Diffusion-weighted MR Imaging for the Assessment of Renal Function: Analysis Using Statistical Models Based on Truncated Gaussian and Gamma Distributions.

To investigate the clinical application of diffusion weighted imaging (DWI) in uterine cervical cancer and the apparent diffusion coefficient (ADC) value in diagnosis and predicting treatment response. Twenty-eight patients with advanced primary cervical cancer confirmed by pathology and 10 cases of normal uterine cervix as control were recruited in this prospective clinical trial. To analyze the correlation between tumor volume measured in DWI and tumor maximum diameter measured according to the RECIST criteria. To compare the ADC value differences among the uterine cervical cancer, uterine myometrium, and normal uterine cervix. To compare the ADC values in 17 cancer patients before and after treatment. The illustration of tumor boundary in DWI was superior to conventional T2WI and post-enhancement T1WI. The DWI with higher b value (2000 s/mm(2)) had a better signal-to-noise ratio. The tumor volume measured in DWI has good correlation with tumor maximum diameter according to RECIST criteria (r = 0.759, P < 0.01). When b = 800 s/mm(2), the ADC values of the uterine cervical cancer, uterine myometrium, and normal uterine cervix were (9.85 ± 1.55)×10(-3) mm(2)/s, (14.20 ± 2.80)×10(-3) mm(2)/s, and (14.14 ± 0.45) ×10(-3) mm(2)/s. When b = 2000 s/mm(2), the ADC values of the uterine cervical cancer, uterine myometrium and normal uterine cervix were (7.38 ± 0.98)×10(-3) mm(2)/s, (8.52 ± 2.38)×10(-3) mm(2)/s, and (8.60 ± 0.63)×10(-3) mm(2)/s, respectively. There were significant differences between the cervical cancer and normal cervix or uterine myometrium (P < 0.001 for both). When b = 800 s/mm(2), the ADC value was (9.85 ± 1.55)×110(-3) mm(2)/s before and (13.41 ± 2.93)×10(-3) mm(2)/s after treatment (P < 0.001). When b = 2000 s/mm(2), the ADC value was (7.38 ± 0.98)×10(-3) mm(2)/s before and (8.93 ± 1.92)×10(-3) mm(2)/s after treatment (P = 0.008). Univariate logistic regression analysis showed that 25% ADC, 50%ADC, and 75%ADC in the tumor ADC value histogram before treatment were significantly correlated to the treatment outcome of cervical cancer (P < 0.05 for all). Multivariate regression analysis showed that 25%ADC, 50%ADC, and 75%ADC in the tumor ADC value histogram before treatment were not significantly correlated to the treatment outcome of cervical cancer (P > 0.05 for all). The values of ROC curves were 25%ADC = 0.818, 50%ADC = 0.775, and 75%ADC = 0.716 (P > 0.05), however, the 25% ADC showed a relatively stronger statistical power. DWI helps to confirm the morphology and exact target zone of the tumor for radiotherapy. DWI volume measurement is well correlated with RECIST criteria, particularly in volume measurement of irregular tumors. ADC value has a potential in quantitatively monitoring treatment response and predicting outcome of cervical cancers.

Objective To study the effect of diffusion-weighted magnetic resonance imaging (DW-MRI) in the differential diagnosis of hydronephrosis and pyonephrosis. Methods From March 2015 to October 2017, 50 patients with renal stone and highly suspected infectious hydronephrosis underwent renal DW-MRI, and clinical materials were collected and analyzed retrospectively. Seventeen male and 33 female patients were enrolled with a mean age of (49.40±10.51) years. The median maximum diameter of renal stone was 30.30 (17.38, 56.01) mm and hydronephrosis was 46.39 (34.33, 56.55) mm. No pyonephrosis was diagnosed by preoperative ultrasound or CT, while 29 cases of hydronephrosis and 21 cases of pyonephrosis were reported by preoperative DW-MRI. Final diagnoses of hydronephrosis and pyonephrosis were made according to whether the pelvic urine drainage was purulent or not during the surgery. DW-MRI reports and characteristics of DW images were analyzed retrospectively. Apparent diffusion coefficient (ADC) was calculated and ADC map constructed, which was compared between the two groups. Receiver operating characteristic curve (ROC) was drawn to analyze the area under curve (AUC) and the optimal cutoff of ADC value, with sensitivity and specificity. Results Thirty-three patients of hydronephrosis and 17 pyonephrosis were confirmed intraoperatively. The overall accuracy of diagnosis using DW-MRI was 84.00% (42/50), with sensitivity of 88.24% (15/17) and specificity of 81.82% (27/33). Among 30 patients who underwent CT scan in our hospital, mean CT value of 18 hydronephrosis was (7.03±3.26) HU and that of 12 pyonephrosis was (8.67±3.52) HU, with no statistical significance (P>0.05). On DW image, when b≥500 s/mm2, hydronephrosis signal intensity was lowered apparently, whereas pyonephrosis signal intensity was intensified. On ADC map, hydronephrosis appeared as hyperintensity, whereas pyonephrosis appeared as hypointensity. The mean ADC value of pyonephrosis group was lower than hydronephrosis group [(1.53±0. 58)×10-3 mm2/s vs. (2.86±0.56)×10-3 mm2/s, P<0.01]. ROC analysis revealed that AUC=0.92(95%CI 0.80-0.98), and the cut-off value of ADC for pyonephrosis diagnosis was 1.39×10-3 mm2/s, of which the sensitivity and specificity was 94.12% and 84.85% respectively. Conclusions Signal of pyonephrosis was enhanced on DW image, while decreased on ADC image. The ADC value of pyonephrosis was much lower than that of hydronephrosis, with which the differential diagnosis between pyonephrosis and hydronephrosis could be made efficiently. Key words: Hydronephrosis; Pyonephrosis; Urosepsis; Diffusion-weighted imaging; Apparent diffusion coefficient

Purpose:Prostate cancer management includes identification of clinically significant cancers that may require curative treatment. Statistical models based on gamma distribution can describe diffusion signal decay curves of prostate cancer. The purpose of this study was to evaluate the ability of parameters obtained with the gamma model in differentiating prostate cancers with different Gleason score values.Methods:This study included 155 patients with prostate cancer who underwent multiparametric magnetic resonance imaging prior to prostate biopsy (127 patients) or radical prostatectomy (28 patients) between January 2015 and June 2017; 159 foci of prostate cancer were included in our study. We compared cases scored as Gleason score (GS) 3 + 3 and GS ≥ 3 + 4, and analyzed cases scored as GS ≤ 3+ 4 and GS ≥ 4 + 3 based on the gamma model (Frac < 1.0, Frac < 0.8, Frac < 0.5, Frac < 0.3, and Frac > 3.0), and apparent diffusion coefficient (ADC).Results:Among 159 cancerous lesions in 155 patients, 13 (8.2%) were GS 3 + 3 prostate cancers, 51 (32.0%) were GS 3 + 4 prostate cancers, 30 (18.2%) were GS 4 + 3 cancers, and 65 (40.9%) were GS ≥ 4 + 4 cancers. Frac < 0.3, Frac < 0.5, Frac < 0.8, and Frac < 1.0 were significantly higher and ADC values were significantly lower in GS ≥ 4 + 3 cancers than in GS ≤ 3 + 4 cancers (P < 0.01, P < 0.01, P < 0.01, P = 0.01, and P < 0.01, respectively). With receiver operating characteristic (ROC) analysis, Frac < 0.3 and Frac < 0.5 had significantly greater area under the ROC curve for discriminating GS ≥ 4 + 3 cancers from GS ≤ 3 + 4 cancers than ADC (P = 0.03, P < 0.01, respectively).Conclusion:Frac < 0.3 and Frac < 0.5 showed higher diagnostic performance than ADC for differentiating GS ≥ 4 + 3 from GS ≤ 3 + 4 cancers. The gamma model may add additional value in discrimination of tumor grades.

Evaluating transcatheter arterial chemoembolization for primary hepatic cancer by magnetic resonance diffusion-weighted imaging

To investigate the use of diffusion-weighted (DW) imaging for differentiating benign lesions from malignant pleural disease (MPD) and to retrospectively assess dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging acquisitions to find out whether combining these measurements with DW imaging could improve the diagnostic value of DW imaging. This study was approved by the local ethics committee, and all patients provided written informed consent. Thirty-one consecutive patients with pleural abnormalities suspicious for MPD underwent whole-body positron emission tomography (PET)/computed tomography (CT) and thorax MR examinations. Diagnostic thoracoscopy with histopathologic analysis of pleural biopsies served as the reference standard. First-line evaluation of each suspicious lesion was performed by using the apparent diffusion coefficient (ADC) calculated from the DW image, and the optimal cutoff value was found by using receiver operating characteristic curve analysis. Afterward, DCE MR imaging data were used to improve the diagnosis in the range of ADCs where DW imaging results were equivocal. Sensitivity, specificity, and accuracy of PET/CT for diagnosis of MPD were 100%, 35.3%, and 64.5%. The optimal ADC threshold to differentiate benign lesions from MPD with DW MR imaging was 1.52 × 10(-3) mm(2)/sec, with sensitivity, specificity, and accuracy of 71.4%, 100%, and 87.1%, respectively. This result could be improved to 92.8%, 94.1%, and 93.5%, respectively, when DCE MR imaging data were included in those cases where ADC was between 1.52 and 2.00 × 10(-3) mm(2)/sec. A total of 20 patients had disease diagnosed correctly, nine had disease diagnosed incorrectly, and two cases were undetermined with PET/CT. DW imaging helped stage disease correctly in 27 patients and incorrectly in four. The undetermined cases at PET/CT were correctly diagnosed at MR imaging. DW imaging is a promising tool for differentiating MPD from benign lesions, with high accuracy, and supplementation with DCE MR imaging seems to further improve sensitivity.

To investigate the usefulness of high-field MR diffusion-weighted imaging (DWI) in the diagnosis of endometrial carcinoma. Thirty-five female patients with pathologically proven endometrial carcinoma, 10 patients with pathologically proven endometrial dysplasia and 41 normal volunteers were enrolled into this study. MR images were obtained at a 3.0 T MR scanner (GE, SIGNA EXCITE HD 3.0T) and an 8-element phased-array torsopa coil was used to receive MR signal. The conventional pulse sequences included axial SE T1WI, FSE T2WI and fat saturated FSE T2WI, sagittal FSE T2WI, and coronal fat saturated FSE T2WI. Axial DWI was performed in all patients using a SE-EPI sequence with a 1000 s/mm(2) b value. The apparent diffusion coefficients (ADC) of carcinoma, dysplasia and normal mucosa were measured among the patients. Compared with myometrium, all the endometrial carcinoma, dysplasia and normal endometrium had a markedly high signal intensity on DWI. The ADC of endometrial carcinoma, dysplasia and normal endometrium was (1.08 +/- 0.23) x 10(-3)mm(2)/s, (1.29 +/- 0.21) x 10(-3) mm(2)/s and (1.41 +/- 0.21) x 10(-3) mm(2)/s, respectively. There were statistically significant differences between the carcinoma and normal endometrium (t = -6.416, P = 0.000), and between the carcinoma and dysplasia (t = -2.590, P = 0.013). However, no significant difference in ADC was found between highly-differentiated and moderately-differentiated adenocarcinomas. High-field MR diffusion-weighted imaging (DWI) is highly sensitive in detecting endometrial lesions. It can be used to differentiate the endometrial carcinoma from either dysplasia or normal endometrium, but is difficult to differentiate highly-differentiated adenocarcinoma from moderately-differentiated one.

Multiple ring-enhancing lesions in the brain

Statistical model for diffusion-weighted imaging (DWI) has been proposed for better tissue characterization by introducing a distribution function for apparent diffusion coefficients (ADC) to account for the restrictions and hindrances to water diffusion in biological tissues. This paper studies the precision and uncertainty in the estimation of parameters for statistical DWI model with Gaussian distribution, i.e. the position of distribution maxima (Dm) and the distribution width (σ), by using non-linear least-square (NLLS) fitting. Numerical simulation shows that precise parameter estimation, particularly for σ, imposes critical requirements on the extremely high signal-to-noise ratio (SNR) of DWI signal when NLLS fitting is used. Unfortunately, such extremely high SNR may be difficult to achieve for the normal setting of clinical DWI scan. For Dm and σ parameter mapping of in vivo human brain, multiple local minima are found and result in large uncertainties in the estimation of distribution width σ. The estimation error by using NLLS fitting originates primarily from the insensitivity of DWI signal intensity to distribution width σ, as given in the function form of the Gaussian-type statistical DWI model.

Inter-visit and inter-reader reproducibility of multi-parametric diffusion-weighted MR imaging in longitudinally imaged patients with metabolic dysfunction-associated fatty liver disease and healthy volunteers.

Differentiation of benign and malignant breast lesions using diffusion-weighted imaging with a fractional-order calculus model

Background Using imaging techniques to diagnose malignant and inflammatory lesions in the lung can be challenging. Purpose To compare intravoxel incoherent motion (IVIM) and apparent diffusion coefficient (ADC) magnetic resonance imaging (MRI) analysis in their ability to discriminate lung cancer from focal inflammatory lung lesions. Material and Methods Thirty-eight patients with lung masses were included: 30 lung cancers and eight inflammatory lesions. Patients were imaged with 3.0T MRI diffusion weighted imaging (DWI) using 10 b values (range, 0-1000 s/mm2). Tissue diffusivity ( D), pseudo-diffusion coefficient ( D*), and perfusion fraction ( f) were calculated using segmented biexponential analysis. ADC (total) was calculated with monoexponential fitting of the DWI data. D, D*, f, and ADC were compared between lung cancer and inflammatory lung lesions. Receiver operating characteristic analysis was performed for all DWI parameters. Results The ADC was significantly higher for inflammatory lesions than for lung cancer ([1.21 ± 0.20] × 10-3 mm2/s vs. [0.97 ± 0.15] × 10-3 mm2/s; P = 0.004). By IVIM, f was found to be significantly higher in inflammatory lesions than lung cancer ([46.10 ± 12.92] % vs. [29.29 ± 10.89] %; P = 0.005). There was no difference in D and D* between lung cancer and inflammatory lesions ( P = 0.747 and 0.124, respectively). f showed comparable diagnostic performance with ADC in differentiating lung cancer from inflammatory lung lesions, with areas under the curve of 0.833 and 0.826, sensitivity 80.0% and 73.3%, and specificity 75.0% and 87.5%, respectively. Conclusion The IVIM parameter f value provides comparable diagnostic performance with ADC and could be used as a surrogate marker for differentiating lung cancer from inflammatory lesions.

To compare the diagnostic quality of diffusion-weighted (DW) imaging schemes with regard to apparent diffusion coefficient (ADC) accuracy, ADC precision, and DW imaging contrast-to-noise ratio (CNR) for different types of lesions and breast tissue. Institutional review board approval and written, informed consent were obtained. Fifty-one patients with histopathologic correlation or follow-up performed with a 3.0-T MR imager were included in this study. There were 112 regions of interest drawn in 24 malignant, 17 benign, 20 cystic, and 51 normal tissue regions. ADC maps were calculated for combinations of 10 b values (range, 0-1250 sec/mm(2)). Differences in ADC among tissue types were evaluated. The CNRs of lesions at DW imaging were compared for all b values. A repeated-measures analysis of variance was used to assess lesion differentiation. ADCs calculated from b values of 50 and 850 sec/mm(2) were 0.99 x 10(-3) mm(2)/sec +/- 0.18 (standard deviation), 1.47 x 10(-3) mm(2)/sec +/- 0.21, 1.85 x 10(-3) mm(2)/sec +/- 0.22, and 2.64 x 10(-3) mm(2)/sec +/- 0.30 for malignant, benign, normal, and cystic tissues, respectively. An ADC threshold level of 1.25 x 10(-3) mm(2)/sec allowed discrimination between malignant and benign lesions with a diagnostic accuracy of 95% (P < .001). ADC calculations performed with multiple b values were not significantly more precise than those performed with only two. We found an overestimation of ADC for maximum b values of up to 1000 sec/mm(2). The best CNR for tumors was identified at 850 sec/mm(2). Optimum ADC determination and DW imaging quality at 3.0 T was found with a combined b value protocol of 50 and 850 sec/mm(2). This provided a high accuracy for differentiation of benign and malignant breast tumors.

Characterization of focal pancreatic lesions using normalized apparent diffusion coefficient at 1.5-Tesla: Preliminary experience

To investigate the efficacy of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the early prediction of the pathologic response to neoadjuvant chemotherapy (NAC) in patients with locally advanced gastric cancer (LAGC). Fifty patients with LAGC who were treated with NAC followed by radical gastrectomy were enrolled. Uncontrasted and DCE-MRI were performed within 1week before NAC. According to tumor regression grading (TRG), patients were labeled as responders (TRG = 0 + 1) and non-responders (TRG = 2 + 3). Apparent diffusion coefficients (ADC) and DCE-MRI kinetics (Ktrans, Ve, and Kep) were compared between the two groups. Logistic regression analysis was performed to screen independent factors to predict the NAC efficacy. The relationship between MRI parameters and TRG was studied by Spearman's correlation analysis. Receiver-operating characteristic curve analyses were applied to evaluate the efficacy. ADC, Ktrans, and Kep values were higher in responders than in non-responders (p < 0.05) and correlated with TRG (p < 0.05). The ADC and Kep values were independent markers for predicting TRG. The area under the curve, sensitivities, specificities of ADC, Ktrans, Kep, and ADC + Kep were 0.813, 0.699, 0.709, 0.886;73.64%, 65.54%, 63.21%, 70.37%; 86.47%, 54.97%, 79.47%, 95.65%; respectively. ADC + Kep demonstrated a higher efficacy than Ktrans and Kep (p = 0.012, 0.011), but without improvement compared with ADC (p > 0.05). Both DWI and DCE-MRI can effectively predict the pathologic response to NAC in LAGC. A combination of ADC and Kep increased the efficacy, and ADC is the most valuable imaging parameter.

To compare the value of whole-lesion apparent diffusion coefficient (ADC) histogram analysis derived from readout-segmented echo-planar imaging (RS-EPI) and single-shot echo-planar imaging (SS-EPI) diffusion-weighted imaging (DWI) in evaluating normal-sized lymph node metastasis (LNM) in cervical cancer. Seventy-six pathologically confirmed cervical cancer patients (stages IB and IIA) were enrolled, including 61 patients with non-LNM (group A) and 15 patients with normal-sized LNM (group B). The recorded tumor volume on T2-weighted imaging was the reference against which both DWIs were evaluated. Each ADC histogram parameter (including ADC max , ADC 90 , ADC median , ADC mean , ADC 10 , ADC min , ADC skewness , ADC kurtosis , and ADC entropy ) was compared between SS-EPI and RS-EPI and between the 2 groups. There was no significant difference in tumor volume between the 2 DWIs and T2-weighted imaging (both P > 0.05). Higher ADC max and ADC entropy but lower ADC 10 , ADC min and ADC skewness were found in SS-EPI than those in RS-EPI (all P < 0.05). For SS-EPI, lower ADC 90 and higher ADC kurtosis were found in group B than those in group A (both P < 0.05). For RS-EPI, lower ADC 90 and higher ADC kurtosis and ADC entropy were found in group B than those in group A (all P < 0.05). Readout-segmented echo-planar imaging ADC kurtosis showed the highest area under the curve of 0.792 in the differentiation of the 2 groups (sensitivity, 80%; specificity, 73.77%). Compared with SS-EPI, the ADC histogram parameters derived from RS-EPI were more accurate, and ADC kurtosis held great potential in differentiating normal-sized LNM in cervical cancer.