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Diffusion-weighted imaging (DWI) utilizing maximum-intensity projection (MIP) was suggested as a cost-effective alternative tool without the risk of gadolinium-based contrast agents. The purpose of this study was to investigate whether DWI MIPs played a supportive role in young (≤60) patients with marked background parenchymal enhancement (BPE) on contrast-enhanced MRI (CE-MRI). The research included 1303 patients with varying degrees of BPE, and correlations between BPE on CE-MRI, the background diffusion signal (BDS) on DWI, and clinical parameters were analyzed. Lesion detection scores were compared between CE-MRI and DWI, with DWI showing higher scores. Among the 186 lesions in 181 patients with marked BPE on CE-MRI, the main lesion on MIPs of CE-MRI was partially or completely seen in 88.7% of cases, while it was not seen in 11.3% of cases. On the other hand, the main lesion on MIPs of DWI was seen in 91.4% of cases, with only 8.6% of cases showing no visibility. DWI achieved higher scores for lesion detection compared to CE-MRI. The presence of a marked BDS was significantly associated with a lower likelihood of a higher DWI score (p < 0.001), and non-mass lesions were associated with a decreased likelihood of a higher DWI score compared with mass lesions (p = 0.196). In conclusion, the inclusion of MIPs of DWI in the preoperative evaluation of breast cancer patients, particularly young women with marked BPE, proved highly beneficial in improving the overall diagnostic process. [ABSTRACT FROM AUTHOR]

Abstract Background In the scenario of lung lesions, the differential diagnosis is important, since the treatment is determined by the characteristics of the lesion. The goal in the evaluation of pulmonary lesions is to distinguish malignant lesions from benign lesions in a non-invasive manner as possible. Since, CT is not sufficient to accurately distinguish malignant nodules from benign nodules and patients with benign nodules might undergo invasive diagnostic methods, such as lung biopsy or video-assisted thoracoscopic surgery, to rule out a malignancy. Now, MRI performed by using diffusion-weighted (DW) can offer both qualitative and quantitative information that can be helpful for tumour assessment. Moreover, lesion‐to‐spinal cord signal intensity ratio (LSR) has also been shown to be useful for the differentiation of lung lesions. Quantitative tumour assessment is possible by the calculation of ADC. Results A total of 30 patients were eligible for inclusion in our final analysis; with male/female case number about 10/20 (33.3%/ 66.7%) and age range from 20 to 74 (46.8 ± 14.9) were subjected to MRI study and MRI diffusion. Sensitivity analysis showed that ADC mean, and ADC min value can significantly predict malignant lung lesions using cutoff point 502.8, with sensitivity 92.9% and specificity 68.7%, AUC 89.3% and p value 0.0001. Lesion-to-spinal cord signal intensity ratio (LSR) can significantly predict malignant lung lesions using cutoff point > 1.3, with sensitivity 85.7% and specificity 75%, AUC 79.7% and p value 0.006. Conclusions This study confirmed that the DWI combined with ADC value and LSR is effective and valuable tool in differentiation of pulmonary lesions whether benign or malignant which is considered to be noninvasive alternative tool for the characterization of pulmonary lesions. We recommend before invasive intervention to perform diffusion MRI and LSR as and important aid for proper diagnosis.

Background: Surgical exploration and histologic evaluation are often required to determine the nature of the ovarian tumors being benign or malignant. Therefore, it may be impossible to determine beforehand whether minimally invasive or extensive surgery is required. Better preoperative planning might be accomplished with the use of a trustworthy approach that could distinguish malignant and benign masses. MRI is beneficial for identifying ovarian masses and their origins due to its sensitivity and improved characters by the application of diffusion-weighted imaging. This research aimed to assess the characterization of ovarian lesions using MRI with DWI.Methods: Forty patients diagnosed to have ovarian masses were evaluated in this cross-sectional analytical study after being referred to the University Hospital at the radiology department. All patients were exposed to pelvic MRI with DWI, and 7 underwent DWIBS. Surgery was performed with pathologic correlation on 39 individuals. Only one patient was given a 3-month course of routine US monitoring.Results: MRI's sensitivity was 99.9 percent, whereas DWI's was one hundred percent. When comparing DWI with traditional MRI, the former has a greater specificity (78.1%) while the latter has a better accuracy (86.0%). On average, malignant lesions had an ADC of (0.93x 10-3 ± 0.43 SD mm2/s), whereas benign ones had 1.3 x 10-3 ± 0.6 SD mm2/s with a p-value = 0.005. Because of the teratoma's mixed cellularity, mature teratomas exhibited restricted diffusion with ADC values of 0.5x10-3mm2/s (false positive).Conclusion: The specificity of conventional MRI was enhanced when combined with DWI, boosting radiologist confidence in picture interpretation and, in turn, improving patients' outcomes and prognoses.

Background: In the scenario of lung lesions, the differential diagnosis is important, since the treatment is determined by the characteristics of the lesion. The goal in the evaluation of pulmonary lesions is to distinguish malignant lesions from benign lesions in a non-invasive manner as possible. Since, CT is not sufficient to accurately distinguish malignant nodules from benign nodules and patients with benign nodules might undergo invasive diagnostic methods, such as lung biopsy or video-assisted thoracoscopic surgery, to rule out a malignancy. Now, MRI performed by using diffusion-weighted (DW) can offer both qualitative and quantitative information that can be helpful for tumour assessment. Moreover, lesion‐to‐spinal cord signal intensity ratio (LSR) has also been shown to be useful for the differentiation of lung lesions. Quantitative tumour assessment is possible by the calculation of ADC. Results: A total of 30 patients were eligible for inclusion in our final analysis; with male/female case number about 10/20 (33.3%/ 66.7%) and age range from 20 to 74 (46.8 ± 14.9) were subjected to MRI study and MRI diffusion. Sensitivity analysis showed that ADC mean, and ADC min value can significantly predict malignant lung lesions using cutoff point < 1.53 and < 1.34 respectively, with sensitivity 75%, 56.3%, and specificity 92.9%, 100% with p values 0.001, and 0.005 respectively. SI lesion can significantly predict malignant lung lesions using cutoff point > 502.8, with sensitivity 92.9% and specificity 68.7%, AUC 89.3% and p value 0.0001. Lesion-to-spinal cord signal intensity ratio (LSR) can significantly predict malignant lung lesions using cutoff point > 1.3, with sensitivity 85.7% and specificity 75%, AUC 79.7% and p value 0.006. Conclusions: This study confirmed that the DWI combined with ADC value and LSR is effective and valuable tool in differentiation of pulmonary lesions whether benign or malignant which is considered to be noninvasive alternative tool for the characterization of pulmonary lesions. We recommend before invasive intervention to perform diffusion MRI and LSR as and important aid for proper diagnosis. [ABSTRACT FROM AUTHOR]

Diffusion-weighted imaging (DWI) utilizing maximum-intensity projection (MIP) was suggested as a cost-effective alternative tool without the risk of gadolinium-based contrast agents. The purpose of this study was to investigate whether DWI MIPs played a supportive role in young (≤60) patients with marked background parenchymal enhancement (BPE) on contrast-enhanced MRI (CE-MRI). The research included 1303 patients with varying degrees of BPE, and correlations between BPE on CE-MRI, the background diffusion signal (BDS) on DWI, and clinical parameters were analyzed. Lesion detection scores were compared between CE-MRI and DWI, with DWI showing higher scores. Among the 186 lesions in 181 patients with marked BPE on CE-MRI, the main lesion on MIPs of CE-MRI was partially or completely seen in 88.7% of cases, while it was not seen in 11.3% of cases. On the other hand, the main lesion on MIPs of DWI was seen in 91.4% of cases, with only 8.6% of cases showing no visibility. DWI achieved higher scores for lesion detection compared to CE-MRI. The presence of a marked BDS was significantly associated with a lower likelihood of a higher DWI score (p < 0.001), and non-mass lesions were associated with a decreased likelihood of a higher DWI score compared with mass lesions (p = 0.196). In conclusion, the inclusion of MIPs of DWI in the preoperative evaluation of breast cancer patients, particularly young women with marked BPE, proved highly beneficial in improving the overall diagnostic process.

Objectives: To explore the potential of Radiomics alone and in combination with a diffusion-weighted derived quantitative parameter, namely the apparent diffusion co-efficient (ADC), using supervised classification algorithms in the prediction of outcomes and prognosis. Materials and Methods: Retrospective evaluation of the imaging was conducted for a study cohort of uterine cervical cancer, candidates for radical treatment with chemo radiation. ADC values were calculated from the darkest part of the tumor, both before (labeled preADC) and post treatment (labeled postADC) with chemo radiation. Post extraction of 851 Radiomics features and feature selection analysis—by taking the union of the features that had Pearson correlation >0.35 for recurrence, >0.49 for lymph node and >0.40 for metastasis—was performed to predict clinical outcomes. Results: The study enrolled 52 patients who presented with variable FIGO stages in the age range of 28–79 (Median = 53 years) with a median follow-up of 26.5 months (range: 7–76 months). Disease recurrence occurred in 12 patients (23%). Metastasis occurred in 15 patients (28%). A model generated with 24 radiomics features and preADC using a monotone multi-layer perceptron neural network to predict the recurrence yields an AUC of 0.80 and a Kappa value of 0.55 and shows that the addition of radiomics features to ADC values improves the statistical metrics by approximately 40% for AUC and approximately 223% for Kappa. Similarly, the neural network model for prediction of metastasis returns an AUC value of 0.84 and a Kappa value of 0.65, thus exceeding performance expectations by approximately 25% for AUC and approximately 140% for Kappa. There was a significant input of GLSZM features (SALGLE and LGLZE) and GLDM features (SDLGLE and DE) in correlation with clinical outcomes of recurrence and metastasis. Conclusions: The study is an effort to bridge the unmet need of translational predictive biomarkers in the stratification of uterine cervical cancer patients based on prognosis.

Background: Numerous endometrial disorders can create several difficulties for the radiologist due to the overlapping of imaging characteristics and diverse endometrial pathologies. The most frequently utilized imaging tool for diagnosing and characterizing endometrial focal lesions is magnetic resonance imaging (MRI) with diffusion weighted images (DWI). Objective: We conducted this study to determine the efficacy of MRI with DWI in improving the diagnostic accuracy of endometrial focal lesions, especially in the differential diagnosis of benign and malignant focal endometrial masses. Patients and methods: This study recruited 36 women (21 postmenopausal and 15 premenopausal) who experienced vaginal bleeding and had endometrial thickness and focal endometrial lesions with a distinct echo pattern on ultrasound (US) examination. The age of patients was between 27 to 85 years, with an average of 45.2 years. Ethics Committee approval was obtained in addition to written informed consent from all included patients. Results: The 36 patients included in this study, were classified according to their lesions histopathological results; Benign group (15 lesions; 41.67%) and malignant group (21 lesions; 58.33%). The most common benign lesion was endometrial polyp (9/15) while the most common malignant lesion was endometrial carcinoma (21/21). In the current study MRI with diffusion could correctly diagnose 33 lesions out of 36 lesions, achieving (91.6%) sensitivity, (100%) specificity, (100%) positive predictive value (PPV), (95.6%) negative predictive value (NPV) and accuracy (97.05 %). Conclusion: Integrating DWI and ADC mapping at a high b value in pelvic MRI examination improves the sensitivity, specificity, and precision of diagnosing endometrial focal lesions. [ABSTRACT FROM AUTHOR]

Objectives: To explore the potential of Radiomics alone and in combination with a diffusionweighted derived quantitative parameter, namely the apparent diffusion co-efficient (ADC), using supervised classification algorithms in the prediction of outcomes and prognosis. Materials and Methods: Retrospective evaluation of the imaging was conducted for a study cohort of uterine cervical cancer, candidates for radical treatment with chemo radiation. ADC values were calculated from the darkest part of the tumor, both before (labeled preADC) and post treatment (labeled postADC) with chemo radiation. Post extraction of 851 Radiomics features and feature selection analysis--by taking the union of the features that had Pearson correlation >0.35 for recurrence, >0.49 for lymph node and >0.40 for metastasis--was performed to predict clinical outcomes. Results: The study enrolled 52 patients who presented with variable FIGO stages in the age range of 28-79 (Median = 53 years) with a median follow-up of 26.5 months (range: 7-76 months). Disease recurrence occurred in 12 patients (23%). Metastasis occurred in 15 patients (28%). A model generated with 24 radiomics features and preADC using a monotone multi-layer perceptron neural network to predict the recurrence yields an AUC of 0.80 and a Kappa value of 0.55 and shows that the addition of radiomics features to ADC values improves the statistical metrics by approximately 40% for AUC and approximately 223% for Kappa. Similarly, the neural network model for prediction of metastasis returns an AUC value of 0.84 and a Kappa value of 0.65, thus exceeding performance expectations by approximately 25% for AUC and approximately 140% for Kappa. There was a significant input of GLSZM features (SALGLE and LGLZE) and GLDM features (SDLGLE and DE) in correlation with clinical outcomes of recurrence and metastasis. Conclusions: The study is an effort to bridge the unmet need of translational predictive biomarkers in the stratification of uterine cervical cancer patients based on prognosis. [ABSTRACT FROM AUTHOR]

Background. The 2010 revision of the McDonald criteria, widely used for the diagnosis of multiple sclerosis (MS), has established that dissemination in time (DIT) can be demonstrated by the simultaneous presence of asymptomatic gadolinium-enhancing and non-enhancing plaques on a single magnetic resonance imaging (MRI). When the use of gadolinium contrast agents is contraindicated, diffusion-weighted imaging (DWI) is utilized to confirm diffusion alterations in active inflammatory plaques. This study intended to examine whether DWI can be a viable alternative to contrast-enhanced T1-weighted imaging for demonstrating DIT in MS. Material and methods.We assessed 30 previously diagnosed MS patients during acute relapse (based on the 2010 McDonald criteria) and evaluated their brain MRI via DWI‚ contrast-enhanced T1-weighted imaging, and FLAIR sequences. Asymptomatic plaques were defined as either hyperintense or non-hyperintense in DWI and enhancing or non-enhancing in T1GAD-MRI. Statistical indices for the prediction of plaque enhancement in T1 GAD-MRI via DWI-MRI were calculated and compared. Results. The 30 participants in our study had a total of 925 demyelinating plaques that were larger than 3mm in size and presented to be hyperintense in FLAIR-MRI. Diffusion hyperintensity and plaque enhancement were significantly correlated. The sensitivity‚ specificity, positive predictive value‚ negative predictive value, and accuracy of DWI were calculated to be 69.66%‚ 99.76%‚ 96.88%‚ 96.86%, and 96.86%, respectively. Conclusions. Hyperintense DWI findings do not necessarily overlap with contrast enhancements in T1 GAD-MRI. DWI was shown to produce a higher rate of false-positive results. Our study concludes that although T1 GAD-MRI should not be replaced by DWI to determine DIT due to its lower specificity, DWI’s continued use as a surrogate screening imaging sequence whenever the use of T1GAD-MRI is of concern is not without its merits. [ABSTRACT FROM AUTHOR]

Introduction: Diffusion-weighted (DW) is an evolving technique that provides both qualitative and quantitative data about the diffusion of water molecules and b-value plays a significant role in DW images. The aim of this study is to find the optimal b-value in diffusion-weighted MRI for the detection of breast lesions. Methods: The study included 124 subjects. T2-FS sequences were acquired for lesion measurement. DW was acquired with b-values 300, 600 and 1000 s/mm². DW images were evaluated by two radiologists under the criteria's - signal-to-noise ratio (SNR), contrast differentiation of lesion from the glandular tissue, and contrast differentiation of glandular tissue from fatty tissues. Relative Signal intensity ratio (SIR), SNR and contrast-to-noise ratio (CNR) were calculated. Results: Kappa value is highest for a b-value of 600 for all the three criteria, for subjective SNR the kappa value was 0.906 which indicates that the inter-rater reliability rate is an almost perfect agreement. Differentiation of lesion from the fibro-glandular tissues, the kappa coefficient is 0.904 which interprets that the agreement between the readers is almost perfect and the kappa coefficient to differentiate the fibro-glandular from fatty tissues is 0.875 which shows that there is substantial agreement. Relative SIR, SNR, and CNR is highest for a b-value of 600 with a mean value of 4.6, 14.7, and 44 respectively. Conclusion: Optimal b-value for good image quality is 0, 600 s/mm². Standardizing an optimal b-value is highly significant since it improves the overall image quality and enhances multi- center diagnosing with an accurate report. [ABSTRACT FROM AUTHOR]

Introduction: The aim of this study was to analyze the sensitivity and specificity of non-echoplanar (non-EPI) diffusion-weighted (DW) magnetic resonance imaging (MRI) for the detection of cholesteatoma, with a focus on its value as an adjunct to clinical examination. Methods: In a prospective cohort study, 92 cases were divided into 2 groups: “clinically cholesteatoma” (n = 79) and “clinically no cholesteatoma” (n = 13). Non-EPI DW MRI was performed preoperatively in all cases. The presence of a cholesteatoma was assessed by clinicians otoscopically, by neuroradiologists on non-EPI DW MRI, by the surgeon intraoperatively, and finally by the pathologist postoperatively. Data analysis was performed for specificity, sensitivity, positive predictive value, negative predictive value, and interrater variability. Results: The sensitivity and specificity were 89.3% and 75%, respectively, in the “clinically cholesteatoma” group and 0% and 100% in the “clinically no cholesteatoma” group. Non-EPI DW MRI had a positive predictive value of 98.5% when cholesteatoma was suspected clinically and a negative predictive value of 84.6% when cholesteatoma was not suspected clinically. Conclusion: If cholesteatoma is suspected clinically, non-EPI DW MRI is not necessary. If there is no clinical suspicion of cholesteatoma in second-look situations, sensitivity is low and serial follow-up MRI with long intervals is advised. [ABSTRACT FROM AUTHOR]

Background: Diffusion-weighted (DW)-MRI is invaluable in detecting prostate cancer. We determined its sensitivity and specificity and established interobserver agreement for detecting tumour in men with a family history of prostate cancer stratified by genetic risk. Methods: 51 men with a family history of prostate cancer underwent T2-W + DW-endorectal MRI at 3.0 T. Presence of tumour was noted at right and left apex, mid and basal prostate sextants by 2 independent observers, 1 experienced and the other inexperienced in endorectal MRI. Sensitivity and specificity against a 10-core sampling technique (lateral and medial cores at each level considered together) in men with >2× population risk based on 71 SNP analysis versus those with lower genetic risk scores was established. Interobserver agreement was determined at a subject level. Results: Biopsies indicated cancer in 28 sextants in 13/51 men; 32 of 51 men had twice the population risk (>0.25) based on 71 SNP profiling. Sensitivity/specificity per-subject for patients was 90.0%/86.4% (high-risk) vs. 66.7%/100% (low-risk, observer 1) and 60.0%/86.3% (high-risk) vs. 33.3%/93.8% (low-risk, observer 2) with moderate overall inter-observer agreement (kappa = 0.42). Regional sensitivities/specificities for high-risk vs. low-risk for observer 1 apex 72.2%/100% [33.3%/100%], mid 100%/93.1% [100%/97.3%], base 16.7%/98.3% [0%/100%] and for observer 2 apex 36.4%/98.1% [0%/100%], mid 28.6%/96.5% [100%/100%], base 20%/100% [0%/97.3%] were poorer as they failed to detect multiple lesions. Conclusion: Endorectal T2W + DW-MRI at 3.0 T yields high sensitivity and specificity for tumour detection by an experienced observer in screening men with a family history of prostate cancer and increased genetic risk.

Purpose To improve spatial resolution and image quality of diffusion-weighted (DW) MRI in detecting low-risk prostate cancer (lrPC) in patients undergoing active surveillance protocol (AS-PC), we propose the application of a diffusion-prepared balanced steady-state free precession (bSSFP) technique capable of multishot acquisition. Methods Diffusion-prepared bSSFP was compared with single-shot DW echo planar imaging (SS-DW-EPI) at two prescribed resolutions (2.1 × 2.1 × 3.5mm3, 0.9 × 0.9 × 3.5 mm3) in nine healthy subjects and nine AS-PC patients. Geometric distortion and susceptibility artifacts were quantitatively assessed in all subjects. In AS-PC patients, lesion detection via blinded multiparametric MRI including T1-weighted, T2-weighted, dynamic contrast-enhanced imaging, and along with either of two DW methods were evaluated against 12-point biopsy. Results Geometric distortion and susceptibility artifacts were significantly less for diffusion-prepared bSSFP at both prescribed spatial resolutions than SS-DW-EPI. Apparent diffusion coefficients of healthy prostate tissue were concordant between the two DW methods at both spatial resolutions. In AS-PC patients, multiparametric MRI with diffusion-prepared bSSFP had greater sensitivity (94%, 63%), accuracy (76%, 67%), positive-predictive value (54%, 48%), negative-predictive value (97%, 82%), and area under the curve (0.80, 0.67) than with SS-DW-EPI. Conclusions The proposed diffusion-prepared technique with higher spatial resolution and improved image quality over SS-DW-EPI resulted in better multiparametric MRI detection of lrPC in AS-PC patients. Magn Reson Med 75:616-626, 2016. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: To evaluate the utility of conventional MRI and diffusion-weighted imaging (DWI) in differentiating benign from malignant endometrial lesions. Methods: 52 patients with an abnormal endometrium on MRI and subsequent pathologic evaluation (35 benign, 17 malignant) were included. Two radiologists (R1, R2) independently evaluated endometrial abnormalities for characteristics on conventional MRI and DWI. Findings were assessed using unpaired t-tests, Fisher's exact test, and multi-variate logistic regression. Results: Findings with significantly higher frequency in malignant abnormalities were: presence of irregularly marginated endometrial lesion (R1: 71% vs. 34%, R2: 94% vs. 26%), irregular endo-myometrial interface on T2WI (R1: 77% vs. 26%, R2: 94% vs. 29%), irregular endo-myometrial interface on post-contrast T1WI (R1: 82% vs. 23%, R2: 88% vs. 20%), increased signal on high b-value DWI (R1: 82% vs. 20%, R2: 94% vs. 20%), decreased ADC (R1: 88 vs. 40%, R2: 94% vs. 20%) (all p <0.001, both readers). Endometrial thickness, presence of any focal endometrial lesion regardless of contour, diameter of endometrial lesion, endometrial heterogeneity on T2WI, decreased T2 signal, and increased endometrial enhancement, failed to show significant differences between groups (all p ≥0.159, both readers). At multivariate analysis, for R1, irregular endo-myometrial interface on post-contrast T1WI and increased DWI signal were significant independent predictors of malignancy (AUC=0.89); for R2, only increased DWI signal was a significant independent predictor of malignancy (AUC=0.87). Conclusion: Abnormal signal on DWI and irregularity of either the endo-myometrial interface or focal endometrial lesion were the most helpful MRI features in differentiating benign from malignant endometrial abnormalities. [Copyright &y& Elsevier]

Purpose To document the apparent diffusion coefficient (ADC) of fibroglandular breast tissue in women at high-risk of developing breast cancer and investigate the relationship between ADC and breast density. Materials and Methods Local research ethics approval was obtained. A total of 33 high-risk women including 17 BRCA1/2 mutation carriers (mean age, 43 years) and 16 women postmantle irradiation (mean age 40 years) underwent diffusion-weighted MRI between days 6 and 16 of their menstrual cycle. ADC histograms from a region of interest in fibroglandular tissue and mammographic breast density measurements were obtained. Mean, percentile ADC values (10th, 25th, 50th, 75th, 90th) and skew were compared for the two groups; ADC and mammographic breast density were correlated. Results Mean ADC values (×10−6 mm2/s) were 2017 ± 197 in postmantle irradiated women and 1827 ± 289 in BRCA1/2 mutation carriers ( P = 0.035) with significant differences at all percentiles ( P < 0.0001) but not skew ( P = 0.44). ADC values showed weak positive correlation with mammographic breast density in BRCA1/2 mutation carriers ( r = 0.51, P = 0.043) but not in postmantle radiotherapy patients ( r = 0.49, P = 0.13). Conclusion Higher ADC values seen in fibroglandular tissue postmantle irradiation compared with BRCA1/2 mutation carriers has potential to improve tumor detection in these patients. Lack of correlation between ADC and breast density postmantle irradiation may be a result of microstructural changes. J. Magn. Reson. Imaging 2014;39:805-811. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this study was to determine the feasibility of diffusion-weighted magnetic resonance imaging (DWI) for detecting colorectal polyps. DWI (high b-value of 1000 s/mm2) was prospectively performed in 26 symptomatic patients who were scheduled to undergo colonoscopy. DWI and colonoscopic findings were interpreted in a blinded manner. The sensitivity and positive predictive value (PPV) of DWI for the detection of clinically relevant polyps (≥6 mm) and colorectal cancer (CRC) were calculated on a per-lesion basis, using colonoscopy results as the standard of reference. Sensitivity, specificity, PPV and negative predictive value (NPV) on a per-patient basis were also calculated. Sensitivity and PPV on a per-lesion basis were 80.0% [95% confidence interval (CI): 49.0%–94.3%] and 72.7% (95% CI: 43.4%–90.3%) for polyps ≥6 mm and CRC. Sensitivity, specificity, PPV and NPV on a per-patient basis were 85.7% (95% CI: 48.7%–97.4%), 84.2% (95% CI: 62.4%–94.5%), 66.7% (95% CI: 35.4%–87.9%) and 94.1% (95% CI: 73.0%–99.0%) for polyps ≥6mm and CRC. In conclusion, DWI cannot yet be recommended in a clinical setting in which DWI is performed first and subsequent colonoscopy is only performed in patients with positive findings at DWI. Further (technical) developments are required to increase its diagnostic yield. [Copyright &y& Elsevier]

Objectives: To establish the reproducibility of apparent diffusion coefficient (ADC) measurements in normal fibroglandular breast tissue and to assess variation in ADC values with phase of the menstrual cycle and menopausal status. Methods: Thirty-one volunteers (13 premenopausal, 18 postmenopausal) underwent magnetic resonance twice (interval 11-22 days) using diffusion-weighted MRI. ADC and a perfusion-insensitive ADC (omitting b = 0) were calculated. Reproducibility and inter-observer variability of mean ADC values were assessed. The difference in mean ADC values between the two phases of the menstrual cycle and the postmenopausal breast were evaluated. Results: ADC and ADC showed good reproducibility ( r% = 17.6, 22.4). ADC showed very good inter-observer agreement ( kappa = 0.83). The intraclass correlation coefficients (ICC) were 0.93 and 0.91. Mean ADC values were significantly lower in the postmenopausal breast (ADC 1.46 ± 0.3 × 10 mm/s, ADC 1.33 ± 0.3 × 10 mm/s) compared with the premenopausal breast (ADC 1.84 ± 0.26 × 10 mm/s, ADC 1.77 ± 0.26 × 10 mm/s; both P < 0.001). No significant difference was seen in ADC values in relation to menstrual cycle (ADC P = 0.2, ADC P = 0.24) or between postmenopausal women taking or not taking oestrogen supplements (ADC P = 0.6, ADC P = 0.46). Conclusions: ADC values in fibroglandular breast tissue are reproducible. Lower ADC values within the postmenopausal breast may reduce diffusion-weighted contrast and have implications for accurately detecting tumours. Key Points: • ADC values from fibroglandular breast tissue are measured reproducibly by multiple observers. • Mean ADC values were significantly lower in postmenopausal than premenopausal breast tissue. • Mean ADC values did not vary significantly with menstrual cycle. • Low postmenopausal ADC values may hinder tumour detection on DW-MRI. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the effect of fat infiltration on the apparent diffusion coefficient (ADC) of liver, and assess the relationship between ADC and hepatic fat fraction (HFF). Materials and Methods: MRI scans of 120 consecutive patients were included in this retrospective study. Of these, 42 patients were included in the fatty liver group and 78 in the control group. ADC values were measured from a pair of diffusion-weighted (DW) images ( b = 0 mm2/s and 1000 mm2/s). HFFs were measured using T1W GRE dual-echo images. The difference between the ADCs of the two groups was assessed with the t-test. The relationship between HFF and ADC was determined using linear regression analysis and the Pearson correlation coefficient ( r). Results: Mean HFFs were 0.85 ± 2.86 and 13.67 ± 8.62 in the control and fatty liver groups, respectively. The mean ADC of fatty liver group 1.20 ± 0.22 × 10−3 mm2/s was significantly lower than that of the control group 1.32 ± 0.23 × 10−3 mm2/s ( P = 0.02). Linear regression analysis revealed an inverse relationship between ADC and HFF ( r = −0.39, P < 0.0001). Conclusion: ADC significantly decreases in patients with >5% HFF, and ADC and HFF exhibit an inverse relationship. J. Magn. Reson. Imaging 2012;. © 2011 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Abstract: Diffusion-weighted MRI has enabled the imaging of white matter architecture in vivo. Fiber orientations have classically been assumed to lie along the major eigenvector of the diffusion tensor, but this approach has well-characterized shortcomings in voxels containing multiple fiber populations. Recently proposed methods for recovery of fiber orientation via spherical deconvolution utilize a spherical harmonics framework and are susceptible to noise, yielding physically-invalid results even when additional measures are taken to minimize such artifacts. In this work, we reformulate the spherical deconvolution problem onto a discrete spherical mesh. We demonstrate how this formulation enables the estimation of fiber orientation distributions which strictly satisfy the physical constraints of realness, symmetry, and non-negativity. Moreover, we analyze the influence of the flexible regularization parameters included in our formulation for tuning the smoothness of the resultant fiber orientation distribution (FOD). We show that the method is robust and reliable by reconstructing known crossing fiber anatomy in multiple subjects. Finally, we provide a software tool for computing the FOD using our new formulation in hopes of simplifying and encouraging the adoption of spherical deconvolution techniques. [Copyright &y& Elsevier]

There are few studies regarding functional outcome and lesion extent on diffusion-weighted MRI (DWI) in patients with posterior circulation (PC) infarction. The aim of our study was to assess whether a newly proposed posterior circulation Alberta Stroke Program Early CT Score (pc-ASPECTS) on DWI is useful for predicting functional outcome in PC patients. One hundred thirty-two patients with first-ever ischemic stroke in the posterior circulation within 24 h of onset who were admitted to our hospital were enrolled in the study. We compared background characteristics, vital signs, laboratory data, and MRI findings between favorable (F) and unfavorable (U) outcome groups at 3 months, according to the modified Rankin Scale (mRS). The F and U groups were defined as having a mRS of 0–2 and 3–6, respectively. pc-ASPECTS was scored by DWI obtained 12–36 h after onset. Ninety-eight patients (74.2%) were classified into the F group and 34 patients (25.8%) into the U group. On univariate analysis, F group patients were younger, had lower National Institutes of Health Stroke Scale (NIHSS) score at entry, and a lower rate of early neurological deterioration (END) and cardioembolic stroke than U group patients. On MRI, F group patients had lower leukoaraiosis and medial temporal atrophy score and higher pc-ASPECTS score on DWI compared to U group patients. Multiple logistic regression analysis revealed NIHSS ( p < 0.001), END ( p = 0.0057), pc-ASPECTS ( p < 0.001), and leukoaraiosis ( p = 0.0091) as independent predictors of functional outcome. pc-ASPECTS appears to be a powerful marker for predicting functional outcome, along with clinical severity and END. Leukoaraiosis may also be an independent predictor of functional outcome. [ABSTRACT FROM AUTHOR]

Diffusion-weighted images based on magnetic resonance reveal the microstructure of tissues by monitoring the random movement of water molecules. In this study, we investigated whether this new technique could visualize pathologic lesions on ulnar nerve in cubital tunnel. Six elbows in six healthy males without any symptoms and eleven elbows in ten patients with cubital tunnel syndrome underwent on diffusion-weighted MRI. No signal from the ulnar nerve was detected in normal subjects. Diffusion-weighted MRI revealed positive signals from the ulnar nerve in all of the eleven elbows with cubital tunnel syndrome. In contrast, conventional T2W-MRI revealed high signal intensity in eight elbows and low signal intensity in three elbows. Three elbows with low signal MRI showed normal nerve conduction velocity of the ulnar nerve. Diffusion-weighted MRI appears to be an attractive technique for diagnosis of cubital tunnel syndrome in its early stages which show normal electrophysiological and conventional MRI studies. [ABSTRACT FROM AUTHOR]

Measurement of striatal volume using magnetic resonance imaging (MRI) provides a marker of striatal degeneration in Huntington disease (HD). Recent evidence suggests that diffusion-weighted MRI (DWI) may also detect striatal damage in HD. Here, we compared the sensitivities of volumetric MRI and DWI at distinguishing 10 patients with early symptomatic HD from 12 agematched controls. Additionally, we assessed longitudinal changes in striatal volume and diffusivity in 8 of the HD patients over a 2-year period. At baseline, HD patients had significantly smaller volumes and significantly higher trace of the diffusion coefficient (Trace(D)) values of putamen and caudate than controls, but the volume differences were relatively larger than the Trace(D) differences. Putaminal and caudate volumes were outside the normal range in 9 of 10 HD patients, whereas Trace(D) values of putamen and caudate were abnormal in 8 and 6 of 10 HD subjects, respectively. During 2-year follow-up, there was significant volume loss of HD putamen (mean change: –8.0 %) and caudate (mean change: –12.7 %). By contrast, longitudinal Trace(D) changes of putamen (mean change: 4.0 %) and caudate (mean change: 3.8 %) did not reach statistical significance. Thus, volumetric MRI seems more sensitive to striatal degeneration in early symptomatic HD than DWI. [ABSTRACT FROM AUTHOR]

This study presents a method for computing a probabilistic atlas that describes the spatial distributions of acute infarcts of the brain. The data consisted of diffusion-weighted-images (DWI) and high-resolution T1-weighted MR images rep resenting ww studies from 22 subjects. All DWI data sets contained high-intensity lesions on B-1000 maps, known from clinical history to be related to acute stroke. To compute the atlas, manually segmented infarcts on original DWI were spatially transformed and registered to a common coordinate system. This coordinate system allowed combining all lesions into a statistical atlas in the model space. As a result, the computed probabilistic map showed mild left-sided predominance of brain infarcts, which likely represents asymmetry in eloquence of brain regions. In our opinion, the statistical atlas of acute brain infarcts can facilitate computer-based detection of stroke in large image data sets. [ABSTRACT FROM AUTHOR]

Image contrast in intermolecular double-quantum coherence (iDQC) imaging of a pig tail was investigated on a 7.05-T microimaging scanner. In addition to TR (repetition time) and TE (echo time), the time interval τ between radio frequency pulses during iDQC evolution and the areas under the iDQC-encode gradients in the iDQC imaging sequence were also used to manipulate image contrast. When suitable imaging parameters were selected, images with unique contrast, such as those with certain regions of the sample highlighted, were obtained without using contrast agents. The effects of iDQC-encode gradient on image contrast were studied quantitatively, and the unique contrast imposed by the related diffusion weighting was also shown. Experimental results demonstrated that the iDQC images have contrast fundamentally different from the conventional single-quantum coherence images. [Copyright &y& Elsevier]