B-value Imaging Research Articles

Low b-value (50-100) diffusion-weighted images detect significantly more hyperintense liver lesions in children than T2-weighted images.

Low b-value (50-100s/mm2) diffusion-weighted images (low b-value DWI) have been shown to be superior to T2-weighted fast spin echo sequence (T2-W) in detecting liver lesions in adults. There are no such studies assessing this difference in children. The purpose of the study was to compare the sensitivity of low b-value DWI images and T2-W images in detecting focal liver lesions in children. A retrospective review of liver magnetic resonance imaging (MRI) to assess focal liver lesions in 50 children (22 males, 28 females; age: 2months to 17years [mean: 10.9years]) was performed. Two radiologists reviewed both low b-value DWI and T2-W sequences independently on different occasions to note lesions, the smallest lesion size and the location. A consensus reading of the entire MRI examination and a correlation with follow-up, other imaging modalities and pathology in available cases were used to determine the final number of lesions as a reference standard. The average number of lesions per patient detected by both readers on each sequence was compared with each other and with the reference standard using the signed-rank test. The smallest lesions detected by each sequence were compared using the paired t-test. One hundred seventy hyperintense lesions were identified on consensus review to serve as the reference standard. The average number of lesions identified by both readers on low b-value DWI was 134 (79%) and on T2-W was 95 (56%). There was excellent interobserver agreement for detection of lesions on low b-value DWI (intraclass correlation coefficient [ICC]=0.96 [0.93-0.98]) and T2-W (ICC=0.85 [0.75-0.91]), with slightly better agreement on low b-value DWI. Both readers identified significantly more number of lesions on low b-value DWI compared to T2-W (Reader 1: P=0.0036, Reader 2: P=0.0001). Compared to the reference standard (mean number of lesions: 3.45), T2-W detected significantly fewer lesions (mean number of lesions: 1.91; P=0.0001) while there was no significant difference in lesion detection on low b-value DWI (mean number of lesions: 2.68; P=0.1527). Low b-value DWI and T2-W were not significantly different in identifying the smallest lesion size (Reader 1: P=0.19, Reader 2: P=0.47). Low b-value DWI images are more sensitive than T2-W sequences in detecting hyperintense focal liver lesions in children.

Potential of diffusion-weighted imaging in magnetic resonance enterography to identify neoplasms in the ileocecal region: Use of ultra-high b-value diffusion-weighted imaging.

Patients with chronic inflammatory bowel disease have an increased risk of colorectal cancer, and the differentiation between neoplastic and inflammatory lesions often poses a clinical dilemma. The aim of the present study was to investigate whether diffusion-weighted (DW) magnetic resonance (MR) enterography with ultra-high b-value facilitates the identification of neoplastic lesions in the ileocecal region. A total of 76 patients (22 patients with neoplasms, 26 inflammatory lesions and 28 normal subjects) from 292 cases of suspected bowel disorders were included in the present study. All patients were examined with conventional MR enterography and DW imaging (DWI) with seven different b-values (400, 600, 800, 1,000, 1,200, 1,500 and 3,000 sec/mm2) in a 3T MR scanner. DWI scans with different b-values were analyzed independently by two radiologists for the presence of ileocecal lesions. The signal intensity of the majority of inflammatory lesions and normal bowel segments gradually decreased to the background intensity with increasing b-values; however, neoplastic lesions demonstrated relative hyperintensity compared with the background. In addition, ~76% of the positive findings from b=3,000 sec/mm2 DWI were neoplasms. In conclusion, a lesion with consistently high signal intensity from DWI images with b-values increasing to 3,000 sec/mm2 indicated the presence of neoplasms. The results suggested that ultra-high b-value (3,000 sec/mm2) imaging may aid the clinical differentiation of neoplasms from benign conditions.

Threshold Isocontouring on High b-Value Diffusion-Weighted Images in Magnetic Resonance Mammography.

Motivated by the similar appearance of malignant breast lesions in high b-value diffusion-weighted imaging (DWI) and positron emission tomography, the purpose of this work was to evaluate the applicability of a threshold isocontouring approach commonly used in positron emission tomography to analyze DWI data acquired from female human breasts with minimal interobserver variability. Twenty-three female participants (59.4 ± 10.0 years) with 23 lesions initially classified as suggestive of cancers in x-ray mammography screening were subsequently imaged on a 1.5-T magnetic resonance imaging scanner. Diffusion-weighted imaging was performed prior to biopsy with b values of 0, 100, 750, and 1500 s/mm. Isocontouring with different threshold levels was performed on the highest b-value image to determine the voxels used for subsequent evaluation of diffusion metrics. The coefficient of variation was computed by specifying 4 different regions of interest drawn around the lesion. Additionally, a receiver operating statistical analysis was performed. Using a relative threshold level greater than or equal to 0.85 almost completely suppresses the intra-individual and inter-individual variability. Among 4 studied diffusion metrics, the diffusion coefficients from the intravoxel incoherent motion model returned the highest area under curve value of 0.9. The optimal cut-off diffusivity was found to be 0.85 μm/ms with a sensitivity of 87.5% and specificity of 90.9%. Threshold isocontouring on high b-value maps is a viable approach to reliably evaluate DWI data of suspicious focal lesions in magnetic resonance mammography.

Signal Intensity of High B-value Diffusion-weighted Imaging for the Detection of Prostate Cancer.

Background:Diffusion-weighted imaging (DWI) is a main component of multiparametric MRI for prostate cancer detection. Recently, high b value DWI has gained more attention because of its capability for tumor characterization. Objective:To assess based on histopathological findings of transrectal ultrasound (TRUS)-guided prostate biopsy as a reference, an increase in signal intensity of prostatic lesions in comparison with normal background tissue on high b-value diffusion-weighted images could be a sign of malignancy. Material and Methods: Fifty-three consecutive patients retrospectively included in the study. All patients underwent routine TRUS-guided prostate biopsies involving 12 cores after the magnetic resonance imaging (MRI) examinations. In seventeen patients (n =35 lesions), the prostate cancer was histologically confirmed by TRUS-guided prostate biopsy. The biopsy results of other patients were negative. Signal intensities on the high b-value (1600 s/mm2) images of the peripheral zone, the central gland, and the defined lesions were evaluated using region of interest-based measurements. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for prostate cancer detection using signal intensity of high b value diffusion-weighted images were calculated. Results:In the patients with confirmed prostate cancer, fourteen had visually increased SI on the high b-value images. The SI of lesions for these patients was higher than the SI of peripheral zone (22±18%) or central gland (31±20%). In patients with a negative biopsy, eight had visually increased SI on the high b-value images. The SI of lesions for these patients was 23±21% and 35±18% higher than the SI in the peripheral zone and the central gland, respectively. The sensitivity, specificity, PPV, and NPV for prostate cancer using SI of high b value DWI were 71, 87, 62, and 87 %, respectively. Conclusion:Visually increased SI on the high b-value images can be an indication of malignancy, although some benign lesions also show this increase in signal intensity.

MRI for prostate cancer: can computed high b-value DWI replace native acquisitions?

To compare computed high b-value diffusion-weighted images (c-DWI) derived from low b-value DWI images and acquired high b-value DWI (a-DWI), in overall image quality and prostate cancer detection rate. A total of 124 consecutive men with suspected prostate cancer (PCa) underwent diagnosis prostate MRI on a 3.0T MR system using a 32-channel phased-array torso coil. Among them, 63 underwent prostate biopsy. MRI protocol included 3DT2w images, high resolution Fov Optimized and Constrained Undistorted Single-Shot (FOCUS™) DWI images with b-values of 100, 400, 800, and 2000s/mm2 and dynamic contrast enhanced images. C-DWI images (2000 and 2500s/mm2) were derived from the three lower acquired b-value DWI images using a mono-exponential diffusion decay. C-DWI and acquired high b-value DWI (a-DWI) (2000s/mm2) were compared for image quality (background signal suppression, anatomic clarity, ghosting, distortion) and tumor conspicuity by four radiologists. C-DWIs demonstrated higher rating than a-DWIs for overall image quality despite worsened ghosting. In patients with a biopsy, similar detection rate was observed while conspicuity was better with c-DWI (p < 0.001). Non-acquisition of high b-value a-DWI reduced total acquisition time by 220s per patient. C-DWI provides a substantial reduction in acquisition time while maintaining comparable prostate cancer detection rate and improving global image quality. • Computed DWI improves global quality of prostate MRI. • Computed DWI improves analysis of DWI images with decrease acquisition time. • Computed DWI provides greater background suppression of parenchyma and improves conspicuity of suspicious lesion.

Computed diffusion-weighted imaging for acute pediatric encephalitis/encephalopathy.

BackgroundComputed diffusion-weighted imaging (DWI) (cDWI) is a computational technique that can be used to calculate a high b-value image from DWI acquired with at least two different lower b-valu...

Diffusion-weighted imaging of the kidney: comparison between simultaneous multi-slice and integrated slice-by-slice shimming echo planar sequence

To compare the simultaneous multi-slice (SMS) and integrated slice-by-slice shimming (iShim) single-shot echo planar imaging (ssEPI) for diffusion-weighted imaging (DWI) of the kidneys. In this prospective study, six healthy volunteers and 22 patients with renal diseases underwent SMS and iShim DWI of the kidney with five b-values (0, 80, 400, 800, 1,600 s/mm2) at 3 T. The subjective image quality, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC values were evaluated. The subjective image quality scores, SNR, CNR, ADC values and scan time of SMS and iShim DWI were compared. Scan time of SMS DWI (1 minute 38 seconds) was significantly reduced compared to iShim ssEPI (3 minutes 33 seconds). No statistically significant differences in the SNR or subjective image quality were observed on the b=0 images, but the SNR and overall image quality scores were significantly higher on the other four b-value images at SMS DWI. Image distortions were also comparable, but there were fewer artefacts on the b=80 and b=800 images in SMS DWI. CNR was significantly higher on the b=0 and b=1,600 images in SMS DWI. SNR and subjective image-quality scores of ADC maps were significantly higher in SMS DWI, whereas CNR showed no significant difference. The ADC value of renal parenchyma was similar in SMS and iShim DWI (1.54±0.11 × 10-3 versus 1.52±0.16×10-3 mm2/s, p=0.343). SMS can substantially reduce imaging time of kidney DWI with slightly improved image quality and comparable ADC values of renal parenchyma compared to iShim ss-EPI sequence.

Classification of suspicious lesions on prostate multiparametric MRI using machine learning.

We present a radiomics-based approach developed for the SPIE-AAPM-NCI PROSTATEx challenge. The task was to classify clinically significant prostate cancer in multiparametric (mp) MRI. Data consisted of a "training dataset" (330 suspected lesions from 204 patients) and a "test dataset" (208 lesions/140 patients). All studies included T2-weighted (T2-W), proton density-weighted, dynamic contrast enhanced, and diffusion-weighted imaging. Analysis of the images was performed using the MIM imaging platform (MIM Software, Cleveland, Ohio). Prostate and peripheral zone contours were manually outlined on the T2-W images. A workflow for rigid fusion of the aforementioned images to T2-W was created in MIM. The suspicious lesion was outlined using the high b-value image. Intensity and texture features were extracted on four imaging modalities and characterized using nine histogram descriptors: 10%, 25%, 50%, 75%, 90%, mean, standard deviation, kurtosis, and skewness (216 features). Three classification methods were used: classification and regression trees (CART), random forests, and adaptive least absolute shrinkage and selection operator (LASSO). In the held out by the organizers test dataset, the areas under the curve (AUCs) were: 0.82 (random forests), 0.76 (CART), and 0.76 (adaptive LASSO). AUC of 0.82 was the fourth-highest score of 71 entries (32 teams) and the highest for feature-based methods.

Introduction to the Technical Aspects of Computed Diffusion-weighted Imaging for Radiologists.

Diffusion-weighted (DW) imaging is a magnetic resonance (MR) imaging method. It is an indispensable sequence for the diagnosis of acute cerebral infarction and is recognized as a standard tool in oncologic imaging. Computed DW imaging refers to the synthesizing of arbitrary b-value DW images from a set of measured b-value images by voxelwise fitting. Computed DW imaging is advantageous because it generates DW images with a higher diffusion effect than that achievable by using the MR imaging units in use today. Additionally, computed DW imaging can reduce imaging time while producing images characterized by a higher signal-to-noise ratio than what the acquired DW images would display at the corresponding b values. By fitting input images acquired at a lower b value and correspondingly a shorter echo time, the signal intensity of the resulting computed DW image is closer to the ideal case. Computed DW images are generated by employing mathematical models that use mono-, bi-, or triexponential equations. To generate accurate computed DW images, the appropriate model must be selected, and the image parameters for the input data must be chosen accordingly. In addition, to reduce artifacts on computed DW images, the misalignment of input data must be corrected with the aid of image registration techniques. ©RSNA, 2018.

Dual-Phase ADC Modelling of Breast Masses in Diffusion-Weighted Imaging: Comparison with Histopathologic Findings.

To investigate the diagnostic value of dual-phase apparent diffusion coefficient (ADC) compared to traditional ADC values in quantitative diffusion-weighted imaging (DWI) for differentiating between benign and malignant breast masses. Diffusion-weighted images of pathologically confirmed 88 benign and 85 malignant lesions acquired using a 3.0T MR scanner were analyzed. Small region-of-interests focusing on the highest signal intensity of lesions were used. Lesion ADC estimates were obtained separately from all b-value images (ADC; b=50, 400 and 800s/mm2), lower b-value images (ADClow; b=50 and 400s/mm2) and higher b-value images (ADChigh; b=400 and 800s/mm2). A set of dual-phase ADC (dpADC) models were constructed using ADClow, ADChigh and a perfusion influence factor ranging from 0 to 1. Strong positive correlation is observable between ADC and all dpADCs (ρ=0.80-1.00). Differences in ADC and dpADCs between the benign and the malignant lesions are all significant (p<0.05). In detecting malignancy, traditional lesion ADC provides a good performance (AUC=89.9%) however dpADC0.5 (dpADC with a factor of 0.5) accomplishes a better performance (AUC=90.8%). At optimal thresholds, ADC achieves 94.1% sensitivity, 72.7% specificity and 83.2% accuracy while dpADC0.5 leads to 92.9% sensitivity, 79.5% specificity and 86.1% accuracy. Dual-phase ADC modelling may improve the accuracy in breast cancer diagnosis using DWI. Further prospective studies are needed to justify its benefit in clinical setting.

Ultra-high-b radial diffusion-weighted imaging (UHb-rDWI) of human cervical spinal cord.

Injury in the cervical spinal cord (CSC) can lead to varying degrees of neurologic deficit and persistent disability. Diffusion tensor imaging (DTI) is a promising method to evaluate white matter integrity and pathology. However, the conventional DTI results are limited with respect to the specific details of neuropathology and microstructural architecture. In this study we used ultrahigh-b radial-DWI (UHb-rDWI) with b-values ranging from 0 to ∼7500 s/mm2 and calculated decay constant (DH ) at the high b-values, which gives much deeper insight about the microscopic environment of CSC white matter. To evaluate a novel diffusion MRI, UHb-rDWI technique for imaging of the CSC. Longitudinal. Four healthy controls, each scanned twice. 3T/2D single shot diffusion-weighted stimulated echo planar imaging with reduced field of view. The signal from each pixel of b0 (b = 0) and b-value (b ≠ 0) images were fitted to a biexponential function and normalized. The signal-b curve is obtained by dividing the latter curve by the former. DH was obtained from the curve at b >4000 s/mm2 . A Monte-Carlo Simulation (MCS) was performed to investigate how DH changes upon the increased water-exchange at the CSC. The signal-b curves plotted at multiple levels of healthy CSC are almost identical on two successive scans and show a biexponential decay behavior: fast exponential decay at lower b-values and much slower decay at UHb-values. The mean values of DH were measured as (0.0607 ± 0.02531) ×10-3 and (0.0357 ± 0.02072) ×10-3 s/mm2 at the lateral funiculus and posterior column, respectively. MCS of diffusion MRI shows that the DH is elevated by increased water exchange between the intra- and extraaxonal spaces. UHb-rDWI signal-b plots of the normal CSC were highly reproducible on successive scans and their biexponential decay behavior can be used to characterize normal spinal white matter. 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:204-211.

The impact of computed high b-value images on the diagnostic accuracy of DWI for prostate cancer: A receiver operating characteristics analysis

To evaluate the performance of computed high b value diffusion-weighted images (DWI) in prostate cancer detection. 97 consecutive patients who had undergone multiparametric MRI of the prostate followed by biopsy were reviewed. Five radiologists independently scored 138 lesions on native high b-value images (b = 1200 s/mm2), apparent diffusion coefficient (ADC) maps, and computed high b-value images (contrast equivalent to b = 2000 s/mm2) to compare their diagnostic accuracy. Receiver operating characteristic (ROC) analysis and McNemar’s test were performed to assess the relative performance of computed high b value DWI, native high b-value DWI and ADC maps. No significant difference existed in the area under the curve (AUC) for ROCs comparing B1200 (b = 1200 s/mm2) to computed B2000 (c-B2000) in 5 readers. In 4 of 5 readers c-B2000 had significantly increased sensitivity and/or decreased specificity compared to B1200 (McNemar’s p < 0.05), at selected thresholds of interpretation. ADC maps were less accurate than B1200 or c-B2000 for 2 of 5 readers (P < 0.05). This study detected no consistent improvement in overall diagnostic accuracy using c-B2000, compared with B1200 images. Readers detected more cancer with c-B2000 images (increased sensitivity) but also more false positive findings (decreased specificity).

Computed diffusion weighted imaging (cDWI) and voxelwise-computed diffusion weighted imaging (vcDWI) for oncologic liver imaging: A pilot study

ObjectiveAim of the study was to evaluate the influence of the selection of measured b-values on the precision of cDWI in the upper abdomen as well as on the lesion contrast of PET-positive liver metastases in cDWI and vcDWI. MethodsWe performed a retrospective analysis of 10 patients (4 m, 63.5 ± 12.9 y/o) with PET-positive liver metastases examined in 3 T-PET/MRI with b = 100,600,800,1000 and 1500s/mm2. cDWI (cb1000/cb1500) and vcDWI were computed based on following combinations: i) b = 100/600 s/mm2, ii) b = 100/800 s/mm2, iii) b = 100/1000s/mm2, iv) b = 100/600/1000s/mm2 v) all measured b-values. Mean signal intensity (SI) and standard deviation (SD) in the liver, spleen, kidney, bone marrow and in liver lesions were acquired. The coefficient of variation (CV = SD/SI), the differences of SI between measured and calculated high b-value images and the lesion contrast (SI lesion/liver) were computed. ResultsWith increasing upper measured b-values, the CV in cDWI and vcDWI decreased (CV in the liver in cb1500: 0.42 with b100/600 s/mm2 and 0.28 with b100/b1000s/mm2) while the differences of measured and calculated b-value images decreased (in the liver in cb1500: 30.7% with b = 100/600 s/mm2, 19.7% with b100/b1000s/mm2). In diffusion-restricted lesions, lesion contrast was at least 1.6 in cb1000 and 1.4 in cb1500, respectively, with an upper measured b-value of b = 800 s/mm2 and 2.1 for vcDWI with an upper measured b-value of b = 1000s/mm2. Overall, the lesion contrast was superior in cb1500 and vcDWI compared to cb1000 (15% and 11%, respectively). ConclusionMeasuring higher upper b-values seems to lead to more precise computed high b-value images and a decrease of CV. vcDWI provides a comparable lesion contrast to b = 1500s/mm2 and offers additionally the reduction of T2 shine-through effects. For vcDWI, measuring b = 1000s/mm2 as upper b-value seems to be necessary to guarantee good lesion visibility in the liver based on our preliminary results.

Computed Diffusion-Weighted Imaging in Prostate Cancer: Basics, Advantages, Cautions, and Future Prospects

Computed diffusion-weighted MRI is a recently proposed post-processing technique that produces b-value images from diffusion-weighted imaging (DWI), acquired using at least two different b-values. This article presents an argument for computed DWI for prostate cancer by viewing four aspects of DWI: fundamentals, image quality and diagnostic performance, computing procedures, and future uses.

Imaging Facilities' Adherence to PI-RADS v2 Minimum Technical Standards for the Performance of Prostate MRI

This study aimed to assess variability in imaging facilities' adherence to the minimum technical standards for prostate magnetic resonance imaging acquisition established by Prostate Imaging-Reporting and Data System (PI-RADS) version 2 (v2). A total of 107 prostate magnetic resonance imaging examinations performed at 107 unique imaging facilities after the release of PI-RADS v2 and that were referred to a tertiary care center for secondary interpretation were included. Image sets, DICOM headers, and outside reports were reviewed to assess adherence to 21 selected PI-RADS v2 minimum technical standards. Hardware arrangements were 23.1%, 1.5T without endorectal coil; 7.7%, 1.5T with endorectal coil; 63.5%, 3T without endorectal coil; and 5.8%, 3T with endorectal coil. Adherence to minimum standards was lowest on T2 weighted imaging (T2WI) for frequency resolution ≤0.4 mm (16.8%) and phase resolution ≤0.7 mm (48.6%), lowest on diffusion-weighted imaging (DWI) for field of view (FOV) 120-220 mm (30.0%), and lowest on dynamic contrast-enhanced (DCE) imaging for slice thickness 3 mm (33.3%) and temporal resolution <10 s (31.5%). High b-value (≥1400 s/mm2) images were included in 58.0% (calculated in 25.9%). Adherence to T2WI phase resolution and DWI inter-slice gap were greater (P < .05) at 3T than at 1.5T. Adherence did not differ (P > .05) for any parameter between examinations performed with and without an endorectal coil. Adherence was greater for examinations performed at teaching facilities for T2WI slice thickness and DCE temporal resolution (P < .05). Adherence was not better for examinations performed in 2016 than in 2015 for any parameter (P > .05). Facilities' adherence to PI-RADS v2 minimum technical standards was variable, being particularly poor for T2WI frequency resolution and DCE temporal resolution. The standards warrant greater community education. Certain technical standards may be too stringent, and revisions should be considered.

Diffusion-Weighted Imaging and Proton Magnetic Resonance Spectroscopy Findings in Osteosarcoma Versus Normal Muscle

Objectives: The goal of our study was to assess diffusion-weighted (DW) imaging and proton magnetic resonance (MR) spectroscopy findings in osteosarcoma versus normal muscle at 3 Tesla (3 T) MR system. Patients and Methods: Nineteen patients highly suspicious for osteosarcoma and 12 normal young healthy adults were enrolled in this study. Two patients were excluded from the study due to incompatible histopathologic results. DW imaging and multivoxel proton MR spectroscopy at 3 T were performed for all participants. Surgical biopsy and histopathological examination were done for every patient after imaging. SPSS 20 was used for statistical analysis. Results: The minimum apparent diffusion coefficient (ADC) value of osteosarcoma (0.88 ± 0.28) in this study confirms the significant restriction of this tumor against the dark background of normal muscle in high b-value images. Fourteen (82%) of the available 17 patients had ADC values ≤ 1 × 10-3 mm2/s. The maximum choline/creatine (Cho/Cr) ratio of osteosarcoma (1.94 ± 1.12) was statistically higher than the normal muscle (1.34 ± 0.11). Receiver operating curve (ROC) analysis (the area under the curve = 0.7) indicated a maximum Cho/Cr ratio of 1.37 as the cut point between the normal muscle and osteosarcoma, with a sensitivity, specificity and accuracy of 58.8%, 83.3%, and 69%, respectively. All patients with Cho/Cr ratios more than the cut point had ADC values ≤ 1 × 10-3 mm2/s and all patients with ADC values higher than 1 × 10-3 mm2/s had Cho/Cr ratios ≤ 1.37. Conclusion: It was concluded that DW imaging and proton MR spectroscopy are two effective noninvasive techniques in the evaluation of osteosarcoma.

Repeated diffusion MRI reveals earliest time point for stratification of radiotherapy response in brain metastases

An imaging biomarker for early prediction of treatment response potentially provides a non-invasive tool for better prognostics and individualized management of the disease. Radiotherapy (RT) response is generally related to changes in gross tumor volume manifesting months later. In this prospective study we investigated the apparent diffusion coefficient (ADC), perfusion fraction and pseudo diffusion coefficient derived from diffusion weighted MRI as potential early biomarkers for radiotherapy response of brain metastases. It was a particular aim to assess the optimal time point for acquiring the DW-MRI scan during the course of treatment, since to our knowledge this important question has not been addressed directly in previous studies. Twenty-nine metastases (N = 29) from twenty-one patients, treated with whole-brain fractionated external beam RT were analyzed. Patients were scanned with a 1 T MRI system to acquire DW-, T2*W-, T2W- and T1W scans, before start of RT, at each fraction and at follow up two to three months after RT. The DW-MRI parameters were derived using regions of interest based on high b-value images (b = 800 s mm−2). Both volumetric and RECIST criteria were applied for response evaluation. It was found that in non-responding metastases the mean ADC decreased and in responding metastases it increased. The volume based response proved to be far more consistently predictable by the ADC change found at fraction number 7 and later, compared to the linear response (RECIST). The perfusion fraction and pseudo diffusion coefficient did not show sufficient prognostic value with either response assessment criteria. In conclusion this study shows that the ADC derived using high b-values may be a reliable biomarker for early assessment of radiotherapy response for brain metastases patients. The earliest response stratification can be achieved using two DW-MRI scans, one pre-treatment and one at treatment day 7–9 (equivalent to 21 Gy).

Squamous cell carcinoma of the oral cavity and oropharynx: what does the apparent diffusion coefficient tell us about its histology?

Background Diffusion-weighted imaging obtained with magnetic resonance (DW-MRI) is a non-invasive imaging tool potentially able to provide information about microstructural tumor characteristics. Purpose To prospectively analyze the correlation between the apparent diffusion coefficient (ADC) and clinical-histologic characteristics of squamous cell carcinoma (SCCA) of the oral cavity and oropharynx. Material and Methods Sixty-seven patients with untreated, histologically proven SCCA of the oral cavity and oropharynx underwent conventional and diffusion-weighted (b-values 0, 50, 250, 500, and 900 s/mm2) MRI. Tumor ADC was calculated from regions of interest drawn manually on the highest b-value images using ImageJ (ImageJ, NIH) and fsl (fsl 4, University of Oxford) image processing packages. ADC was calculated in two ways: standard ADC using all b-values; and ADCHigh using only b-values ≥ 250 s/mm2. We assessed the correlations between both ADC and ADCHigh and the clinical-histological characteristics of SCCA. Results Fifty-two patients (36 men, 16 women; mean age, 55 ± 13 years) were suitable for ADC calculation. Mean ADC was 1136.0 ± 108.5 × 10-6 mm2/s. Mean tumor ADCHigh was 991.2 ± 152.1 × 10-6 mm2/s. Mean tumor size was 32.3 ± 13.4 mm (range, 14.0-69.0 mm). We observed no correlation of either ADC or ADCHigh values with any of the clinical-histological tumor characteristics. Undifferentiated tumors (G3) showed lower apparent diffusion coefficient values compared to differentiated ones (G1-G2), without reaching statistical significance. Conclusion We did not observe any statistically significant correlation between ADC values and clinical-histological characteristics of SCCA of the oral cavity and oropharynx.

Predicting Prostate Biopsy Outcomes: A Preliminary Investigation on Screening with Ultrahigh B-Value Diffusion-Weighted Imaging as an Innovative Diagnostic Biomarker.

BackgroundRoutine screening of prostate specific antigen (PSA) is no longer recommended because of a high rate of over-diagnosis of prostate cancer (PCa).ObjectiveTo evaluate the efficacy of diffusion-weighted magnetic resonance imaging (DW-MRI) for PCa detection, and to explore the clinical utility of ultrahigh b-value DW-MRI in predicting prostate biopsy outcomes.Methodology73 male patients were selected for the study. They underwent 3T MRI using T2WI conventional DW-MRI with b-value 1000 s/mm2, and ultrahigh b-value DW-MRI with b-values of 2000 s/mm2 and 3000 s/mm2. Two radiologists evaluated individual prostate gland images on a 5-point rating scale using PI-RADS, for the purpose of region-specific comparisons among modalities. Sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV) and likelihood ratios (LR) were investigated for each MRI modality. The area under the receiver operating characteristic (ROC) curve (AUC) was also calculated.ResultsResults showed the improved diagnostic value of ultrahigh b-value DWI-MRI for detection of PCa when compared to other b values and conventional MRI protocols. Sensitivity values for 3000 s/mm2 in both peripheral zone (PZ) and transition zone (TZ) were significantly higher than those observed with conventional DW-MRI—Specificity values for 3000 s/mm2 in the TZ were significantly higher than other b-value images, whereas specificity values using 3000 s/mm2 in the PZ were not significantly higher than 2000 s/mm2 images. PPV and NPV between 3000 s/mm2 and the other three modalities were significantly higher for both PZ and TZ images. The PLRs and NLRs of b-value 3000 s/mm2 DW-MRI in the PZ and TZ were also recorded. ROC analysis showed greater AUCs for the b value 3000 s/mm2 DWI than for the other three modalities.ConclusionsDW-MRI with a b-value of 3000 s/mm2 was found to be the most accurate and reliable MRI modality for PCa tumor detection and localization, particularly for TZ lesion discrimination. It may be stated that the b-value of 3000 s/mm2 is a novel, improved diagnostic biomarker with greater predictive accuracy for PCa prior to biopsy.

Diffusion in prostate cancer detection on a 3T scanner: How many b-values are needed?

To assess the influence of perfusion on apparent coefficient diffusion (ADC) maps, the contribution of b-value images, and the number of b-values needed in prostate cancer detection by diffusion-weighted imaging (DWI). Patients scheduled for prostatectomy were scanned by 3T magnetic resonance imaging (MRI) with DWI based on b-values 0-500-1000-1500 s/mm(2) . A monoexponential model was fitted to obtain ADC using multiple b-values, with or without b0 (perfusion-sensitive ADC4b-b0-500-1000-1500 , perfusion-insensitive ADC3b-b500-1000-1500 ), or two b-values (ADC2b-b0-500 , ADC2b-b0-1000 , ADC2b-b0-1500 ). Prostate and cancer foci were segmented to label voxels as normal or tumoral, according to histology. Areas under receiver operating characteristic curves (AUC) were calculated for each ADC and b-value, then for multivariate logistic regression models combining them. A threshold of 85 tumoral voxels (=0.5 cm(3) ) was used to stratify AUC analysis. In all, 21 patients were selected. Segmentation collected 143,665 prostatic voxels including 10,069 tumoral voxels. In five patients, tumor segmentation provided fewer than 85 voxels, resulting in an ADC with AUC inferior to 0.52. In 16 patients with larger tumors, perfusion-sensitive ADC4b-b0-500-1000-1500 performed better than perfusion-insensitive ADC3b-b500-1000-1500 and similar to ADC2b-b0-1500 (AUC of 0.840, 0.809, and 0.838, respectively). In comparison to the ADC alone, models combining ADC4b-b0-500-1000-1500 or ADC2b-b0-1500 with b1500 improved performance, leading to similar AUCs of 0.884 and 0.883, respectively. In both models, ADC and b1500 were significant markers (P < 0.001). Including b0 in ADC calculation provided superior ADC maps for prostate cancer detection. b1500 images as a combined parameter with ADC also improved performance. Using more than two b-values showed no improvement. J. Magn. Reson. Imaging 2016;44:601-609.