Identification of prostate cancer using multiparametric MR imaging characteristics of prostate tissues referenced to whole mount histopathology.

In this study, the objective was to characterize the MR signatures of the various benign prostate tissues and to differentiate them from cancer. Data was from seventy prostate cancer patients who underwent multiparametric MRI (mpMRI) and subsequent prostatectomy. The scans included T2-weighted imaging (T2W), diffusion weighted imaging, dynamic contrast-enhanced MRI (DCE MRI), and MR spectroscopic imaging. Histopathology tissue information was translated to MRI images. The mpMRI parameters were characterized separately per zone and by tissue type. The tissues were ordered according to trends in tissue parameter means. The peripheral zone tissue order was cystic atrophy, high grade prostatic intraepithelial neoplasia (HGPIN), normal, atrophy, inflammation, and cancer. Decreasing values for tissue order were exhibited by ADC (1.8 10-3 mm2/s to 1.2 10-3 mm2/s) and T2W intensity (3447 to 2576). Increasing values occurred for DCE MRI peak (143% to 157%), DCE MRI slope (101%/min to 169%/min), fractional anisotropy (FA) (0.16 to 0.19), choline (7.2 to 12.2), and choline / citrate (0.3 to 0.9). The transition zone tissue order was cystic atrophy, mixed benign prostatic hyperplasia (BPH), normal, atrophy, inflammation, stroma, anterior fibromuscular stroma, and cancer. Decreasing values occurred for ADC (1.6 10-3 mm2/s to 1.1 10-3 mm2/s) and T2W intensity (2863 to 2001). Increasing values occurred for DCE MRI peak (143% to 150%), DCE MRI slope (101%/min to 137%/min), FA (0.18 to 0.25), choline (7.9 to 11.7), and choline / citrate (0.3 to 0.7). Logistic regression was used to create parameter model fits to differentiate cancer from benign prostate tissues. The fits achieved AUCs ≥0.91. This study quantified the mpMRI characteristics of benign prostate tissues and demonstrated the capability of mpMRI to discriminate among benign as well as cancer tissues, potentially aiding future discrimination of cancer from benign confounders.

Identifying Areas for Operational Improvement and Growth in IR Workflow Using Workflow Modeling, Simulation, and Optimization Techniques.

Identifying areas for workflow improvement and growth is essential for an interventional radiology (IR) department to stay competitive. Deployment of traditional methods such as Lean and Six Sigma helped in reducing the waste in workflows at a strategic level. However, achieving efficient workflow needs both strategic and tactical approaches. Uncertainties about patient arrivals, staff availability, and variability in procedure durations pose hindrances to efficient workflow and lead to delayed patient care and staff overtime. We present an alternative approach to address both tactical and strategic needs using discrete event simulation (DES) and simulation based optimization methods. A comprehensive digital model of the patient workflow in a hospital-based IR department was modeled based on expert interviews with the incumbent personnel and analysis of 192 days' worth of electronic medical record (EMR) data. Patient arrival patterns and process times were derived from 4393 individual patient appointments. Exactly 196 unique procedures were modeled, each with its own process time distribution and rule-based procedure-room mapping. Dynamic staff schedules for interventional radiologists, technologists, and nurses were incorporated in the model. Stochastic model simulation runs revealed the resource "computed tomography (CT) suite" as the major workflow bottleneck during the morning hours. This insight compelled the radiology department leadership to re-assign time blocks on a diagnostic CT scanner to the IR group. Moreover, this approach helped identify opportunities for additional appointments at times of lower diagnostic scanner utilization. Demand for interventional service from Outpatients during late hours of the day required the facility to extend hours of operations. Simulation-based optimization methods were used to model a new staff schedule, stretching the existing pool of resources to support the additional 2.5 h of daily operation. In conclusion, this study illustrates that the combination of workflow modeling, stochastic simulations, and optimization techniques is a viable and effective approach for identifying workflow inefficiencies and discovering and validating improvement options through what-if scenario testing.

Characterization and stratification of prostate lesions based on comprehensive multiparametric MRI using detailed whole-mount histopathology as a reference standard.

The purpose of this study was to characterize prostate cancer (PCa) based on multiparametric MR (mpMR) measures derived from MRI, diffusion, spectroscopy, and dynamic contrast-enhanced (DCE) MRI, and to validate mpMRI in detecting PCa and predicting PCa aggressiveness by correlating mpMRI findings with whole-mount histopathology. Seventy-eight men with untreated PCa received 3 T mpMR scans prior to radical prostatectomy. Cancerous regions were outlined, graded, and cancer amount estimated on whole-mount histology. Regions of interest were manually drawn on T2 -weighted images based on histopathology. Logistic regression was used to identify optimal combinations of parameters for the peripheral zone and transition zone to separate: (i) benign from malignant tissues; (ii) Gleason score (GS) ≤3 + 3 disease from ≥GS3 + 4; and (iii) ≤ GS3 + 4 from ≥GS4 + 3 cancers. The performance of the models was assessed using repeated fourfold cross-validation. Additionally, the performance of the logistic regression models created under the assumption that one or more modality has not been acquired was evaluated. Logistic regression models yielded areas under the curve (AUCs) of 1.0 and 0.99 when separating benign from malignant tissues in the peripheral zone and the transition zone, respectively. Within the peripheral zone, combining choline, maximal enhancement slope, apparent diffusion coefficient (ADC), and citrate measures for separating ≤GS3 + 3 from ≥GS3 + 4 PCa yielded AUC = 0.84. Combining creatine, choline, and washout slope yielded AUC = 0.81 for discriminating ≤GS3 + 4 from ≥GS4 + 3 disease. Within the transition zone, combining washout slope, ADC, and creatine yielded AUC = 0.93 for discriminating ≤GS3 + 3 and ≥GS3 + 4 cancers. When separating ≤GS3 + 4 from ≥GS4 + 3 PCa, combining choline and washout slope yielded AUC = 0.92. MpMRI provides excellent separation between benign tissues and PCa, and across PCa tissues of different aggressiveness. The final models prominently feature spectroscopy and DCE-derived metrics, underlining their value within a comprehensive mpMRI examination.

Improved multiparametric MRI discrimination between low-risk prostate cancer and benign tissues in a small cohort of 5α-reductase inhibitor treated individuals as compared with an untreated cohort.

The purpose of this study was to determine whether 5α-reductase inhibitors (5-ARIs) affect the discrimination between low-grade prostate cancer and benign tissues on multiparametric MRI (mpMRI). Twenty men with biopsy-proven Gleason 3 + 3 prostate cancer and 3 T mpMRI were studied. Ten patients (Tx) had been receiving 5-ARIs for at least a year at scan time. Ten untreated patients (Un) were matched to the treated cohort. For each subject two regions of interest representing cancerous and benign tissues were drawn within the peripheral zone of each prostate, MR measures evaluated, and cancer contrast versus benign (contrast = (MRTumor  - MRHealthy )/MRHealthy ) calculated. Decreased cancer contrast was noted on T2 -weighted images: 0.4 (Un) versus 0.3 (Tx). However, for functional MR measures, a better separation of cancerous and benign tissues was observed in the treated group. Cancer contrast on high-b diffusion-weighted imaging (DWI) was 0.61 (Un) versus 0.99 (Tx). Logistic regression analysis yielded higher AUC (area under the curve) values for distinguishing cancerous from benign regions in treated subjects on high-b DWI (0.71 (Un), 0.94 (Tx)), maximal enhancement slope (0.95 (Un), 1 (Tx)), peak enhancement (0.84 (Un), 0.93 (Tx)), washout slope (0.78 (Un), 0.99 (Tx)), Ktrans (0.9 (Un), 1 (Tx)), and combined measures (0.86 (Un), 0.99 (Tx)). Coefficients of variation for MR measures were lower in benign and cancerous tissues in the treated group compared with the untreated group. This study's results suggest an increase in homogeneity of benign and malignant peripheral zone prostatic tissues with 5-ARI exposure, observed as reduced variability of MR measures after treatment. Cancer discrimination was lower with T2 -weighted imaging, but was higher with functional MR measures in a 5-ARI-treated cohort compared with controls.

Practical aspects of prostate MRI: hardware and software considerations, protocols, and patient preparation.

The use of multiparametric MRI scans for the evaluation of men with prostate cancer has increased dramatically and is likely to continue expanding as new developments come to practice. However, it has not yet gained the same level of acceptance of other imaging tests. Partly, this is because of the use of suboptimal protocols, lack of standardization, and inadequate patient preparation. In this manuscript, we describe several practical aspects of prostate MRI that may facilitate the implementation of new prostate imaging programs or the expansion of existing ones.

Reduced-FOV excitation decreases susceptibility artifact in diffusion-weighted MRI with endorectal coil for prostate cancer detection.

The purposes of this study were to determine if image distortion is less in prostate MR apparent diffusion coefficient (ADC) maps generated from a reduced-field-of-view (rFOV) diffusion-weighted-imaging (DWI) technique than from a conventional DWI sequence (CONV), and to determine if the rFOV ADC tumor contrast is as high as or better than that of the CONV sequence. Fifty patients underwent a 3T MRI exam. CONV and rFOV (utilizing a 2D, echo-planar, rectangularly-selective RF pulse) sequences were acquired using b=600, 0s/mm(2). Distortion was visually scored 0-4 by three independent observers and quantitatively measured using the difference in rectal wall curvature between the ADC maps and T2-weighted images. Distortion scores were lower with the rFOV sequence (p<0.012, Wilcoxon Signed-Rank Test, n=50), and difference in distortion scores did not differ significantly among observers (p=0.99, Kruskal-Wallis Rank Sum Test). The difference in rectal curvature was less with rFOV ADC maps (26%±10%) than CONV ADC maps (34%±13%) (p<0.011, Student's t-test). In seventeen patients with untreated, biopsy confirmed prostate cancer, the rFOV sequence afforded significantly higher ADC tumor contrast (44.0%) than the CONV sequence (35.9%), (p<0.0012, Student's t-test). The rFOV sequence yielded significantly decreased susceptibility artifact and significantly higher contrast between tumor and healthy tissue.

Semiautomatic registration of digital histopathology images to in vivo MR images in molded and unmolded prostates.

PURPOSE: To evaluate a semiautomatic software-based method of registering in vivo prostate MR images to digital histopathology images using two approaches: (i) in which the prostates were molded to simulate distortion due to the endorectal imaging coil before fixation, and (ii) in which the prostates were not molded. MATERIALS AND METHODS: T2-weighted MR images and digitized whole-mount histopathology images were acquired for 26 patients with biopsy-confirmed prostate cancer who underwent radical prostatectomy. Ten excised prostates were molded before fixation. A semiautomatic method was used to align MR images to histopathology. Percent overlap between MR and histopathology images, as well as distances between corresponding anatomical landmarks were calculated and used to evaluate the registration technique for molded and unmolded cases. RESULTS: The software successfully morphed histology-based prostate images into corresponding MR images. Percent overlap improved from 80.4 ± 5.8% before morphing to 99.7 ± 0.62% post morphing. Molded prostates had a smaller distance between landmarks (1.91 ± 0.75 mm) versus unmolded (2.34 ± 0.68 mm), P < 0.08. CONCLUSION: Molding a prostate before fixation provided a better alignment of internal structures within the prostate, but this did not reach statistical significance. Software-based morphing allowed for nearly complete overlap between the pathology slides and the MR images.

Physiological complexity and system adaptability: evidence from postural control dynamics of older adults.

The degree of multiscale complexity in human behavioral regulation, such as that required for postural control, appears to decrease with advanced aging or disease. To help delineate causes and functional consequences of complexity loss, we examined the effects of visual and somatosensory impairment on the complexity of postural sway during quiet standing and its relationship to postural adaptation to cognitive dual tasking. Participants of the MOBILIZE Boston Study were classified into mutually exclusive groups: controls [intact vision and foot somatosensation, n = 299, 76 ± 5 (SD) yr old], visual impairment only (<20/40 vision, n = 81, 77 ± 4 yr old), somatosensory impairment only (inability to perceive 5.07 monofilament on plantar halluxes, n = 48, 80 ± 5 yr old), and combined impairments (n = 25, 80 ± 4 yr old). Postural sway (i.e., center-of-pressure) dynamics were assessed during quiet standing and cognitive dual tasking, and a complexity index was quantified using multiscale entropy analysis. Postural sway speed and area, which did not correlate with complexity, were also computed. During quiet standing, the complexity index (mean ± SD) was highest in controls (9.5 ± 1.2) and successively lower in the visual (9.1 ± 1.1), somatosensory (8.6 ± 1.6), and combined (7.8 ± 1.3) impairment groups (P = 0.001). Dual tasking resulted in increased sway speed and area but reduced complexity (P < 0.01). Lower complexity during quiet standing correlated with greater absolute (R = -0.34, P = 0.002) and percent (R = -0.45, P < 0.001) increases in postural sway speed from quiet standing to dual-tasking conditions. Sensory impairments contributed to decreased postural sway complexity, which reflected reduced adaptive capacity of the postural control system. Relatively low baseline complexity may, therefore, indicate control systems that are more vulnerable to cognitive and other stressors.

Frailty and the degradation of complex balance dynamics during a dual-task protocol.

BACKGROUND: Balance during quiet stance involves the complex interactions of multiple postural control systems, which may degrade with frailty. The complexity of center of pressure (COP) dynamics, as quantified using multiscale entropy (MSE), during quiet standing is lower in older adults, especially those with falls. We hypothesized that COP dynamics from frail elderly individuals demonstrate less complexity than those from nonfrail elderly controls; complexity decreases when performing a dual task; and postural complexity during quiet standing is independent of other conventional correlates of balance control, such as age and vision. METHODS: We analyzed data from a population-based study of community-dwelling older adults. Frailty phenotype (nonfrail, prefrail, or frail) was determined for 550 participants (age 77.9 +/- 5.5 years). COP excursions were quantified for 10 trials of 30 seconds each. Participants concurrently performed a serial subtraction task in half of the trials. Complexity of balance dynamics was quantified using MSE. Root-mean-square sway amplitude was also computed. RESULTS: Of the 550, 38% were prefrail and 9% were frail. Complexity of the COP dynamics in the anteroposterior direction was lower in prefrail (8.78 +/- 1.91 [mean +/- SD]) and frail (8.38 +/- 2.13) versus nonfrail (9.20 +/- 1.74) groups (p < .001). Complexity reduced by a comparable amount in all three groups while performing the subtraction task (p < .001). Quiet standing complexity was independently associated with frailty after adjusting for covariates related to balance while sway amplitude was not. CONCLUSION: Cognitive distractions during standing may further compromise balance control in frail individuals, leading to an increased risk of falls.

Subsensory vibrations to the feet reduce gait variability in elderly fallers.

The purpose of this study was to investigate the effect of subsensory vibratory noise applied to the soles of the feet on gait variability in a population of elderly recurrent fallers compared to non-fallers and young controls. Eighteen elderly recurrent fallers and 18 elderly non-fallers were recruited from the MOBILIZE Boston Study (MBS), a population-based cohort study investigating novel risk factors for falls. Twelve young participants were included as controls. Participants performed three 6-min walking trials while wearing a pair of insoles containing vibrating actuators. During each trial, the noise stimulus was applied for 3 of the 6min, and differences in stride, stance, and swing time variability were analyzed between noise and no-noise conditions. The use of vibrating insoles significantly reduced stride, stance, and swing time variability measures for elderly recurrent fallers. Elderly non-fallers also demonstrated significant reductions in stride and stance time variability. Although young participants showed decreases in all variability measures, the results did not achieve statistical significance. Gait variability reductions with noise were similar between the elderly recurrent fallers and elderly non-fallers. This study supports the hypothesis that subsensory vibratory noise applied to the soles of the feet can reduce gait variability in elderly participants. Future studies are needed to determine if this intervention reduces falls risk.