmed prostate cancer and labeled by an experienced radiologist. These annotated data were used to train classifiers using the proposed radiomics-driven feature model in order to evaluate the classification performance. The preliminary experimental results indicated that the proposed model outperformed each of its constituent feature groups as well as a comparable conventional mpMRI feature model. A further validation of the proposed algorithm will be conducted using a larger dataset as future work.
    Article · Sep 2015 · IEEE Transactions on Biomedical Engineering
  • [Show abstract] [Hide abstract] ABSTRACT: Accurate and fast segmentation and volume estimation of the prostate gland in magnetic resonance (MR) images are necessary steps in the diagnosis, treatment, and monitoring of prostate cancer. This paper presents an algorithm for the prostate gland volume estimation based on the semi-automated segmentation of individual slices in T2-weighted MR image sequences. The proposed sequential registration-based segmentation (SRS) algorithm, which was inspired by the clinical workflow during medical image contouring, relies on inter-slice image registration and user interaction/correction to segment the prostate gland without the use of an anatomical atlas. It automatically generates contours for each slice using a registration algorithm, provided that the user edits and approves the marking in some previous slices. We conducted comprehensive experiments to measure the performance of the proposed algorithm using three registration methods (i.e., rigid, affine, and nonrigid). Five radiation oncologists participated in the study where they contoured the prostate MR (T2-weighted) images of 15 patients both manually and using the SRS algorithm. Compared to the manual segmentation, on average, the SRS algorithm reduced the contouring time by 62 % (a speedup factor of 2.64×) while maintaining the segmentation accuracy at the same level as the intra-user agreement level (i.e., Dice similarity coefficient of 91 versus 90 %). The proposed algorithm exploits the inter-slice similarity of volumetric MR image series to achieve highly accurate results while significantly reducing the contouring time.
    Article · Sep 2015 · Journal of Digital Imaging

Publication Stats

5k Citations

Institutions

  • 2011
    • University Health Network
      • Joint Department of Medical Imaging
      Toronto, Ontario, Canada
  • 2010-2011
    • Mount Sinai Hospital, Toronto
      • Department of Medical Imaging
      Toronto, Ontario, Canada
  • 2007-2008
    • The Princess Margaret Hospital
      Toronto, Ontario, Canada