Ibrahim Karademir

High-Resolution Diffusion-Weighted Imaging of the Prostate

OBJECTIVE The purpose of this study was to evaluate the effect of increasing the spatial resolution of the prostate DWI protocol on image quality and lesion conspicuity. SUBJECTS AND METHODS Twenty-nine patients with biopsy-proven prostate cancer undergoing MRI examinations were imaged with two diffusion-weighted imaging (DWI) protocols: current standard clinical protocol (6.7 mm(3) voxels) and a new high-resolution protocol (3.1 mm(3) voxels). Diffusion-weighted images were independently and subjectively scored on lesion conspicuity, internal architecture definition, and overall image quality by two radiologists. Average apparent diffusion coefficient (ADC) values were measured in normal tissue and cancerous lesions on both sequences. Reader scores and ADC and contrast values were compared between the two protocols. Cancer ADC values were correlated with Gleason scores. RESULTS The signal-to-noise ratio of the new high-resolution DWI protocol was 40% lower than that of the standard protocol. The reader scores were higher by 0.73 (range, 0.29-1.16) grades, or 19% (range, 7-32%), on average, for the new protocol, indicating better image quality. The average ADC values were 8% higher with the new protocol, with ADC contrast values between cancer and normal prostate unchanged. There was marginally significant correlation of cancer ADC values with Gleason scores (p = 0.05, r ≈ -0.36). CONCLUSION We showed that for DWI of the prostate at 3-7 mm(3) voxel sizes the benefits of higher spatial resolution outweigh the effects of reduced signal-to-noise and contrast-to-noise ratios, potentially improving the sensitivity to small or sparse prostate cancers. Radiologists can consider using higher-spatial-resolution DWI sequences in their practices.

Computerized Liver Volumetry on MRI by Using 3D Geodesic Active Contour Segmentation

OBJECTIVE Our purpose was to develop an accurate automated 3D liver segmentation scheme for measuring liver volumes on MRI. SUBJECTS AND METHODS Our scheme for MRI liver volumetry consisted of three main stages. First, the preprocessing stage was applied to T1-weighted MRI of the liver in the portal venous phase to reduce noise and produce the boundary-enhanced image. This boundary-enhanced image was used as a speed function for a 3D fast-marching algorithm to generate an initial surface that roughly approximated the shape of the liver. A 3D geodesic-active-contour segmentation algorithm refined the initial surface to precisely determine the liver boundaries. The liver volumes determined by our scheme were compared with those manually traced by a radiologist, used as the reference standard. RESULTS The two volumetric methods reached excellent agreement (intraclass correlation coefficient, 0.98) without statistical significance (p = 0.42). The average (± SD) accuracy was 99.4% ± 0.14%, and the average Dice overlap coefficient was 93.6% ± 1.7%. The mean processing time for our automated scheme was 1.03 ± 0.13 minutes, whereas that for manual volumetry was 24.0 ± 4.4 minutes (p < 0.001). CONCLUSION The MRI liver volumetry based on our automated scheme agreed excellently with reference-standard volumetry, and it required substantially less completion time.

MR imaging of ectopic pregnancy with an emphasis on unusual implantation sites

Ectopic pregnancy (EP) is a life-threatening condition and remains the leading cause of death in the first trimester of pregnancy, although the mortality rate has significantly decreased over the past few decades because of earlier diagnoses and great improvements in treatment. EP is most commonly located in the ampullary portion of the fallopian tube and rarely in unusual sites such as the interstitium, cervix, cesarean scar, anomalous rudimentary horn of the uterus and peritoneal abdominal cavity. MRI may confirm or give additional information to ultrasonography, which is the most user-dependent imaging modality. Magnetic resonance imaging can accurately localize the site of abnormal implantation. It could be helpful for EP patient treatment by distinguishing the ruptured and unruptured cases before methotrexate treatment. MRI is quite sensitive to blood and can identify the hemorrhage phase.

Dynamic contrast-enhanced MR imaging features of the normal central zone of the prostate.

RATIONALE AND OBJECTIVES Evaluate qualitative dynamic contrast-enhanced magnetic resonance imaging (MRI) characteristics of normal central zone based on recently described central zone MRI features. MATERIALS AND METHODS Institutional review board-approved, Health Insurance Portability and Accountability Act compliant study, 59 patients with prostate cancer, histopathology proven to not involve central zone or prostate base, underwent endorectal MRI before prostatectomy. Two readers independently reviewed T2-weighted images and apparent diffusion coefficient (ADC) maps identifying normal central zone based on low signal intensity and location. Next, two readers drew bilateral central zone regions of interest on dynamic contrast-enhanced magnetic resonance images in consensus and independently recorded enhancement curve types as type 1 (progressive), type 2 (plateau), and type 3 (wash-out). Identification rates of normal central zone and enhancement curve type were recorded and compared for each reviewer. The institutional review board waiver was approved and granted 05/2010. RESULTS Central zone identified in 92%-93% of patients on T2-weighted images and 78%-88% on ADC maps without significant difference between identification rates (P = .63 and P = .15 and inter-reader agreement (κ) is 0.64 and 0.29, for T2-weighted images and ADC maps, respectively). All central zones were rated either curve type 1 or curve type 2 by both radiologists. No statistically significant difference between the two radiologists (P = .19) and inter-reader agreement was κ = 0.37. CONCLUSIONS Normal central zone demonstrates either type 1 (progressive) or type 2 (plateau) enhancement curves on dynamic contrast-enhanced MRI that can be potentially useful to differentiate central zone from prostate cancer that classically demonstrates a type 3 (wash-out) enhancement curve.

Automatic prostate MR image segmentation with sparse label propagation and domain-specific manifold regularization

Automatic prostate segmentation in MR images plays an important role in prostate cancer diagnosis. However, there are two main challenges: (1) Large inter-subject prostate shape variations; (2) Inhomogeneous prostate appearance. To address these challenges, we propose a new hierarchical prostate MR segmentation method, with the main contributions lying in the following aspects: First, the most salient features are learnt from atlases based on a subclass discriminant analysis (SDA) method, which aims to find a discriminant feature subspace by simultaneously maximizing the inter-class distance and minimizing the intra-class variations. The projected features, instead of only voxel-wise intensity, will be served as anatomical signature of each voxel. Second, based on the projected features, a new multi-atlases sparse label fusion framework is proposed to estimate the prostate likelihood of each voxel in the target image from the coarse level. Third, a domain-specific semi-supervised manifold regularization method is proposed to incorporate the most reliable patient-specific information identified by the prostate likelihood map to refine the segmentation result from the fine level. Our method is evaluated on a T2 weighted prostate MR image dataset consisting of 66 patients and compared with two state-of-the-art segmentation methods. Experimental results show that our method consistently achieves the highest segmentation accuracies than other methods under comparison.

Prostate Volumes Derived From MRI and Volume-Adjusted Serum Prostate-Specific Antigen: Correlation With Gleason Score of Prostate Cancer

OBJECTIVE The purpose of this article is to study relationships between MRI-based prostate volume and volume-adjusted serum prostate-specific antigen (PSA) concentration estimates and prostate cancer Gleason score. MATERIALS AND METHODS The study included 61 patients with prostate cancer (average age, 63.3 years; range 52-75 years) who underwent MRI before prostatectomy. A semiautomated and MRI-based technique was used to estimate total and central gland prostate volumes, central gland volume fraction (central gland volume divided by total prostate volume), PSA density (PSAD; PSA divided by total prostate volume), and PSAD for the central gland (PSA divided by central gland volume). These MRI-based volume and volume-adjusted PSA estimates were compared with prostatectomy specimen weight and Gleason score by using Pearson (r) or Spearman (ρ) correlation coefficients. RESULTS The estimated total prostate volume showed a high correlation with reference standard volume (r = 0.94). Of the 61 patients, eight (13.1%) had a Gleason score of 6, 40 (65.6%) had a Gleason score of 7, seven (11.5%) had a Gleason score of 8, and six (9.8%) had a Gleason score of 9 for prostate cancer. The Gleason score was significantly correlated with central gland volume fraction (ρ = -0.42; p = 0.0007), PSAD (ρ = 0.46; p = 0.0002), and PSAD for the central gland (ρ = 0.55; p = 0.00001). CONCLUSION Central gland volume fraction, PSAD, and PSAD for the central gland estimated from MRI examinations show a modest but significant correlation with Gleason score and have the potential to contribute to personalized risk assessment for significant prostate cancer.

Hybrid multidimensional T2 and diffusion‐weighted MRI for prostate cancer detection

To study the dependence of apparent diffusion coefficient (ADC) and T2 on echo time (TE) and b‐value, respectively, in normal prostate and prostate cancer, using two‐dimensional MRI sampling, referred to as “hybrid multidimensional imaging.”

MRI-based prostate volume-adjusted prostate-specific antigen in the diagnosis of prostate cancer

To determine whether prostate‐specific antigen (PSA) levels adjusted by prostate and zonal volumes estimated from magnetic resonance imaging (MRI) improve the diagnosis of prostate cancer (PCa) and differentiation between patients who harbor high‐Gleason‐sum PCa and those without PCa.

Liver Volumetry in MRI by Using Fast Marching Algorithm Coupled with 3D Geodesic Active Contour Segmentation

In this chapter, we present an accurate automated 3D liver segmentation scheme for measuring liver volumes in MR images. Our scheme consisted of five steps. First, an anisotropic diffusion smoothing filter was applied to T1-weighted MR images of the liver in the portal-venous phase to reduce noise while preserving the liver boundaries. An edge enhancer and a nonlinear gray-scale converter were applied to enhance the liver boundary. This boundary-enhanced image was used as a speed function for a 3D fast marching algorithm to generate an initial surface that roughly approximated the liver shape. A 3D geodesic active contour segmentation algorithm refined the initial surface so as to more precisely determine the liver boundary. The liver volume was calculated based on the refined liver surface. The MR liver volumetry based on our automated scheme agreed excellently with “gold-standard” manual volumetry (intra-class correlation coefficient was 0.98) and required substantially less completion time (our processing time of 1 vs. 24 min/case in manual segmentation).

Agreement assessment in size measurement of hepatic metastases

The purpose of the study was to investigate patient-wise agreement among multiparametric magnetic resonance (MR) imaging sequences and radiologists, respectively, in the size assessment of hepatic metastases. A total of 30 liver metastases were identified from 20 patients and three radiologists independently measured the long and short axes for all metastases in T1-weighted, T2-weighted, diffusion-weighted imaging (DWI) with b of 0 and 800 s/mm2, and the apparent diffusion coefficient (ADC) map. We calculated the patient-wise intraclass correlation coefficient (ICCs) to estimate the interobserver and intersequence agreement in measured lesion size. Interobserver ICCs were 0.92-0.98 for different MR sequences and intersequence ICCs were 0.93-0.98. In conclusion, multiparametric MR imaging is a reliable tool for hepatic metastatic lesion measurement.