DW-MR Images Research Articles

Added value of diffusion-weighted magnetic resonance imaging for the detection of pancreatic fluid collection infection.

To investigate the added value of diffusion-weighted (DW) magnetic resonance (MR) imaging in the detection of infection in pancreatic fluid collections (PFC). Forty-patients with PFC requiring endoscopic-transmural drainage underwent conventional-MR and DW-MR imaging (b = 1000s/mm2) before endoscopy. MR images were divided into two sets (set1, conventional-MR; set2, conventional-MR, DW-MR and ADC maps) and randomized. Two independent readers performed qualitative and quantitative (apparent diffusion coefficient, ADC) image analysis. Bacteriological analysis of PFC content was the gold standard. Non-parametric tests were used for comparisons. Sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV) and accuracy were calculated for the two sets for both readers. Receiver operating characteristic curves (ROC) were drawn to assess quantitative DW-MR imaging diagnostic performance. For both readers, sensitivity, specificity, NPV, PPV and accuracy for infected PFCs were higher for set2 (P > .05). ADC were lower in infected versus non-infected PFCs (P ≤ .031). Minimum ADC cut-off: 1,090×10-3 mm2/s for reader 1 and 1,012×10-3 mm2/s for reader 2 (sensitivity and specificity 67% and 96% for both readers). Qualitative information provided by DW-MR may help to assess PFCs infection. Infected PFCs show significantly lower ADCs compared to non-infected ones. • DW improves MR diagnostic accuracy to detect infection of PFC • Infected PFCs show lower ADC compared to non-infected ones (P < .031) • DW-MR images are easy to interpret especially for non-experienced radiologist.

A Population-Based Gaussian Mixture Model Incorporating 18F-FDG PET and Diffusion-Weighted MRI Quantifies Tumor Tissue Classes.

The aim of our study was to create a novel Gaussian mixture modeling (GMM) pipeline to model the complementary information derived from(18)F-FDG PET and diffusion-weighted MRI (DW-MRI) to separate the tumor microenvironment into relevant tissue compartments and follow the development of these compartments longitudinally. Serial (18)F-FDG PET and apparent diffusion coefficient (ADC) maps derived from DW-MR images of NCI-H460 xenograft tumors were coregistered, and a population-based GMM was implemented on the complementary imaging data. The tumor microenvironment was segmented into 3 distinct regions and correlated with histology. ANCOVA was applied to gauge how well the total tumor volume was a predictor for the ADC and (18)F-FDG, or if ADC was a good predictor of (18)F-FDG for average values in the whole tumor or average necrotic and viable tissues. The coregistered PET/MR images were in excellent agreement with histology, both visually and quantitatively, and allowed for validation of the last-time-point measurements. Strong correlations were found for the necrotic (r = 0.88) and viable fractions (r = 0.87) between histology and clustering. The GMM provided probabilities for each compartment with uncertainties expressed as a mixture of tissues in which the resolution of scans was inadequate to accurately separate tissues. The ANCOVA suggested that both ADC and (18)F-FDG in the whole tumor (P = 0.0009, P = 0.02) as well as necrotic (P = 0.008, P = 0.02) and viable (P = 0.003, P = 0.01) tissues were a positive, linear function of total tumor volume. ADC proved to be a positive predictor of (18)F-FDG in the whole tumor (P = 0.001) and necrotic (P = 0.02) and viable (P = 0.0001) tissues. The complementary information of (18)F-FDG and ADC longitudinal measurements in xenograft tumors allows for segmentation into distinct tissues when using the novel GMM pipeline. Leveraging the power of multiparametric PET/MRI in this manner has the potential to take the assessment of disease outcome beyond RECIST and could provide an important impact to the field of precision medicine.

Diffusion‐weighted MRI for early detection and characterization of prostate cancer in the transgenic adenocarcinoma of the mouse prostate model

To improve early diagnosis of prostate cancer to aid clinical decision-making. Diffusion-weighted magnetic resonance imaging (DW-MRI) is sensitive to water diffusion throughout tissues, which correlates with Gleason score, a histological measure of prostate cancer aggressiveness. In this study the ability of DW-MRI to detect prostate cancer onset and development was evaluated in transgenic adenocarcinoma of the mouse prostate (TRAMP) mice. T2 -weighted and DW-MRI were acquired using a 7T MR scanner, 200 mm bore diameter; 10 TRAMP and 6 C57BL/6 control mice were scanned every 4 weeks from 8 weeks of age until sacrifice at 28-30 weeks. After sacrifice, the genitourinary tract was excised and sectioned for histological analysis. Histology slides registered with DW-MR images allowed for validation of DW-MR images and the apparent diffusion coefficient (ADC) as tools for cancer detection and disease stratification. An automated early assessment tool based on ADC threshold values was developed to aid cancer detection and progression monitoring. The ADC differentiated between control prostate ((1.86 ± 0.20) × 10(-3) mm(2) /s) and normal TRAMP prostate ((1.38 ± 0.10) × 10(-3) mm(2) /s) (P = 0.0001), between TRAMP prostate and well-differentiated cancer ((0.93 ± 0.18) × 10(-3) mm(2) /s) (P = 0.0006), and between well-differentiated cancer and poorly differentiated cancer ((0.63 ± 0.06) × 10(-3) mm(2) /s) (P = 0.02). DW-MRI is a tool for early detection of cancer, and discrimination between cancer stages in the TRAMP model. The incorporation of DW-MRI-based prostate cancer stratification and monitoring could increase the accuracy of preclinical trials using TRAMP mice.

Diffusion-weighted magnetic resonance imaging during radiotherapy of locally advanced cervical cancer – treatment response assessment using different segmentation methods

ABSTRACTBackground. Diffusion-weighted magnetic resonance imaging (DW-MRI) and the derived apparent diffusion coefficient (ADC) value has potential for monitoring tumor response to radiotherapy (RT). Method used for segmentation of volumes with reduced diffusion will influence both volume size and observed distribution of ADC values. This study evaluates: 1) different segmentation methods; and 2) how they affect assessment of tumor ADC value during RT.Material and methods. Eleven patients with locally advanced cervical cancer underwent MRI three times during their RT: prior to start of RT (PRERT), two weeks into external beam RT (WK2RT) and one week prior to brachytherapy (PREBT). Volumes on DW-MRI were segmented using three semi-automatic segmentation methods: “cluster analysis”, “relative signal intensity (SD4)” and “region growing”. Segmented volumes were compared to the gross tumor volume (GTV) identified on T2-weighted MR images using the Jaccard similarity index (JSI). ADC values from segmented volumes were compared and changes of ADC values during therapy were evaluated.Results. Significant difference between the four volumes (GTV, DWIcluster, DWISD4 and DWIregion) was found (p < 0.01), and the volumes changed significantly during treatment (p < 0.01). There was a significant difference in JSI among segmentation methods at time of PRERT (p < 0.016) with region growing having the lowest JSIGTV (mean± sd: 0.35 ± 0.1), followed by the SD4 method (mean± sd: 0.50 ± 0.1) and clustering (mean± sd: 0.52 ± 0.3). There was no significant difference in mean ADC value compared at same treatment time. Mean tumor ADC value increased significantly (p < 0.01) for all methods across treatment time.Conclusion. Among the three semi-automatic segmentations of hyper-intense intensities on DW-MR images implemented, cluster analysis and relative signal thresholding had the greatest similarity to the clinical tumor volume. Evaluation of mean ADC value did not depend on segmentation method.

Intrahepatic and hilar mass-forming cholangiocarcinoma: Qualitative and quantitative evaluation with diffusion-weighted MR imaging

ObjectiveTo qualitatively and quantitatively analyze the presentation of intrahepatic and hilar mass-forming cholangiocarcinoma with diffusion-weighted magnetic resonance imaging (DW-MRI). Materials and methodsTwenty-eight patients with histopathologically proven mass-forming cholangiocarcinoma (hilar, n=17; intrahepatic, n=11) underwent hepatic DW-MRI at 1.5-T using free-breathing acquisition and three b-values (0,400,800s/mm2). Cholangiocarcinomas were evaluated qualitatively using visual analysis of DW-MR images and quantitatively with conventional ADC and normalized ADC measurements using liver and spleen as reference organs. ResultsAll cholangiocarcinomas (28/28; 100%) were visible on DW-MR images. DW-MRI yielded best conspicuity of cholangiocarcinomas than the other MRI sequences (P<0.001). Seven cholangiocarcinomas (7/11; 64%) showed hypointense central area on DW-MR images. Conventional ADC value of cholangiocarcinomas (1.042×10−3mm2/s±0.221×10−3mm2/s; range: 0.616×10−3mm2/s to 2.050×10−3mm2/s) was significantly lower than that of apparently normal hepatic parenchyma (1.362×10−3mm2/s±0.187×10−3mm2/s) (P<0.0001), although substantial overlap was found. No significant differences in ADC and normalized ADC values were found between intrahepatic and hilar cholangiocarcinomas. The use of normalized ADC using the liver as reference organ resulted in the most restricted distribution of ADC values of cholangiocarcinomas (variation coefficient=16.6%). ConclusionThere is a trend towards a common appearance of intrahepatic and hilar mass-forming cholangiocarcinomas on DW-MRI but variations may be observed. Familiarity with these variations may improve the diagnosis of mass-forming cholangiocarcinoma.

The added value of PET/Ce-CT/DW-MRI fusion in assessment of hepatic focal lesions: PET/Ce-CT/DW-MRI fusion in hepatic focal lesion

IntroductionThe liver hosts a variety of benign and malignant tumors. Accurate diagnosis can be challenging in certain cases, especially in patients with a history of malignancy or in those with underlying liver pathology, such as cirrhosis. ObjectivesTo evaluate the added clinical value of multi-modality liver imaging utilizing PET/Ce-CT/DW-MRI for characterization of hepatic focal lesions (HFL) and compare it with each diagnostic modality when interpreted alone. MethodsThe study included 35 patients with HFL. They were 7 females & 28 males; their age ranged from 41 to 78years, all patients underwent PET/Ce-CT and DW-MRI scans. Ce-CT, PET and DW-MR images were reviewed independently, and then combined PET/Ce-CT, PET/DW-MRI and PET/Ce-CT/DW-MRI scans were analyzed. The results were correlated with histopathology or clinical/imaging follow-up. ResultsThe 35 patients had 98 focal lesions. Fifty-three lesions were finally diagnosed as primary hepatocellular carcinoma, 18 lesions were metastases, 7 lesions were lymphoma and 20 lesions were benign. On a patient based analysis; the sensitivity, specificity, PPV, NPV and accuracy were 100%, 67%, 94%, 100% and 94% for PET/Ce-CT compared to 97%, 83%, 97%, 83% and 94 % for DW-MRI, respectively. Combined PET/Ce-CT/DW-MR scans raise those parameters up to 100%. On a lesion based analysis; the sensitivity, specificity, PPV, NPV and accuracy were 94%, 75%, 94%, 75%, 90% for PET/Ce-CT compared to 94%, 95%, 99%, 97% and 94 % for DW-MRI, respectively. All these parameters were 100 % with PET/Ce-CT/DW-MRI. ConclusionsThe addition of DW-MRI to PET/Ce-CT is valuable in the characterization of hepatic focal lesions.

Diagnostic efficacy of diffusion-weighted MRI for pre-operative assessment of myometrial and cervical invasion and pelvic lymph node metastasis in endometrial carcinoma.

To determine the diagnostic accuracy of diffusion-weighted magnetic resonance imaging (DW-MRI) for the pre-operative assessment of patients with endometrial carcinoma and to assess myometrial and cervical invasion as well as pelvic lymph node metastasis. Fifty-eight women who underwent surgery for histopathologically confirmed endometrial carcinoma were included in the current study. Prior to surgery, patients were evaluated using pelvic DW-MRI and gadolinium-enhanced T1-weighted imaging (Gd-T1WI). Gd-T1WI was evaluated together with T2-weighted images. DW-MR images were obtained in the axial plane using echo-planar spin-echo pulse sequences with different b factors. Endometrial carcinomas were observed as areas of increased intensity on DW-MRI images, and their intensity was compared with the surrounding hypo-intense myometrium. Pre-operative DW-MRI and Gd-T1WI results were compared with post-operative histopathological findings that served as reference standards. The sensitivity, specificity, positive (PPV) and negative predictive values (NPV), and diagnostic accuracy of DW-MRI for differentiation between superficial myometrial invasion and deep myometrial invasion were 85%, 89%, 81%, 92% and 88%, respectively. The sensitivity, specificity and diagnostic accuracy rates were 82%, 91% and 89.6% for cervical invasion and 100%, 96% and 96.5% for pelvic lymph node metastasis, respectively. The sensitivity, specificity, PPV and NPV, and diagnostic accuracy of Gd-T1WI for differentiation between superficial myometrial invasion and deep myometrial invasion were 85%, 81.5%, 71%, 91% and 83%, respectively. The sensitivity, specificity and diagnostic accuracy were 73%, 89% and 86% for cervical invasion, respectively. These findings suggest that DW-MRI may be a good diagnostic tool with high sensitivity and specificity for assessing myometrial invasion and detecting tumour extension. We suggest that DW-MRI should be considered as a routine part of the pre-operative pelvic MRI in all patients with endometrial carcinoma.

Diffusion-weighted MRI of metastatic liver lesions: is there a difference between hypervascular and hypovascular metastases?

Different perfusion characteristics and histopathologic features of liver metastasis may potentially lead to different diffusion-weighted magnetic resonance imaging (DW-MRI) characteristics which can affect the performance of DW-MRI in their diagnosis. To compare ADC values of hypervascular and hypovascular metastases and the added value of DW-MRI to T2-weighted (T2-w) images in their detection. In this retrospective study, 46 patients (21 with hypervascular, 25 with hypovascular liver metastases) who had undergone abdominal MRI were included. Two independent observers first reviewed T2-w images only and then T2-w+DW-MR images and recorded number of metastases in each session. Lesion detection rate was compared using McNemar test. ADC of metastases in each patient was measured and compared between hypo- and hypervascular lesions using t-test. A total of 153 hypervascular and 187 hypovascular metastases were detected at consensus review. Two observers detected significantly more hypervascular metastases on T2-w+DW-MR image review session compared to T2-w image only review session (reader 1: 148 [96.7%] vs. 129 [84.3%], P=0.002; reader 2: 125 [81.9%] vs. 113 [73.8%], P=0.004). Detection rate of hypovascular metastases was similar between two sessions for both observers (reader 1: 180 [96.2%] vs. 184 [98.4%]; reader 2: 176 [94.1%] vs. 180 [96.2%], P>0.05). The mean ADC value of hypervascular metastases was significantly lower than mean ADC value of hypovascular metastases (1.23+/-0.31 × 10(-3)mm(2)/s vs. 1.49+/-0.19 × 10(-3)mm(2)/s) (P=0.001). Liver metastases are not a homogenous group of lesions with uniform DW-MRI features. Hypervascular metastases demonstrate significantly lower ADC values compared to hypovascular metastases. DW-MRI improved detection of hypervascular metastases compared to T2-w images alone and is a useful adjunct to T2-w images for their detection.

The role of multi-parametric MR imaging in the detection of early inflammatory sacroiliitis according to ASAS criteria

PurposeTo retrospectively evaluate the accuracy of multi-parametric magnetic resonance (MR) imaging including fat saturated (FS) T2-weighted, short-tau inversion recovery (STIR), diffusion-weighted (DW-MR), and dynamic-contrast-enhanced MR (DCE-MR) imaging techniques in the diagnosis of early inflammatory sacroiliitis and determine the additional value of DW-MR and DCE-MR images according to recently defined ‘Assessment in SpondyloArthritis international Society’ criteria. Materials and methodsThe study included 45 patients with back pain. Two radiologists estimated the likelihood of osteitis in 4 independent viewing sessions including FS T2-weighted, STIR, DW-MR and DCE-MR images. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic (ROC) curve (AUC) were calculated. ResultsOf the 45 patients, 31 had inflammatory back pain. Of 31, 28 (90.3%) patients had inflammatory sacroiliitis diagnosed by clinical and laboratory analysis. FS T2-weighted MR images had the highest sensitivity (42.8% for both radiologists) for detecting osteitis in patients with inflammaory sacroiliitis when compared to other imaging sequences. For specificity, PPV, NPV, accuracy, and AUC levels there were no statistically significant difference between image viewing settings. However, adding STIR, DW-MR and DCE-MR images to the FS T2-weighted MR images did not improve the above stated indices. ConclusionFS T2-weighted MR imaging had the highest sensitivity when compared to other imaging sequences. The addition of DW-MR and DCE-MR images did not significantly improve the diagnostic value of MR imaging in the diagnosis of osteitis for both experienced and less experienced radiologists.

Automatic Bone Segmentation in Pelvis Area with Bone Marrow Metastases; Applications in Breast Cancer Treatment Monitoring

Background: In bone marrow metastatic cancers, therapy goals are delay skeletal-related events, reduce symptoms, improve patients life quality and increase their survival. Correct knowledge about patients bone state in shortest possible time is the key to achieve therapy goals. Therefore, several quantitative analyses of MR images have been used, in which accurate segmentation of the bone plays a vital role. Due to heterogeneous nature of tumors and presence of cystic or necrotic areas, correct separation of the overall border of bone is difficult, creating source of error for the quantitative analysis results. Diffusion-weighted (DW) MR images are capable of revealing information of bone status, showing applications in skeletal related diseases. The poor anatomy available in these images gears them toward anatomical MR images such as T1-wighted (T1-w) images. However, boundary distortion created by bone metastasis hierarchically affects information extracted from DW-MR images. Commonly used bone segmentation methods are applicable on healthy bone structures, while they partly fail in presence of bone metastasis, especially in advanced situations. Objectives: In this study, we proposed an automatic method to extract pelvis bone from T1-w images in the presence of bone marrow metastasis. This method eliminates manual segmentation variability, resulting reproducible quantitative analysis independent of human error. We also investigated clinical quantitative analyses variations caused by miss-segmentation of the bone due to the bone marrow metastasis, and how our proposed method eliminates such errors. Patients and Methods: Pelvis images of ten female patients, with metastatic bone marrow breast cancer under treatment, were carried out on 1.5T MR with the following specifications: TR/TE = 171/4.76 ms, FOV = 430 430, slice thickness = 5 mm, spaces between slices = 5.5 mm. Whole-body DW images acquired using GE-EPI sequence with the following specifications: TR/TE = 5540/102 ms, percent phase FOV =430430, slice thickness=5 mm, spaces between slices = 5.5 mm, at b-value = 50, 900 sec/mm2. ADC-maps were then calculated from DW images. Image processing and analysis: Image processing consisted of the following steps: 1) automatic non-rigid registration of T1w MR images with the ADC-maps with SPM8 software; 2) segmentation of bone in each T1-w image using local level-set with prior information algorithm, implemented in MATLAB; 3) using result of step 2 as a mask, for bone extraction from corresponding DW-MR images such as ADC-map. In order to show the applicability of the automatic segmentation-based analysis, its performance in ADC-map analysis was compared to manual-based analysis methods. Results: An example of bone structure was illustrated which was diminished due to bone marrow metastasis. Registration and segmentation procedure leads to bone structure extraction regardless of the disease, providing an efficient and accurate bone study. In order to exhibit the variation of information extracted from DW-MR images based on ROI selection, three common parameters extracted from ADC-map based on manual segmentation (performed by 10 different unbiased observers) against parameters extracted based on proposed automatic segmentation method, suggesting significant differences in analysis results. Automatic segmentation accuracy has been evaluated using boundary-based (Hausdorff parameter, result: 5.55 + 1.4) and volume-based (Dice, result: 83% + 0.06 and sensitivity parameter, result: 81% + 0.08) measures. Performance of proposed method was quantitatively evaluated, comparing its performance with two commonly used different methods, in terms of segmentation accuracy. The proposed method is superior to the other two methods with Dice values of 76% and 67%, respectively. Conclusions: In conclusion, the proposed automatic algorithm has promising results in bone segmentation and in the presence of bone marrow metastasis. This method is accurate and robust, which improves the design of the patients treatment plan and provides the opportunity for accurate high profile analyses. This segmentation is a significant step towards accurate information extraction and therefore, applicable usage of DW-MRI images in bone marrow metastatic cancers, bringing consistency and reproducibility to the extracted information.

Comparison of apparent diffusion coefficient values among different MRI platforms: a multicenter phantom study

We aimed to compare apparent diffusion coefficient (ADC) values among magnetic resonance imaging (MRI) scanners from different vendors. We used a custom-made phantom solution consisting of distilled water, 0.9% NaCl, 25% NaCl, and shampoo for diffusion-weighted MRI (DW-MRI) examinations. DW-MRI was performed with similar sequence parameters using six different 1.5 Tesla MR scanners (scanners A-F). ADC maps were automatically constructed for all DW-MR images (b factors of 0 and 1000 s/mm(2)). ADC measurements were performed using regions of interest and seven different software programs, including four different postprocessing workstations, two different picture archiving and communication systems, and operator console software for each MR scanner. The ADC values generated by scanners A and F were higher and those of scanner B were lower than those generated by the other scanners (P = 0.002). The intravendor difference in the ADC values averaged from scanners D, E, and F was statistically significant (P < 0.001). The difference between the ADC values obtained by scanners C and E was not statistically different (P = 0.15). ADC values may differ among different MRI systems used for DW-MRI. Thus, the MRI vendor should be considered when using DW-MRI in a clinical setting.

Locally advanced rectal cancer: diffusion-weighted MR tumour volumetry and the apparent diffusion coefficient for evaluating complete remission after preoperative chemoradiation therapy

To evaluate DW MR tumour volumetry and post-CRT ADC in rectal cancer as predicting factors of CR using high b values to eliminate perfusion effects. One hundred rectal cancer patients who underwent 1.5-T rectal MR and DW imaging using three b factors (0, 150, and 1,000 s/mm(2)) were enrolled. The tumour volumes of T2-weighted MR and DW images and pre- and post-CRT ADC150-1000 were measured. The diagnostic accuracy of post-CRT ADC, T2-weighted MR, and DW tumour volumetry was compared using ROC analysis. DW MR tumour volumetry was superior to T2-weighted MR volumetry comparing the CR and non-CR groups (P < 0.001). Post-CRT ADC showed a significant difference between the CR and non-CR groups (P = 0.001). The accuracy of DW tumour volumetry (Az = 0.910) was superior to that of T2-weighed MR tumour volumetry (Az = 0.792) and post-CRT ADC (Az = 0.705) in determining CR (P = 0.015). Using a cutoff value for the tumour volume reduction rate of more than 86.8 % on DW MR images, the sensitivity and specificity for predicting CR were 91.4 % and 80 %, respectively. DW MR tumour volumetry after CRT showed significant superiority in predicting CR compared with T2-weighted MR images and post-CRT ADC.

Abstract 4066: Early assessment of the XL184 treatment by Diffusion-Weighted MRI in metastatic prostate cancer to the bone murine model

Abstract Ninety percent of patients with advanced prostate cancer develop metastases to the bone1. At present, there is no definitive means for assessing response to therapy, with RECIST identifying tumors in the bone as “unmeasureable”. Cabozantinib (XL184) is an oral small molecular pan-tyrosine kinase inhibitor of primarily MET and vascular endothelial growth factor receptor 2 (VEGFR2). MET is known to play key roles in cellular proliferation, migration and invasion, which contribute to the survival and metastasis of cancer cells. XL184 is already in Phase 2 trials to evaluate the therapeutic benefit on castration-resistant prostate cancer metastatic to the bone. Diffusion-weighted MRI (DW-MRI) is highly sensitive to microscopic changes in tumor tissue. Our goal was to evaluate DW-MRI for detection and quantification of changes in tumor tissue following one-week XL184 treatment. MR experiments were performed on a 9.4T MRI. Human prostate cancer (PC3) cells were implanted by direct intra-tibial injection into male SCID mice, which serves as a model for prostate bone metastases2. Upon measuring tumor volume of ∼10mm3 on anatomical scans, mice were distributed into 2 groups: XL184 at 30 mg/kg (N=7) and vehicle (N=5). Treatments were delivered by oral gavage once a day for 7 days. DW-MRI was performed at days 0 (pre-treatment), 1, 4, 7, 11, 14 and twice a week after. Apparent diffusion coefficient (ADC) maps were calculated analytically from DW-MR images acquired at b-value 120 and 1200 s/mm2. End point of the study was when tumor volume reached 5x the initial measure. Unpaired Student t-test was performed to compare MRI metrics. XL184 treated mice had smaller tumor volume growth rate than control mice. Significant differences in tumor volume were not observed until 14 days post-treatment initiation (p&amp;lt;0.05). In contrast, significantly higher ADC values (p&amp;lt;0.0.5) for the treated group compared to control were observed at day 7. These results demonstrate the use of DW-MRI as a early biomarker of tumor response to XL184 in a metastatic prostate cancer tumor model. DW-MRI may serve as a surrogate endpoint for assessing patient response to treatment in clinical trials.

Semiautomated spleen volumetry with diffusion‐weighted MR imaging

In this article, we determined the relative accuracy of semiautomated spleen volumetry with diffusion-weighted (DW) MR images compared to standard manual volumetry with DW-MR or CT images. Semiautomated spleen volumetry using simple thresholding followed by 3D and 2D connected component analysis was performed with DW-MR images. Manual spleen volumetry was performed on DW-MR and CT images. In this study, 35 potential live liver donor candidates were included. Semiautomated volumetry results were highly correlated with manual volumetry results using DW-MR (r = 0.99; P < 0.0001; mean percentage absolute difference, 1.43 ± 0.94) and CT (r = 0.99; P < 0.0001; 1.76 ± 1.07). Mean total processing time for semiautomated volumetry was significantly shorter compared to that of manual volumetry with DW-MR (P < 0.0001) and CT (P < 0.0001). In conclusion, semiautomated spleen volumetry with DW-MR images can be performed rapidly and accurately when compared with standard manual volumetry.

Predictive validity of MRI in detecting and following cholesteatoma

High recurrence rate of the middle ear cholesteatoma requires regular postoperative follow-up. This study evaluated data from the patients investigated with DW MRI to ascertain (1) the strength of the technique in detecting primary, and residual recurrent cholesteatoma, and (2) its accuracy in differentiating cholesteatoma from postoperative tissue changes. The diagnostic accuracy of two different DW imaging (EPI and non-EPI) techniques was evaluated. The data have been collected prospectively from 33 consecutive patients with either primary cholesteatoma, or with suspicious symptoms for potential cholesteatoma recurrence. The findings from non-EPI (HASTE) DW MR and EPI DW MR images were blindly compared with those obtained during a primary or secondary surgery. Preoperative non-EPI (HASTE) DWI pointed to a cholesteatoma in 25 out of 33 patients. In this subgroup, cholesteatoma were confirmed also by the surgery. In five cases, the non-EPI (HASTE) DWI did not show a cholesteatoma in the temporal bone, which agreed with the surgical findings. Three misclassifications were made by non-EPI (HASTE) DWI, all in the subgroup of patients indicated for primary surgery. The resulting pooled sensitivity of non-EPI (HASTE) DW imaging for diagnosing cholesteatoma in our study amounted to 96.15% (95% confidence interval (CI) 80.36-99.9), specificity was 71.43% (95% CI 29.04-96.33). Positive predictive value was 92.59% (95% CI 75.71-99.09) and negative predictive value 83.33% (95% CI 35.88-99.58). In conclusion, we recommend the non-EPI (HASTE) DW MRI as a valid method for diagnosing cholesteatoma and follow-up after cholesteatoma surgery.

Whole-body diffusion-weighted MR imaging with fat suppression by using STIR: Clinical utility for detection of primary malignancies in patients initially presented with metastasis

Purpose The purpose of this study was to prospectively evaluate the usefulness of DW MR imaging with fat suppression by using short time inversion recovery (STIR) to detect primary malignancies for patients initially presented with metastasis by direct visual assessment. Materials and methods Twenty-nine consecutive patients presented with metastatic lesions were included in this study and underwent whole-body DW MR imaging for detection of the primary malignancies. Twenty-five healthy volunteers were included in this study as control subjects. Whole-body DW MR imaging was conducted with a multi-stack pulse sequence and two b values of 0 and 600 s/mm 2 and a coverage from head to knees. Three radiologists reviewed the whole-body DW MR images independently to detect the primary malignancies. Receiver operating characteristic (ROC) analysis was used to assess the overall accuracy of this imaging technique in direct visual detection of primary malignancies. Inter-observer agreement was assessed by using kappa analysis. Results For 82.8% (24/29) of the patients, primary malignancies were correctly identified with this whole-body DW MR imaging, and subsequently confirmed by biopsy and/or pathology. While for 17.2% (5/29) of patients, no definite primary malignancy was identified. ROC analysis yielded Az values of 0.907, 0.914, and 0.910 for the three reviewers, respectively. The sensitivity and specificity was 82.8% (24/29) and 100% (25/25) for the three viewers. The inter-observer agreement between each pair of reviewer was 0.935, 0.804, and 0.873, respectively. Conclusion For patients originally presented with metastases, whole-body DW MR imaging might have potential utility in detecting primary malignancies.

Artificial Neural Networks for Prediction of Response to Chemoradiation in HT29 Xenografts

To evaluate the feasibility of using neural networks for predicting treatment response by using longitudinal measurements of apparent diffusion coefficient (ADC) obtained from diffusion-weighted magnetic resonance imaging (DWMRI). Mice bearing HT29 xenografts were allocated to six treatment groups receiving different combinations of daily chemotherapy and/or radiation therapy for 2 weeks. T(2)-weighted and DWMR images were acquired before treatment, twice during fractionated chemoradiation (at days 4 and 11), and four times after treatment ended (at days 18, 25, 32, and 46). A tumor doubling growth delay (T(delay)) value was found for individual xenografts. ADC values and treatment groups (1-6) were used as input to a back propagation neural network (BPNN) to predict T(delay). When treatment group and ADC values from days 0, 4, 11, 18, 25, 32, and 46 were used as inputs to the BPNN, a strong correlation between measured and predicted T(delay) values was found (R = 0.731, p < 0.01). When ADC values from days 0, 4, and 11, and the treatment group were used as inputs, the correlation between predicted and measured T(delay) was 0.693 (p < 0.01). BPNN was successfully used to predict T(delay) from tumor ADC values obtained from HT29 xenografts undergoing fractionated chemoradiation therapy.

Dialectical multispectral classification of diffusion-weighted magnetic resonance images as an alternative to apparent diffusion coefficients maps to perform anatomical analysis

Multispectral image analysis is a relatively promising field of research with applications in several areas, such as medical imaging and satellite monitoring. A considerable number of current methods of analysis are based on parametric statistics. Alternatively, some methods in computational intelligence are inspired by biology and other sciences. Here we claim that philosophy can be also considered as a source of inspiration. This work proposes the objective dialectical method (ODM): a method for classification based on the philosophy of praxis. ODM is instrumental in assembling evolvable mathematical tools to analyze multispectral images. In the case study described in this paper, multispectral images are composed of diffusion-weighted (DW) magnetic resonance (MR) images. The results are compared to ground-truth images produced by polynomial networks using a morphological similarity index. The classification results are used to improve the usual analysis of the apparent diffusion coefficient map. Such results proved that gray and white matter can be distinguished in DW-MR multispectral analysis and, consequently, DW-MR images can also be used to furnish anatomical information.

A software tool to generate simulated white matter structures for the assessment of fibre-tracking algorithms

The assessment of Diffusion-Weighted MRI (DW-MRI) fibre-tracking algorithms has been limited by the lack of an appropriate ‘gold standard’. Practical limitations of alternative methods and physical models have meant that numerical simulations have become the method of choice in practice. However, previous numerical phantoms have consisted of separate fibres embedded in homogeneous backgrounds, which do not capture the true nature of white matter. In this paper we describe a method that is able to randomly generate numerical structures consisting of densely packed bundles of fibres, which are much more representative of human white matter, and simulate the DW-MR images that would arise from them under many imaging conditions. User-defined parameters may be adjusted to produce structures with a range of complexities that spans the levels we would expect to find in vivo. These structures are shown to contain many different features that occur in human white matter and which could confound fibre-tracking algorithms, such as tract kissing and crossing. Furthermore, combinations of such features can be sampled by the random generation of many different structures with consistent levels of complexity. The proposed software provides means for quantitative assessment via direct comparison between tracking results and the exact location of the generated fibres. This should greatly improve our understanding of algorithm performance and therefore prove an important tool for fibre tracking development.

Human cerebral cortices: signal variation on diffusion-weighted MR imaging

We have often encountered high signal intensity (SI) of the cingulate gyrus and insula during diffusion-weighted magnetic resonance imaging (DW-MRI) on neurologically healthy adults. To date, cortical signal heterogeneity on DW images has not been investigated systematically. The purpose of our study was to determine whether there is regional signal variation in the brain cortices of neurologically healthy adults on DW-MR images. The SI of the cerebral cortices on DW-MR images at 1.5 T was evaluated in 50 neurologically healthy subjects (34 men, 16 women; age range 33-84 years; mean age 57.6 years). The cortical SI in the cingulate gyrus, insula, and temporal, occipital, and parietal lobes was graded relative to the SI of the frontal lobe. Contrast-to-noise ratios (CNRs) on DW-MR images were compared for each cortical area. Diffusion changes were analyzed by visually assessment of the differences in appearance among the cortices on apparent diffusion coefficient (ADC) maps. Increased SI was frequently seen in the cingulate gyrus and insula regardless of patient age. There were no significant gender- or laterality-related differences. The CNR was significantly higher in the cingulate gyrus and insula than in the other cortices (p< .01) , and significant differences existed among the cortical regions (p< .001). There were no apparent ADC differences among the cortices on ADC maps. Regional signal variation of the brain cortices was observed on DW-MR images of healthy subjects, and the cingulate gyrus and insula frequently manifested high SI. These findings may help in the recognition of cortical signal abnormalities as visualized on DW-MR images.