Benjamin Spilseth

Detection of Prostate Cancer: Quantitative Multiparametric MR Imaging Models Developed Using Registered Correlative Histopathology

Purpose To develop multiparametric magnetic resonance (MR) imaging models to generate a quantitative, user-independent, voxel-wise composite biomarker score (CBS) for detection of prostate cancer by using coregistered correlative histopathologic results, and to compare performance of CBS-based detection with that of single quantitative MR imaging parameters. Materials and Methods Institutional review board approval and informed consent were obtained. Patients with a diagnosis of prostate cancer underwent multiparametric MR imaging before surgery for treatment. All MR imaging voxels in the prostate were classified as cancer or noncancer on the basis of coregistered histopathologic data. Predictive models were developed by using more than one quantitative MR imaging parameter to generate CBS maps. Model development and evaluation of quantitative MR imaging parameters and CBS were performed separately for the peripheral zone and the whole gland. Model accuracy was evaluated by using the area under the receiver operating characteristic curve (AUC), and confidence intervals were calculated with the bootstrap procedure. The improvement in classification accuracy was evaluated by comparing the AUC for the multiparametric model and the single best-performing quantitative MR imaging parameter at the individual level and in aggregate. Results Quantitative T2, apparent diffusion coefficient (ADC), volume transfer constant (K(trans)), reflux rate constant (kep), and area under the gadolinium concentration curve at 90 seconds (AUGC90) were significantly different between cancer and noncancer voxels (P < .001), with ADC showing the best accuracy (peripheral zone AUC, 0.82; whole gland AUC, 0.74). Four-parameter models demonstrated the best performance in both the peripheral zone (AUC, 0.85; P = .010 vs ADC alone) and whole gland (AUC, 0.77; P = .043 vs ADC alone). Individual-level analysis showed statistically significant improvement in AUC in 82% (23 of 28) and 71% (24 of 34) of patients with peripheral-zone and whole-gland models, respectively, compared with ADC alone. Model-based CBS maps for cancer detection showed improved visualization of cancer location and extent. Conclusion Quantitative multiparametric MR imaging models developed by using coregistered correlative histopathologic data yielded a voxel-wise CBS that outperformed single quantitative MR imaging parameters for detection of prostate cancer, especially when the models were assessed at the individual level. (©) RSNA, 2016 Online supplemental material is available for this article.

Diagnostic Performance of Contrast-Enhanced MRI With Secretin-Stimulated MRCP for Non-Calcific Chronic Pancreatitis: A Comparison With Histopathology

OBJECTIVES:Diagnosis of non-calcific chronic pancreatitis (NCCP) in patients presenting with chronic abdominal pain is challenging and controversial. Contrast-enhanced magnetic resonance imaging (MRI) with secretin-stimulated MRCP (sMRCP) offers a safe and noninvasive modality to diagnose mild CP, but its findings have not been correlated with histopathology. We aimed to assess the correlation of a spectrum of MRI/sMRCP findings with surgical histopathology in a cohort of NCCP patients undergoing total pancreatectomy with islet autotransplantation (TPIAT).METHODS:Adult patients undergoing TPIAT for NCCP between 2008 and 2013 were identified from our institution’s surgery database and were included if they had MRI/sMRCP within a year before surgery. Histology was obtained from resected pancreas at the time of TPIAT by wedge biopsy of head, body, and tail, and was graded by a gastrointestinal pathologist who was blinded to the imaging features. A fibrosis score (FS) of 2 or more was considered as abnormal, with FS ≥6 as severe fibrosis. A multivariate regression analysis was performed for MRI features predicting fibrosis, after taking age, sex, smoking, alcohol, and body mass index (BMI) into consideration. A quantitative receiver operating characteristic (ROC) curve analysis was performed and Spearman rank correlation coefficient (r) was calculated.RESULTS:Fifty-seven patients (females=49, males=8) with NCCP and MRI/sMRCP were identified. ROC curve analysis showed that two or more MRI/sMRCP features provided the best balance of sensitivity (65%), specificity (89%), and accuracy (68%) to differentiate abnormal (FS≥2) from normal pancreatic tissue. Two or more features provided the best cutoff (sensitivity 88%, specificity 78%) for predicting severe fibrosis (FS≥6). There was a significant correlation between the number of features and severity of fibrosis (r=0.6, P<0.0001). A linear regression after taking age, smoking, and BMI into consideration showed that main pancreatic duct irregularity, T1-weighted signal intensity ratio between pancreas and paraspinal muscle, and duodenal filling after secretin injection to be significant independent predictors of fibrosis.CONCLUSIONS:A strong correlation exists between MRI/sMRCP findings and histopathology of NCCP.

How and why a generation of radiologists must be trained to accurately interpret prostate mpMRI.

be trained to accurately interpret prostate mpMRI Rajan T. Gupta, Benjamin Spilseth, Adam T. Froemming Department of Radiology, Duke University Medical Center, DUMC, Box 3808, Durham, NC 27710, USA Duke Cancer Institute, DUMC, Box 3494, 20 Duke Medicine Circle, Durham, NC 27710, USA Department of Radiology, University of Minnesota Medical Center, MMC 292, 420 East Delaware Street, Minneapolis, MN 55455, USA Department of Radiology, Mayo Clinic, 200 First St. SW, Rochester, MN 55905, USA

Contrast Enhanced MRI in the Diagnosis of HCC

Hepatocellular carcinoma (HCC) is the 6th most common cancer worldwide. Imaging plays a critical role in HCC screening and diagnosis. Initial screening of patients at risk for HCC is performed with ultrasound. Confirmation of HCC can then be obtained by Computed Tomography (CT) or Magnetic Resonance Imaging (MRI), due to the relatively high specificity of both techniques. This article will focus on reviewing MRI techniques for imaging HCC, felt by many to be the exam of choice for HCC diagnosis. MRI relies heavily upon the use of gadolinium-based contrast agents and while primarily extracellular gadolinium-based contrast agents are used, there is an emerging role of hepatobiliary contrast agents in HCC imaging. The use of other non-contrast enhanced MRI techniques for assessing HCC will also be discussed and these MRI strategies will be reviewed in the context of the pathophysiology of HCC to help understand the MR imaging appearance of HCC.

Use of MRI for Lobar Classification of Benign Prostatic Hyperplasia: Potential Phenotypic Biomarkers for Research on Treatment Strategies

OBJECTIVE We present an MRI classification of benign prostatic hyperplasia (BPH) for use as a phenotype biomarker in the study of proposed therapeutic interventions. CONCLUSION Six patterns of BPH distribution were identified. Illustrations are provided for each classification type.

Multiparametric prostate MRI: focus on T2-weighted imaging and role in staging of prostate cancer.

Multiparametric MRI (mpMRI) represents a growing modality for the non-invasive evaluation of prostate cancer (PCa) and is increasingly being used for patients with persistently elevated PSA and prior negative biopsies, for monitoring patients in active surveillance protocols, for preoperative characterization of cancer for surgical planning, and in planning for MRI-targeted biopsy. The focus of this work is twofold. First, we review the key role of T2-weighted imaging (T2WI) in mpMRI, specifically outlining how it is used for anatomic evaluation of the prostate, detection of clinically significant PCa, assessment of extraprostatic extension (EPE), and mimics of PCa on this sequence. We will also discuss optimal technical acquisition parameters for this sequence and recent technical advancements in T2WI. Second, we will delineate the role that mpMRI plays in the staging of PCa and describe the implications of the information that mpMRI can provide in determining the most appropriate management plan for the patient with PCa.

Which scores need a core? An evaluation of MR-targeted biopsy yield by PIRADS score across different biopsy indications

IntroductionMagnetic resonance imaging is being widely adopted in the clinical management of prostate cancer. The correlation of the Prostate Imaging Reporting and Data System (PIRADS) to the presence of cancer has been established but studies have primarily evaluated this in a single clinical setting. This study aims to characterize the correlation of PIRADS score to the diagnosis of cancer on fusion biopsy among men who are undergoing primary biopsy, those who have had a previous negative biopsy or men on active surveillance.Materials & MethodsA consecutive sample of men undergoing US-MR biopsy at a single academic institution from 2014 to 2017 were included in this retrospective study. Men were stratified into groups according to their clinical history: biopsy-naïve, previous negative transrectal ultrasound (TRUS) biopsy or on active surveillance. The correlation of PIRADS score to the diagnosis of any and clinically significant cancer (Gleason score ≥ 3 + 4) was determined.ResultsA total of 255 patients with 365 discrete lesions were analyzed. PIRADS score 1–2, 3, 4 and 5 yielded any prostate cancer in 7.7, 29.7, 42.3 and 82.4% of the cases, respectively, across all indications while clinically significant cancer was found in 0, 8.9, 21.4 and 62.7%, respectively. The area under the receiver operative curves for the diagnosis of any and significant cancer was 0.69 (95%CI: 0.64–0.74) and 0.74 (95%CI: 0.69–0.79) respectively. Men who have had a previous negative biopsy had lower detection rates for any prostate cancer for PIRADS 3 and 4 lesions compared to those that were biopsy-naïve or on active surveillance.ConclusionCancer detection rates are significantly associated with PIRADS score. Biopsy yields differ across biopsy indications which should be considered when selecting a PIRADS score threshold for biopsy. Biopsy of PIRADS 3 lesions could potentially be avoided in men who have previously undergone a negative TRUS biopsy.

Development of a measure for evaluating lesion‐wise performance of CAD algorithms in the context of mpMRI detection of prostate cancer

PURPOSE Computer-aided detection/diagnosis (CAD) of prostate cancer (PCa) on multiparametric MRI (mpMRI) is an active area of research. In the literature, the performance of predictive models trained to detect PCa on mpMRI has typically been reported in terms of voxel-wise measures such as sensitivity and specificity and/or area under the receiver operating curve (AUC). However, it is unclear whether models that score higher by these measures are actually superior. Here, we propose a novel method for lesion identification as well as novel measures that assess the quality of the detected lesions. METHODS A total of 46 axial MRI slices of interest from 34 patients and the associated histopathologic ground truths were used to develop and to characterize the proposed measures. The proposed lesion-wise score sℓ is based on the Jaccard similarity index with modifications that emphasize the overlap and colocalization of predicted lesions with ground truth lesions. Thresholding of sℓ allowed for the sensitivity and specificity of lesion detection to be assessed, while the proposed lesion-summary score sσ is a weighted average of sℓ s that provides a single summary statistic of lesion detection performance. The proposed measures were used to compare the lesion detection performance of a predictive model vs that of a radiologist on the same data set. The measures were also used to evaluate the degree to which viewing the cancer prediction improved diagnostic accuracy. RESULTS The lesion-wise score qualitatively reflected the goodness of predicted lesions over a wide range of values (sℓ = 0.1 to sℓ = 0.8) and was found to encompass a larger range of values than the Dice coefficient did over the same range of prediction qualities (0-0.9 vs 0-0.75). The lesion-summary score was shown to vary linearly with voxel-wise sensitivity and quadratically with voxel-wise specificity and correlated well with voxel-wise AUC (ρ = 0.68) and the Dice coefficient (ρ = 0.88). Radiologist performance was found to be significantly improved after viewing the model-generated cancer prediction maps as quantified by both sσ (P = 0.01) and DSC (P = 0.04), with improvements in both lesion detection sensitivity and specificity. CONCLUSION The proposed measures allow for the assessment of lesion detection performance, which is most relevant in a clinical setting and would not be possible to do with voxel-wise measures alone.

Small hepatocellular carcinomas displayed as a ring enhancing mass on arterial phase MRI in the chronically diseased liver

AIM To assess the prevalence of arterial phase (AP) ring-enhancing small hepatocellular carcinomas (HCC) on magnetic resonance imaging (MRI); detail additional MRI features that enable HCC diagnosis; and examine arterial timing as one possible cause of this appearance. MATERIALS AND METHODS Patients undergoing HCC screening with both computed tomography (CT) and MRI within 40 days were examined at a single institution over a 7- year time period ending in 2013. From this initial group, small (1-3 cm), (AP) ring-enhancing HCC on MRI were studied. RESULTS From the initial group of 64 patients with 129 HCC, 20 patients with 78 HCCs had a small diameter with 32 (41%) having an AP ring at MRI. The mean age of this latter group was 63-years old, with the average tumour diameter of 1.9 cm. Histopathology and secondary imaging supported a diagnosis of HCC in 20 (100%) patients and 31 (97%) lesions. Most of the ringed lesions had early AP timing. CONCLUSION This study revealed a high prevalence (41%) of small, AP ring HCC with MRI. The use of other MRI sequences adds support in making the proper diagnosis with this appearance. Early AP timing may help create this pattern.