Maximum Apparent Diffusion Coefficient Values Research Articles

Can maximum, mean or minimum ADC values of the cervix-parametrium boundary estimate parametrial invasion for cervical carcinoma?

Purpose: Diffusion weighted imaging (DWI), which is quantified by apparent diffusion coefficient (ADC), can predict tissue microstructure. It has become an essential part of the gynecological magnetic resonance imaging (MRI) protocol. In our study it was aimed to evaluate the value of the maximum, mean, and minimum ADC values of the cervix-parametrium boundary to estimate parametrial invasion for cervix carcinoma. Material and Method: Totally 50 patients with cervical carcinoma, 18 of which had no parametrial invasion (4811-year-old) and 32 had parametrial invasion (5812-year-old) according to conventional T2 weighted imaging were enrolled. Maximum, mean, and minimum ADC values of cervix-parametrium boundary of primary tumors were statistically compared between the groups without and with parametrial invasion. The diagnostic performances of the maximum, mean and minimum ADC values were evaluated by ROC analysis in terms of estimating parametrial invasion. Results: The mean maximum, mean and minimum ADC values were lower for the patients with parametrial invasion. However, only the minimum ADC values had statistically significant differences between the groups. ROC analysis showed an AUC value of 0.726 for minimum ADC in estimating parametrial invasion. A minimum ADC cut-off value of 0.553x10-3 mm2/s had a sensitivity of 63%, specificity of 73%, negative predictive value of 52% and positive predictive value of 80% and accuracy of 66%. Conclusions: ADC values can be applied for the determination of parametrial invasion of cervical carcinoma. Lower minimum ADC values obtained from cervix-parametrium boundary of primary cervical carcinoma may help parametrial invasion. Especially positive predictive value of the cervix-parametrium boundary ADC is remarkable.

The impact of diffusion and perfusion-weighted imaging on glioma grading

Abstract Objectives Determining the grade of a glioma is extremely important for treatment planning and prognosis prediction. The study aimed to evaluate the usefulness of multiparametric perfusion-weighted imaging (PWI) and diffusion-weighted imaging (DWI) in preoperative glioma grading. Methods In this retrospective study, 63 individuals with brain tumors histologically confirmed, of which 23 had low-grade gliomas (LGGs) and 40 had high-grade gliomas (HGGs) were involved. We conducted this paper on apparent diffusion coefficient (ADC) maps using the entire tumor volume method, allowing us to use all ADC values of the tumor. Small-sample regions of interest (ROIs) were drawn to collect parameters of relative cerebral blood flow (rCBF), cerebral blood flow (CBF), and relative cerebral blood volume (rCBV), from both the tumor core and peritumoral edema. The PWI and DWI metrics were compared to identify the most accurate distinguishing HGGs and LGGs, analyze receiver operating characteristics (ROC), and evaluate the diagnostic performance using solitary parameters and combined. Results In diffusion MRI, there were significant differences in minimum ADC and mean ADC between LGGs and HGGs (p<0.05), with the larger area under the curve (AUC) of 0.898 found for mean ADC at a cut-off value of 1.275, with sensitivity of 82.6 % and specificity of 90 %. The maximum ADC value did not differ significantly (p>0.05). All perfusion parameters in both the tumor core and peritumoral edema area were significantly greater values in cases of HGG compared to LGG (p<0.001), with the highest AUC of 0.946 found for solid tumor rCBV value (rCBVt), the cut-off is 3.585, sensitivity of 85 % and specificity of 100 %. Combining mean ADC and rCBVt provided an excellent AUC of 0.975, a sensitivity of 92.5 %, and a specificity of 91.3 % for differentiating between HGGs and LGGs. Conclusions Perfusion and diffusion MRI are valuable in discriminating between high-grade and low-grade gliomas, with the major criterion in the decision-making process being the combined mean ADC and rCBVt parameters.

Quantitative apparent diffusion coefficient metrics for MRI-only suspicious breast lesions: any added clinical value?

Suspicious breast lesions [Breast Imaging Reporting and Data System (BI-RADS) category 4 or 5] detected only by magnetic resonance imaging (MRI) and invisible on other initial imaging modalities (MRI-only lesions) are usually small and poorly characterized in previous literature, thus making diagnosis and management difficult. This study aimed to investigate the clinical significance of quantitative apparent diffusion coefficient (ADC) metrics derived from conventional diffusion-weighted imaging (DWI) on evaluating MRI-only lesions. A total of 90 suspicious MRI-only lesions were evaluated, including 51 malignant and 39 benign lesions. Morphological and kinetic characteristics of all lesions (termed BI-RADS parameters) were described according to the BI-RADS lexicon on dynamic contrast-enhanced (DCE) imaging. Minimum, maximum, and mean ADC values (ADCmin, ADCmax, ADCmean) were obtained by measuring the ADC map of DWI. ADCheterogeneity was then obtained by the following formula: ADCheterogeneity = (ADCmax - ADCmin)/ADCmean. Diagnostic performance of these parameters was assessed and compared using the receiver operating characteristic (ROC) curve. Of the 90 MRI-only lesions, there were 45 masses and 45 non-mass lesions. Among BI-RADS parameters, only two different kinetic patterns were significantly different between benign and malignant groups (P=0.005 and P<0.001, respectively). The area under the ROC curve (AUC) of combined significant ADC parameters (ADCmin, ADCmean, and ADCmax, all P≤0.001) was significantly higher than that of the two different kinetic patterns (P=0.006 for both). For MRI-only masses, only ADCmean and ADCmax, among all BI-RADS and ADC parameters, had diagnostic value (combined AUC =0.833). For non-mass lesions, size, distribution, ADCmin, and ADCmean were significantly different between benign and malignant groups (P=0.004, P<0.001, P=0.001, and P<0.001, respectively). In addition, ADCmean had the highest diagnostic performance among all ADC parameters, regardless of mass or non-mass (AUC =0.825 and 0.812, respectively). ADCheterogeneity showed no significant differences, no matter in mass or non-mass groups (P=0.62 and 0.43, respectively). In differentiating MRI-only suspicious lesions, quantitative ADC metrics generally performed better than BI-RADS parameters, and ADCmean is still the best ADC parameter to distinguish MRI-only lesions.

Readout-segmented diffusion weighted imaging of the testis at 3.0T: comparison with single-shot echo-planar imaging.

The current study aimed to explore the feasibility of readout-segmented echo-planar imaging (RS-EPI) of the testis at 3.0T, by comparing with single-shot echo-planar imaging (SS-EPI) in qualitative image quality and quantitative apparent diffusion coefficient (ADC) values. 66 patients undergoing scrotal MRI for various clinical indications were included retrospectively. RS-EPI image quality was rated from 1 (severe distortion or artifact, or nondiagnostic) to 4 (nearly no distortion or artifact, or outstanding). The comparative image quality (RS- vs. SS-EPI) was rated from -2 (SS-EPI severe or greater conspicuity) to 2 (RS-EPI severe or greater conspicuity). The confidence interval of proportions (CIOP) of comparative image quality and Wilcoxon rank sum test were performed to assess the preferences between RS-EPI and SS-EPI. Paired samples t-test and Bland-Altman analysis were performed to compare the mean ADC values of RS-EPI and SS-EPI. The mean, maximum, and minimum ADC values measured by RS-EPI were compared in normal testicular parenchyma, benign and malignant intratesticular lesions. The evaluation of RS-EPI image quality showed RS-EPI with the characteristics of slight geometric distortion and susceptibility artifact, and good lesion conspicuity. The assessment of comparative image quality showed SS-EPI with obvious geometric distortion and susceptibility artifact, and RS-EPI preferred in lesion conspicuity. The CIOP ranged from 97 to 100% among three readers, with preferring to RS-EPI improving image quality (P < 0.001). There was a strong correlation and good agreement between mean ADC values measured by RS-EPI and SS-EPI. The mean, maximum and minimum ADC values by RS-EPI were significantly different in normal testicular parenchyma, benign and malignant intratesticular lesions. RS-EPI DWI of the testis improved image quality in geometric distortion, susceptibility artifacts, and lesion conspicuity, and provided highly correlated and consistent mean ADC values when compared to SS-EPI DWI, indicating the feasibility of RS-EPI DWI of testes.

Whole body MRI with DWI in people with NF1 and Schwannomatosis: Are qualitative and quantitative imaging features of peripheral lesions comparable to localized MRI?

PurposeTo compare the qualitative and quantitative features of peripheral lesions on localized (L) and whole-body (WB) magnetic resonance imaging (MRI) in people with neurofibromatosis type 1 (NF1) and schwannomatosis. Materials and methodsThis is a retrospective, HIPAA compliant study with twenty-seven patients (14 women, 13 men; mean age (years): 38 (3–67)) who underwent both L-MRI and WB-MRI without interval treatment. WB-MRI and L-MRI were comprised of T1-weighted, fat suppressed (FS) T2-weighted or short tau inversion recovery (STIR), diffusion-weighted imaging (DWI) using b-values of 50, 400, and 800 s/mm2, apparent diffusion coefficient (ADC) mapping and pre- and post-contrast FST1 sequences. Two readers recorded qualitative (T1 and T2/STIR signal intensity and heterogeneity, contrast enhancement and heterogeneity, perilesional enhancement, presence of a target sign and perilesional edema) and quantitative (size, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), ADC) features of peripheral lesions on L-MRI and WB-MRI.Descriptive statistics, Wilcoxon signed-rank test and McNemar’s test were used. ResultsThere were 31 peripheral lesions identified in 27 subjects, (mean size: 3.1 cm (range: 1–8.1 cm) on both L-MRI and WB-MRI).There were no differences in T1 signal and heterogeneity and T2/STIR signal and heterogeneity between WB-MRI and L-MRI ((p = 0.180, 0.083, 0.317 and 0.157 respectively). There were also no differences in contrast enhancement, heterogeneity and perilesional enhancement between WB-MRI and L-MRI (p = 1.000, 0.380 and 1.000 respectively). Presence of a target sign and perilesional edema did not differ between WB-MRI and L-MRI (p = 1.000 and 0.500 respectively). Craniocaudal (CC), mediolateral (ML) and anteroposterior (AP) size measurements on WB-MRI did not differ from CC, ML and AP size measurements on L-MRI (p = 0.597, 0.128 and 0.783 respectively). SNR on WB-DWI did not differ from SNR on L-DWI for b50, b400 and b800 images (p = 0.285, 0.166, and 0.974 respectively), and CNR on WB-DWI did not differ from CNR on L-DWI for b50, b400 and b800 images (p = 0.600, 0.124, and 0.787 respectively). There was no significant difference in minimum, mean and maximum ADC values between WB-DWI and L-DWI (p = 0.234, 0.481, and 0.441 respectively). Median minimum, mean and maximum ADC (×10(-3)mm(2)/s) differences between WB-DWI and L-DWI were 0.0 (range −1 to 0.7), 0.0 (range −0.5 to 0.6), and 0.1 (range −1.2 to 0.8) respectively. Relative ADC difference averages were 29.1% for minimum values, 10.1% for mean values, and 14.8% for maximum values. ConclusionWB-MRI yields qualitative and quantitative features for peripheral lesions, including DWI and ADC measurements, that are comparable to L-MRI scans. WB-DWI can be reliably used for the assessment of peripheral nerve sheath tumors, obviating the need for a repeat follow-up L-DWI acquisition.

Value of quantitative apparent diffusion coefficients in differentiating low-grade gliomas from mixed neuronal-glial tumors

PurposeTo retrospectively assess if diffusion-weighted MR imaging (DWI) and quantitative apparent–diffusion coefficient (ADC) maps could be used to differentiate between low-grade gliomas (LGGs) and mixed neuronal–glial tumors (MNGTs including Dysembryoplastic Neuroepithelial Tumor and Ganglioglioma). Materials and methodsWe retrospectively searched the clinical, pathological, and radiological databases for a span of 9 years and identified 24 patients with biopsy proven LGG. This included WHO (fourth edition) grade I and II tumors including astrocytoma, oligoastrocytoma and oligodendrogliomas. We also identified 22 patients with MNGTs (WHO grade I) including 13 patients with DNET and 9 patients with Ganglioglioma. All patients with pathologically confirmed tumors who had MRI including DWI sequence were included in the study. Regions of interest (ROIs) of 0.1–0.15 cm2 were manually positioned on the ADC maps and multiple values (10−6 mm2/s) were obtained including the ADCmean. Optimal thresholds of ADC values and ADC ratios for distinguishing low-grade gliomas from mixed neuronal–glial tumors were determined by receiver operating characteristic (ROC) curve analysis. ResultsAll the four ADC measurement variables, including the minimum (ADC min), the (ADC max) maximum, the mean of ADC values (ADC mean) and the ADC ratios (ADC mean/ADCnormal) showed significant difference between the MNGTs and LGGs. The most significant difference was seen with the maximum ADC value (ADC max) of the tumor where the values for LGGs were 1317 ± 314 whereas the values for MNGTs were 2134 ± 438. In both subsets of patients with MNGTs (DNET and Ganglioglioma), this difference was statistically significant (P = .015 and P = .0066, respectively). However, there was no significant difference between the ADC values of these subtypes of MNGTs. ConclusionThe ADC values of MNGTs are significantly higher compared to LGGs and can be helpful in radiological demarcation of these two conditions. The high ADC of MNGTs may be attributable to the presence of large extracellular spaces and their cellularity, which is much lower than that of pure glial neoplasms.

Differentiating between adult intracranial medulloblastoma and ependymoma using MRI

To investigate the value of routine magnetic resonance imaging (MRI) examination combined with diffusion-weighted imaging (DWI) in the differential diagnosis of adult intracranial medulloblastomas and ependymomas. MRI images of 18 medulloblastomas and 18 ependymomas in adult patients were analysed retrospectively, and the differences in MRI features of lesions and apparent diffusion coefficient (ADC) of solid lesions between the two groups were recorded. Independent sample t-tests and χ2 tests were used to analyse the differences in MRI signs and maximum ADC (ADCmax), minimum ADC (ADCmin), and mean ADC (ADCmean) values between the two groups. The receiver operating characteristic (ROC) curve was used to determine the differential diagnostic efficacy and optimal threshold for each ADC value. Age, tumour location, and tumour enhancement were significantly different between adult medulloblastoma and ependymoma (p<0.05). The ADCmax (0.69±0.11 versus 1.04±0.20×10-3 mm2/s, p<0.001), ADCmin (0.57±0.12 versus 0.96±0.21×10-3 mm2/s, p<0.001), and ADCmean (0.62±0.11 versus 1.00±0.20×10-3 mm2/s, p<0.001) values were significantly lower in adult medulloblastoma than in ependymoma. The areas under the ROC curves of ADCmax, ADCmin, and ADCmean were 0.951, 0.957, and 0.966, respectively. The optimal ADCmean threshold was 0.75×10-3 mm2/s, with a sensitivity of 88.9% and a specificity of 88.9%. Routine MRI examination combined with DWI helps differentiate between intracranial infratentorial medulloblastoma and ependymoma in adults.

Effectiveness of ADC histogram analysis in the diagnosis of focal liver lesions; is a contrast agent necessary?

Objective: The diagnostic success of apparent diffusion coefficient (ADC) histogram analysis in focal liver lesions, and the effects of quantitative data added to contrast-enhanced abdominal magnetic resonance imaging (MRI) on the diagnostic accuracy were investigated. Materials and Methods: The conventional MRI findings of 524 lesions in total were retrospectively examined. Contrast enhancement kinetics and ADC values for each lesion were found through an image analysis software. Results: Three hundred and fifty (67%) of the lesions were diagnosed as benign and 174 (33%) as malignant. Statistically significant difference was found between the benign and malignant lesion groups in terms of the minimum, maximum and mean ADC values (p&amp;lt;0.001). When optimal thresholds for minimum, maximum and mean ADC were taken as 1.47x10-3mm2/s; 1.85x10-3mm2/s; 1.72x10-3mm2/s respectively, sensitivity was found to be 97%; 83%; 95%, specificity was 100%; 98%; 99%, NPV was 100%; 99%; 99%, and PPV was 93%; 74%; 90%. ADC values added to MRI increased the diagnostic success for metastases (92%→96%), HCC (63%→73%), hemangioma (90%→99%) and FNH (56%→75%). Conclusion: ADC measurement could not show reasonable success in the diagnosis of specific lesions while being successful in the differentiation of benign and malignant lesions. Minimum ADC is more successful than mean and maximum ADC. A non-contrastenhanced MRI protocol based on the ADC measurement applicable to the selected patient group may be helpful.

The Preeminent Value of the Apparent Diffusion Coefficient in Assessing High-Risk Factors and Prognosis for Stage I Endometrial Carcinoma Patients.

ObjectivesTo evaluate the role of the apparent diffusion coefficient (ADC) value in the individualized management of stage I endometrial carcinoma (EC).MethodsA retrospective analysis was performed on 180 patients with stage I EC who underwent 1.5-T magnetic resonance imaging. The mean ADC (mADC), minimum ADC (minADC), and maximum ADC (maxADC) values of each group were measured and compared. We analyzed the relationship between ADC values and stage I EC prognosis by Kaplan-Meier method and Cox proportional hazards analysis.ResultsPatients with lower ADC values were more likely to be characterized by higher grades, specific histological subtypes and deeper myometrial invasion. The mADC, minADC and maxADC values (×10-3 mm2/s) were 1.045, 0.809 and 1.339, respectively, in grade 1/2 endometrioid carcinoma with superficial myometrial invasion, which significantly differed from those in grade 3 or nonendometrioid carcinoma or with deep myometrial invasion (0.929, 0.714 and 1.215) (P=<0.001, <0.001 and <0.001). ADC values could be used to predict these clinicopathological factors. Furthermore, the group with higher ADC values showed better disease-free survival and overall survival.ConclusionsThe present study indicated that ADC values were associated with the high-risk factors for stage I EC and to assess whether fertility-sparing, ovarian preservation or omission of lymphadenectomy represent viable treatment options. Moreover, this information may be applied to predict prognosis. Thus, ADC values could contribute to managing individualized therapeutic schedules to improve quality of life.

Utility of diffusion MRI characteristics of cervical lymph nodes as disease classifier between patients with head and neck squamous cell carcinoma and healthy volunteers

Diffusion MRI characteristics assessed by apparent diffusion coefficient (ADC) histogram analysis in head and neck squamous cell carcinoma (HNSCC) have been reported as helpful in classifying tumours based on diffusion characteristics. There is little reported on HNSCC lymph nodes classification by diffusion characteristics. The aim of this study was to determine whether pretreatment nodal microstructural diffusion MRI characteristics can classify diseased nodes of patients with HNSCC from normal nodes of healthy volunteers. Seventy-nine patients with histologically confirmed HNSCC prior to chemoradiotherapy, and eight healthy volunteers, underwent diffusion-weighted (DW) MRI at a 1.5-T MR scanner. Two radiologists contoured lymph nodes on DW (b =300 s/m2 ) images. ADC, distributed diffusion coefficient (DDC) and alpha (α) values were calculated by monoexponential and stretched exponential models. Histogram analysis metrics of drawn volume were compared between patients and volunteers using a Mann-Whitney test. The classification performance of each metric between the normal and diseased nodes was determined by receiver operating characteristic (ROC) analysis. Intraclass correlation coefficients determined interobserver reproducibility of each metric based on differently drawn ROIs by two radiologists. Sixty cancerous and 40 normal nodes were analysed. ADC histogram analysis revealed significant differences between patients and volunteers (p ≤0.0001 to 0.0046), presenting ADC distributions that were more skewed (1.49 for patients, 1.03 for volunteers; p=0.0114) and 'peaked' (6.82 for patients, 4.20 for volunteers; p=0.0021) in patients. Maximum ADC values exhibited the highest area under the curve ([AUC] 0.892). Significant differences were revealed between patients and volunteers for DDC and α value histogram metrics (p ≤0.0001 to 0.0044); the highest AUC were exhibited by maximum DDC (0.772) and the 25th percentile α value (0.761). Interobserver repeatability was excellent for mean ADC (ICC =0.88) and the 25th percentile α value (ICC =0.78), but poor for all other metrics. These results suggest that pretreatment microstructural diffusion MRI characteristics in lymph nodes, assessed by ADC and α value histogram analysis, can identify nodal disease.

Role of diffusion-weighted MRI in differentiating between benign and malignant bone lesions: a prospective study

To evaluate the ability of diffusion-weighted magnetic resonance imaging (DW-MRI) to differentiate between benign and malignant bony tumours. This prospective study was conducted from October, 2018 to December, 2019. The study included 62 patients (37 male and 25 female) with clinically suspected bony lesions referred to the Radiology Department. Patients underwent clinical examination, radiography, computed tomography (CT), and ultrasonography examinations. MRI studies were conducted using a 1.5-T MRI machine, and post-processing analysis was done using a Philips Extended MRI workspace workstation. The mean apparent diffusion coefficient (ADC) value of benign lesions ranged between 0.85×10-3 and 2.44×10-3 mm2/s. The lowest ADC values were measured in a giant cell tumour and in an inclusion epidermoid cyst (0.85×10-3 and 0.93×10-3 mm2/s, respectively). The highest measurement was in bony cysts (2.44×10-3 mm2/s) followed by osteoid osteoma (2.2×10-3 mm2/s) and osteochondroma (1.85×10-3 mm2/s). Amongst malignant lesions, ADC values ranged from 0.42×10-3 to 2.4×10-3 mm2/s. The lowest value was measured in malignant round cell tumour Ewing's/primitive neuroectodermal tumour (PNET), and the highest was measured in conventional chondrosarcoma. Metastatic lesions were observed in 11 patients with a mean ADC value of 0.71×10-3 mm2/s, followed by osteosarcoma in six patients with a mean ADC value of 0.74×10-3 mm2/s. There was a significant difference between the mean, minimum, and maximum ADC values of benign and malignant tumours. The present findings indicate that the best cut-off ADC range to predict malignancy is 0.78-0.86×10-3 mm2/s, with a sensitivity of 89.47%, specificity of 97.22%, and accuracy of 94.55%.

Pretreatment ADC predicts tumor control after Gamma Knife radiosurgery in solid vestibular schwannomas.

Radiosurgery is a well-established treatment for vestibular schwannomas (VSs), but it is often difficult to identify which tumors will respond to treatment. We sought to determine whether pretreatment or posttreatment tumor apparent diffusion coefficient (ADC) values could predict tumor control in patients undergoing Gamma Knife radiosurgery (GKRS) and whether these values could differentiate between cases of pseudoprogression and cases of true progression in the early posttreatment period. We retrospectively identified patients who underwent GKRS for solid VSs between June 2008 and November 2016 and who had a minimum follow-up of 36 months. Pretreatment and posttreatment minimum, mean, and maximum ADC values were measured for the whole tumor volume and were compared between patients with tumor control and those with tumor progression. In patients with early posttreatment tumor enlargement, ADC values were compared between patients with pseudoprogression and those with true progression. Of the 44 study patients, 34 (77.3%) demonstrated tumor control at final follow-up. Patients with tumor control had higher pretreatment minimum (1.35 vs 1.09; p = 0.008), mean (1.80 vs 1.45; p = 0.004), and maximum (2.41 vs 1.91; p = 0.011) ADC values than patients with tumor progression. ADC values did not differ between patients with pseudoprogression and those with true progression at early posttreatment follow-up. ADC values may be helpful in predicting response to GKRS in patients with solid VSs but cannot predict which tumors will undergo pseudoprogression. Patients with higher pretreatment ADC values may be more likely to demonstrate posttreatment tumor control.

Role of Quantitative Apparent Diffusion Coefficient in Predicting Genetic Subtypes of Gliomas

Introduction: Magnetic resonance morphologic features are widely used in characterising gliomas for predicting grades and thereby aiding in preoperative management planning. We aim to find out if Magnetic Resonance Imaging (MRI) morphologic characters and quantitative apparent diffusion coefficient (ADC) measurements can predict genetic subtypes of high-grade gliomas.&#x0D; Methods and Materials: Preoperative MRI examinations of histopathologically proven gliomas were retrospectively studied for qualitative tumor characteristics, including location, extent, cortical involvement, margin sharpness, cystic component, mineralization or hemorrhage, and contrast enhancement. Quantitative diffusion metrics were also assessed. Chi-square test, students t-test and multivariate regression analysis were used to evaluate the relationship between MRI features and Isocitrate Dehydrogenase (IDH) mutational status.&#x0D; Results: The final study population included 23 patients (sixteen males and seven females, mean age 40 years ± 14.4, age range 13–66 years). Nine tumors were IDH mutant and fourteen were IDH wild type. IDH wild-type tumors showed patchy to diffuse diffusion restriction and a lower apparent diffusion coefficient (ADC) compared to IDH mutant types. T2/FLAIR high signal and maximum ADC values were associated with IDH mutational status. Contrast enhancement, hemorrhage and necrosis were significantly higher in IDH wild type gliomas. There was no statistical difference in the age, gender, tumor burden, location, site and edema between the IDH-mutant and wild-type tumors.&#x0D; Conclusions: Magnetic resonance morphometric parameters that include T2/FLAIR signal character, contrast enhancement pattern, hemorrhage and necrosis and quantitative mean ADC /normalized ADC can support preoperatively the distinction of genetic subtypes of gliomas.

Classification of Primary Cerebral Lymphoma and Glioblastoma Featuring Dynamic Susceptibility Contrast and Apparent Diffusion Coefficient.

This study aimed to differentiate primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) via multimodal MRI featuring radiomic analysis. MRI data sets of patients with histological proven PCNSL and GBM were analyzed retrospectively. Diffusion-weighted imaging (DWI) and dynamic susceptibility contrast (DSC) perfusion imaging were evaluated to differentiate contrast enhancing intracerebral lesions. Selective (contrast enhanced tumor area with the highest mean cerebral blood volume (CBV) value) and unselective (contouring whole contrast enhanced lesion) Apparent diffusion coefficient (ADC) measurement was performed. By multivariate logistic regression, a multiparametric model was compiled and tested for its diagnostic strength. A total of 74 patients were included in our study. Selective and unselective mean and maximum ADC values, mean and maximum CBV and ratioCBV as quotient of tumor CBV and CBV in contralateral healthy white matter were significantly larger in patients with GBM than PCNSL; minimum CBV was significantly lower in GBM than in PCNSL. The highest AUC for discrimination of PCNSL and GBM was obtained for selective mean and maximum ADC, mean and maximum CBV and ratioCBV. By integrating these five in a multiparametric model 100% of the patients were classified correctly. The combination of perfusion imaging (CBV) and tumor hot-spot selective ADC measurement yields reliable radiological discrimination of PCNSL from GBM with highest accuracy and is readily available in clinical routine.

Quantitative Assessment of the Mandibular Condyle in Patients With Rheumatoid Arthritis Using Diffusion-Weighted Imaging

The purpose of this study was to quantitatively assess the mandibular condyle in patients with rheumatoid arthritis (RA) using the apparent diffusion coefficient (ADC) on diffusion-weighted imaging (DWI). Thirty-one patients with RA and temporomandibular joint (TMJ) pain who underwent magnetic resonance imaging (MRI) examination of the TMJs at our hospital between August 2006 and March 2020 were included in this study. Twenty-one patients with normal TMJs who underwent MRI examination at our hospital between August 2006 and March 2020 were included as controls. The MRI findings were compared between the 2 groups. The mean ADC values of the mandibular condyle in patients with RA were 1.20±0.17×10-3mm2/second. The mean ADC values of the mandibular condyle in patients with RA were significantly greater than the controls (P<.01). Receiver operating characteristic curve analysis revealed a cutoff of 0.89 for the ADC values of the mandibular condyle in patients with RA. The receiver operating characteristic curve analysis revealed areas under the curve for maximum ADC values of 0.98. Our study found that the ADC on DWI could be used for the quantitative assessment of the mandibular condyle in patients with RA, which indicated that the ADC on DWI could be useful for predicting RA.

Effective apparent diffusion coefficient parameters for differentiation between mass-forming autoimmune pancreatitis and pancreatic ductal adenocarcinoma.

To evaluate the diagnostic performance of apparent diffusion coefficient (ADC) parameters by region of interest (ROI) methods in differentiating mass-forming autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC). The institutional review board approved this retrospective study and the requirement for informed consent was waived. Twenty-three patients with mass-forming AIP and 144 patients with PDAC underwent diffusion-weighted imaging with b-values of 0 s/mm2 and 800 s/mm2. The minimum, maximum, and mean ADC values obtained by placing ROIs within lesions and percentile ADC values (10th, 25th, 50th, 75th, and 90th) from entire-lesion histogram analysis were compared between the two groups by using Mann-Whitney U tests. The diagnostic performance was evaluated by receiver operating characteristic (ROC) curve analysis. The minimum, maximum, and mean ADC values were significantly different between mass-forming AIP and PDAC groups. ROC curve analysis showed that the maximum ADC had the highest diagnostic performance (0.92), while the minimum ADC value had the lowest diagnostic performance (0.72). The AUC of minimum ADC was significantly lower than that of maximum or mean ADC (P < 0.0001, P < 0.0001). The AUC was lowest in 10th percentile ADC value and highest in 90th percentile value. The AUC increased along with the increase of percentile values. Either the maximum or mean ADC value was effective in differentiating mass-forming AIP from the PDAC group, while the minimum ADC value might not be recommended.

Assessment of histologic prognostic factors of resectable rectal cancer: comparison of diagnostic performance using various apparent diffusion coefficient parameters

This study is to investigate optimum apparent diffusion coefficient (ADC) parameter for predicting lymphovascular invasion (LVI), lymph node metastasis (LNM) and histology type in resectable rectal cancer. 58 consecutive patients with resectable rectal cancer were retrospectively identified. The minimum, maximum, average ADC and ADC difference value were obtained on ADC maps. Maximum ADC and ADC difference value increased with the appearance of LVI (r = 0.501 and 0.495, P < 0.001, respectively) and development of N category (r = 0.615 and 0.695, P < 0.001, respectively). ADC difference value tended to rise with lower tumor differentiation (r = − 0.269, P = 0.041). ADC difference value was an independent risk factor for predicting LVI (odds ratio = 1.323; P = 0.005) and LNM (odds ratio = 1.526; P = 0.005). Maximum ADC and ADC difference value could distinguish N0 from N1 category, N0 from N1–N2, N0–N1 from N2 (all P < 0.001). Only ADC difference value could distinguish histology type (P = 0.041). ADC difference value had higher area under the receiver operating characteristic curve than maximum ADC in identifying LVI (0.828 vs 0.797), N0 from N1 category (0.947 vs 0.847), N0 from N1–N2 (0.935 vs 0.874), and N0–N1 from N2 (0.814 vs 0.770). ADC difference value may be superior to the other ADC value parameters to predict LVI, N category and histology type of resectable rectal cancer.

High-Spatial-Resolution Multishot Multiplexed Sensitivity-encoding Diffusion-weighted Imaging for Improved Quality of Breast Images and Differentiation of Breast Lesions: A Feasibility Study.

Multishot multiplexed sensitivity-encoding diffusion-weighted imaging is a feasible and easily implementable routine breast MRI protocol that yields high-quality diffusion-weighted breast images.Purpose: To compare multiplexed sensitivity-encoding (MUSE) diffusion-weighted imaging (DWI) and single-shot DWI for lesion visibility and differentiation of malignant and benign lesions within the breast.Materials and Methods: In this prospective institutional review board-approved study, both MUSE DWI and single-shot DWI sequences were first optimized in breast phantoms and then performed in a group of patients. Thirty women (mean age, 51.1 years ± 10.1 [standard deviation]; age range, 27-70 years) with 37 lesions were included in this study and underwent scanning using both techniques. Visual qualitative analysis of diffusion-weighted images was accomplished by two independent readers; images were assessed for lesion visibility, adequate fat suppression, and the presence of artifacts. Quantitative analysis was performed by calculating apparent diffusion coefficient (ADC) values and image quality parameters (signal-to-noise ratio [SNR] for lesions and fibroglandular tissue; contrast-to-noise ratio) by manually drawing regions of interest within the phantoms and breast tumor tissue. Interreader variability was determined using the Cohen κ coefficient, and quantitative differences between MUSE DWI and single-shot DWI were assessed using the Mann-Whitney U test; significance was defined at P < .05.Results: MUSE DWI yielded significantly improved image quality compared with single-shot DWI in phantoms (SNR, P = .001) and participants (lesion SNR, P = .009; fibroglandular tissue SNR, P = .05; contrast-to-noise ratio, P = .008). MUSE DWI ADC values showed a significant difference between malignant and benign lesions (P < .001). No significant differences were found between MUSE DWI and single-shot DWI in the mean, maximum, and minimum ADC values (P = .96, P = .28, and P = .49, respectively). Visual qualitative analysis resulted in better lesion visibility for MUSE DWI over single-shot DWI (κ = 0.70).Conclusion: MUSE DWI is a promising high-spatial-resolution technique that may enhance breast MRI protocols without the need for contrast material administration in breast screening.Keywords: Breast, MR-Diffusion Weighted Imaging, OncologySupplemental material is available for this article.© RSNA, 2020.

Treatment-related changes in neuroendocrine tumors as assessed by textural features derived from 68Ga-DOTATOC PET/MRI with simultaneous acquisition of apparent diffusion coefficient

BackgroundNeuroendocrine tumors (NETs) frequently overexpress somatostatin receptors (SSTRs), which is the molecular basis for 68Ga-DOTATOC positron-emission tomography (PET) and radiopeptide therapy (PRRT). However, SSTR expression fluctuates and can be subject to treatment-related changes. The aim of this retrospective study was to assess, which changes in PET and apparent diffusion coefficient (ADC) occur for different treatments and if pre-therapeutic 68Ga-DOTATOC-PET/MRI was able to predict treatment response to PRRT.MethodsPatients with histopathologically confirmed NET, at least one liver metastasis > 1 cm and at least two 68Ga-DOTATOC-PET/MRI including ADC maps were eligible. 68Ga-DOTATOC-PET/MRI of up to 5 liver lesions per patients was subsequently analyzed. Extracted features comprise conventional PET parameters, such as maximum and mean standardized uptake value (SUVmax and SUVmean) and ADC values. Furthermore, textural features (TFs) from both modalities were extracted. In patients with multiple 68Ga-DOTATOC-PET/MRI a pair of 2 scans each was analyzed separately and the parameter changes between both scans calculated. The same image analysis was performed in patients with 68Ga-DOTATOC-PET/MRI before PRRT. Differences in PET and ADC maps parameters between PRRT-responders and non-responders were compared using Mann-Whitney test to test differences among groups for statistical significance.Results29 pairs of 68Ga-DOTATOC-PET/MRI scans of 18 patients were eligible for the assessment of treatment-related changes. In 12 cases patients were treated with somatostatin analogues between scans, in 9 cases with PRRT and in 2 cases each patients received local treatment, chemotherapy and sunitinib. Treatment responders showed a statistically significant decrease in lesion volume and a borderline significant decrease in entropy on ADC maps when compared to non-responders. Patients treated with standalone SSA showed a borderline significant decrease in mean and maximum ADC, compared to patients treated with PRRT. No parameters were able to predict treatment response to PRRT on pre-therapeutic 68Ga-DOTATOC-PET/MRI.ConclusionsPatients responding to current treatment showed a statistically significant decrease in lesion volume on ADC maps and a borderline significant decrease in entropy. No statistically significant changes in PET parameters were observed. No PET or ADC maps parameters predicted treatment response to PRRT. However, the sample size of this preliminary study is small and further research needed.

Associations Between Apparent Diffusion Coefficient Values and the Prognostic Factors of Breast Cancer.

Breast imaging can offer great information about breast cancer heterogeneity. The purpose of this study was to analyze the relationship between apparent diffusion coefficient (ADC) values and various prognostic factors and investigate whether ADC values are useful for breast cancer diagnosis, evaluation of treatment response, and determination of prognosis. A total of 111 cases of breast cancer were included in this study. Magnetic resonance findings were recorded according to the Breast Imaging Reporting and Data System magnetic resonance imaging lexicon. Diffusion-weighted imaging rim sign and minimum, maximum, and difference ADC values (ADCdiff) were also evaluated. ADCdiff was related to all prognostic factors such as histological grade, Ki-67, tumor size, molecular subtype, axillary node metastasis, lymphvascular invasion, internal enhancement pattern, intratumoral high T2 signal, peritumoral edema, and diffusion-weighted imaging rim sign, whereas minimum and maximum ADC values showed variable associations. Apparent diffusion coefficient values were shown to be correlated with many proven or possible prognostic factors of breast cancer. In particular, ADCdiff can reflect tumor heterogeneity and showed higher correlation.