Apparent Diffusion Coefficient In Differentiation Research Articles

Dynamic Contrast Enhanced-MRI and Apparent Diffusion Coefficient Quantitation for Differentiate Hepatocellular Carcinoma from Hepatocellular Adenoma.

Due to their overlapping radiological characteristics, hepatic lesions, such as hepatocellular carcinoma (HCC) and hepatocellular adenoma (HCA), present a substantial diagnostic challenge. Accurate differentiation between HCC and HCA is essential for the best clinical treatment and therapeutic decision-making. This study aims to assess the potential role of DCE-MRI and Apparent Diffusion Coefficient (ADC) quantitation in the diagnosis of hepatocellular carcinoma (HCC) from hepatocellular adenoma (HCA). 103 patients (56 HCC, 47 HCA) with histopathologically proven hepatocellular lesions were the subjects of a cross-sectional investigation. A standardized imaging technique was used for DCE-MRI on all patients. Diffusion-weighted imaging (DWI) provided the ADC values. The diagnostic efficacy of DCE-MRI and ADC in differentiation was evaluated using statistical analyses, such as t-tests and receiver operating characteristic (ROC) curve analysis. SPSS VER 16 was used for the analysis of the collected data. A total of 103 patients (female: male= 52:51, 57.14±3.09 years) were included in the study. The study revealed significant differences in DCE-MRI parameters and ADC values between HCC and HCA lesions. ADC value was significantly lower in HCC than in HCA (p < 0.001). The area under the curve (AUC) was 0.78 (95% CI: 0.69-0.87) for ADC, 0.84 (95% CI: 0.76-0.91) for Ktrans, and 0.72 (95% CI: 0.62-0.82) for Ve. Sensitivity and specificity for ADC were 76.59% and 71.42%, respectively. Also, PPV and NPV of ADC were 69.23% and 78.43%, respectively. Sensitivity and specificity for Ktrans were 82.14% and 76.59%, respectively. Also, PPV and NPV of Ktrans were 80.7% and 78.26%, respectively. In conclusion, DCE-MRI-derived parameters, along with ADC values, exhibit promise as non-invasive tools for differentiating HCC from HCA.

Evaluation of the Diagnostic Performance of F18-Fluorodeoxyglucose-Positron Emission Tomography, Dynamic Susceptibility Contrast Perfusion, and Apparent Diffusion Coefficient in Differentiation between Recurrence of a High-grade Glioma and Radiation Necrosis.

Differentiation between recurrence of brain tumor and radiation necrosis remains a challenge in current neuro-oncology practice despite recent advances in both radiological and nuclear medicine techniques. The purpose of this study was to compare the diagnostic performance of dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI), apparent diffusion coefficient (ADC) derived from diffusion-weighted imaging, and F18-fluorodeoxyglucose-positron emission tomography (F18-FDG-PET) in the differentiation between the recurrence of a high-grade glioma and radiation necrosis. Patients with a diagnosis of high-grade glioma (WHO Grades III and IV) who had undergone surgical resection of the tumor followed by radiotherapy with or without chemotherapy were included in the study. DSC perfusion, diffusion-weighted MRI, and PET scan were acquired on a hybrid PET/MRI scanner. For each lesion, early and delayed tumor-to-brain ratio (TBR), early and delayed maximum standardized uptake value (SUVmax), normalized ADC ratio, and normalized relative cerebral blood volume (rCBV) ratio were calculated and the pattern of lesional enhancement was noted. The diagnosis was finalized with either histopathological examination or the characteristics on follow-up imaging. The statistical analysis using the receiver operator characteristic curves was done to determine the diagnostic performance of DSC perfusion, 18-F FDG-PET, and ADC in differentiation between tumor recurrence and radiation necrosis. Fifty patients were included in the final analysis, 32 of them being men (64%). A cutoff value of early TBR >0.8 (sensitivity of 100% and specificity of 80%), delayed TBR >0.93 (sensitivity of 92.3% and specificity of 80%), early SUVmax >10.2 (sensitivity of 76.9% and specificity of 80%), delayed SUVmax >13.2 (sensitivity of 61.54% and specificity of 100%), normalized rCBV ratio >1.21 (sensitivity of 100% and specificity of 60%), normalized ADC ratio >1.66 (sensitivity of 38.5% and specificity of 80%), and Grade 3 enhancement (sensitivity of 100% and specificity of 60%) were found to differentiate recurrence from radiation necrosis. Early TBR had the highest accuracy (94.44%), while ADC ratio had the lowest accuracy (50%). A combination of early TBR (cutoff value of 0.8), late TBR (cutoff value of 0.93), and rCBV ratio (cutoff value of 1.21) showed a sensitivity of 100%, specificity of 92.3%, positive predictive value of 88.9%, negative predictive value of 93.7%, and an accuracy of 96.6% in discrimination between radiation necrosis and recurrence of tumor. F18-FDG-PET and DSC perfusion can reliably differentiate tumor recurrence from radiation necrosis, with early TBR showing the highest accuracy. ADC demonstrates a low sensitivity, specificity, and accuracy in differentiating radiation necrosis from recurrence. A combination of early TBR, delayed TBR, and rCBV may be more useful in discrimination between radiation necrosis and recurrence of glioma, with this combination showing a better diagnostic performance than individual parameters or any other combination of parameters.

The Diagnostic Role of Normalized and Mean Apparent Diffusion Coefficient in Differentiation between Pancreatic Lesions

Background: Diffusion-weighted magnetic resonance imaging (DWI) with quantification ofapparent diffusion coefficient (ADC) values is well established in the diagnosis of a variety of abdominal abnormalities. Regarding pancreatic disease, several investigators have shown that DWI with ADC measurement helps detect and characterize focal pancreatic lesions, as well as assess the severity of other pancreatic conditions. Objective: The study aimed to evaluate the diagnostic role of both normalized and mean apparent diffusion coefficient in discrimination between pancreatic lesions. Patients and Methods: Thirty-one participants presented with pancreatic lesions using clinical examination and ultrasound. Dynamic contrast MRI abdomen with diffusion-weighted MR imaging (DWI) on a 1.5-Tesla MRI machine was done. Mean ADC and normalized ADC (as the ratio of ADC of the lesion to the adjacent normal pancreas) were measured and compared. Results: Our study reported a mean ADC cut value of ≤1.47 while the cut-off value for normalized ADC was ≤ 0.96. Normalized ADC revealed a higher sensitivity 92.31%, specificity 88.89%, PPV 85.71, NPV 94.12%, accuracy 90.32%, positive likelihood ratio 8.31 and negative likelihood ratio 0.09 as compared to mean ADC, which revealed sensitivity 84.62%, specificity 77.78%, PPV 73.33%, NPV 87.5%, accuracy 80.65%, positive likelihood ratio 3.81 and negative likelihood ratio 0.2 respectively. Conclusion: Measuring the mean and normalized ADC value in pancreatic focal lesions can significantly differentiate between benign and malignant pancreatic lesions. However, normalized ADC has a higher sensitivity, specificity, PPV, and NPV than mean ADC value and could be used to differentiate between pancreatic lesions with higher accuracy than mean ADC.

Accuracy of apparent diffusion coefficient in differentiation of glioblastoma from metastasis.

Brain metastasis and glioblastoma multiforme are two of the most common malignant brain neoplasms. There are many difficulties in distinguishing these diseases from each other. The purpose of this study was to determine whether the mean apparent diffusion coefficient and absolute standard deviation derived from apparent diffusion coefficient measurements can be used to differentiate glioblastoma multiforme from brain metastasis based on cellularity levels. Magnetic resonance images of 34 patients with histologically verified brain tumors were evaluated retrospectively. Apparent diffusion coefficient and standard deviation values were measured in the enhancing tumor, peritumoral region, and contralateral healthy white matter. Then, to determine whether there was a statistical difference between brain metastasis and glioblastoma multiforme, we analyzed different variables between the two groups. Neither mean apparent diffusion coefficient values and ratios nor standard deviation values and ratios were significantly different between glioblastoma multiforme and brain metastasis. Receiver operating characteristic curve analysis of the logistic model with backward stepwise feature selection yielded an area under the curve of 0.77, a specificity of 84%, a sensitivity of 67%, a positive predictive value of 83.33%, and a negative predictive value of 78.26% for distinguishing between glioblastoma multiforme and brain metastasis. The absolute standard deviation and standard deviation ratios were significantly higher in the peritumoral edema compared to the tumor region in each case. Apparent diffusion coefficient values and ratios, as well as standard deviation values and ratios in peritumoral edema, cannot be used to differentiate edema with infiltration of tumor cells from vasogenic edema. However, standard deviation values could successfully characterize areas of peritumoral edema from the tumoral region in each case.

Characterization of small, deeply located soft-tissue tumors: Conventional magnetic resonance imaging features and apparent diffusion coefficient for differentiation between non-malignancy and malignancy.

ObjectivesTo compare magnetic resonance imaging (MRI) parameters of small, deeply located non-malignant and malignant soft-tissue tumors (STTs).MethodsBetween May 2011 and December 2017, 95 MRIs in 95 patients with pathologically proven STTs of small size (<5 cm) and deep location (66 non-malignant and 29 malignant) were identified. For qualitative parameters, consensus reading was performed by three radiologists for presence of necrosis, infiltration, lobulation, and the tail sign. Apparent diffusion coefficient (ADC) was analyzed by two other radiologists independently. Univariable and multivariable analyses were performed to determine the diagnostic performances of MRI parameters in differentiating non-malignancy and malignancy, and for non-myxoid, non-hemosiderin STTs and myxoid STTs as subgroups. Interobserver agreement for ADC measurement was calculated with the intraclass correlation coefficient.ResultsInterobserver agreement on ADC measurement was almost perfect. On univariable analysis, the malignant group showed a significantly larger size, lower ADC, and higher incidence of all qualitative MRI parameters for all STTs. Size (p = 0.012, odds ratio [OR] 2.57), ADC (p = 0.041, OR 3.85), and the tail sign (p = 0.009, OR 6.47) were independently significant on multivariable analysis. For non-myxoid, non-hemosiderin STTs, age, size, ADC, frequency of infiltration, lobulation, and the tail sign showed significant differences between non-malignancy and malignancy on univariable analysis. Only ADC (p = 0.032, OR 142.86) retained its independence on multivariable analysis. For myxoid STTs, only size and tail sign were significant on univariable analysis without independent significance.ConclusionsSize, ADC, and incidence of qualitative MRI parameters were significantly different between small, deeply located non-malignant and malignant STTs. Only ADC was independently significant for both overall analysis and the non-myxoid, non-hemosiderin subgroup.

Diagnostic test accuracy of ADC values for identification of clear cell renal cell carcinoma: systematic review and meta-analysis

To perform a systematic review on apparent diffusion coefficient (ADC) values of renal tumor subtypes and meta-analysis on the diagnostic performance of ADC for differentiation of localized clear cell renal cell carcinoma (ccRCC) from other renal tumor types. Medline, Embase, and the Cochrane Library databases were searched for studies published until May 1, 2019, that reported ADC values of renal tumors. Methodological quality was evaluated. For the meta-analysis on diagnostic test accuracy of ADC for differentiation of ccRCC from other renal lesions, we applied a bivariate random-effects model and compared two subgroups of ADC measurement with vs. without cystic and necrotic areas. We included 48 studies (2588 lesions) in the systematic review and 13 studies (1126 lesions) in the meta-analysis. There was no significant difference in ADC of renal parenchyma using b values of 0-800 vs. 0-1000 (p = 0.08). ADC measured on selected portions (sADC) excluding cystic and necrotic areas differed significantly from whole-lesion ADC (wADC) (p = 0.002). Compared to ccRCC, minimal-fat angiomyolipoma, papillary RCC, and chromophobe RCC showed significantly lower sADC while oncocytoma exhibited higher sADC. Summary estimates of sensitivity and specificity to differentiate ccRCC from other tumors were 80% (95% CI, 0.76-0.88) and 78% (95% CI, 0.64-0.89), respectively, for sADC and 77% (95% CI, 0.59-0.90) and 77% (95% CI, 0.69-0.86) for wADC. sADC offered a higher area under the receiver operating characteristic curve than wADC (0.852 vs. 0.785, p = 0.02). ADC values of kidney tumors that exclude cystic or necrotic areas more accurately differentiate ccRCC from other renal tumor types than whole-lesion ADC values. • Selective ADC of renal tumors, excluding cystic and necrotic areas, provides better discriminatory ability than whole-lesion ADC to differentiate clear cell RCC from other renal lesions, with area under the receiver operating characteristic curve (AUC) of 0.852 vs. 0.785, respectively (p = 0.02). • Selective ADC of renal masses provides moderate sensitivity and specificity of 80% and 78%, respectively, for differentiation of clear cell renal cell carcinoma (RCC) from papillary RCC, chromophobe RCC, oncocytoma, and minimal-fat angiomyolipoma. • Selective ADC excluding cystic and necrotic areas are preferable to whole-lesion ADC as an additional tool to multiphasic MRI to differentiate clear cell RCC from other renal lesions whether the highest b value is 800 or 1000.

The accuracy of pelvic magnetic resonance imaging in the diagnosis of ovarian malignancy in Iraqi patients in comparison with histopathology

Background: Ovarian malignancy is considered to score the highest fatality among women due to lack of significant symptoms. Early diagnosis and treatment lead to good prognosis. Magnetic resonance imaging (MRI) plays a major role in the diagnosis by detecting the lesions and assessing their appearance and consistency.&#x0D; Objective: To determine the accuracy of MRI in the diagnosis of ovarian malignancy and comparing this to histopathology as a gold standard test.&#x0D; Patients and methods: A follow up study was conducted in the MRI unit of the Radiology Department in Baghdad Teaching Hospital / Baghdad Medical City Complex during the period from 1st of February to 31st of December, 2017 on a group of thirty women with clinically suspected adnexal mass(es). All patients were examined with MRI including the diffusion-weighted imaging. Surgical specimens were taken for histopathology assessment.&#x0D; Results: A total of 30 women with adnexal mass were included in this study, with a mean age of 46.8±14.9 years. The MRI T1W image of the cystic part was dark in (60%), while the T2W image of the cystic part was bright (80%), T2W of the solid part was bright in (53.3%), T2W fat saturation of the solid part was bright in the majority (73.3%). T1W fat suppression contrast-enhanced of the solid part was avid in 66.7% of women with an adnexal mass; DWI of the solid part was bright in (76.7%). The mean apparent diffusion coefficient (ADC) value by MRI for women with adnexal mass was 0.9±0.3x103 mm2/sec. Histopathology mainly revealed mucinous cystadenocarcinoma in (10%) and low-grade serous adenocarcinoma in (10%).Validity of the results of MRI regarding malignant adnexal mass were sensitivity (90.9%), specificity (75%), +ve predictive value (90.9%), -ve predictive value (75%) and accuracy (86.6%). The appropriate cutoff value for apparent diffusion coefficient in differentiation between malignant and benign adnexal mass was 0.97 with 100% sensitivity and 90.9% specificity.&#x0D; Conclusions: MRI and diffusion-weighted imaging is a valid and reliable technique in the diagnosis and characterization of ovarian malignancy.

Apparent diffusion coefficient in differentiation between malignant and benign breast masses: does size matter?

To determine whether lesion size affects the diagnostic performance of apparent diffusion coefficient (ADC) in the evaluation of breast masses. Consecutive breast lesions detected at magnetic resonance imaging (MRI) from June 2010 to July 2013 were retrospectively reviewed. Differences in the ADCs of benign and malignant mass lesions were compared. Receiver operating characteristics analysis was performed to evaluate diagnostic performance of ADC regarding lesion size (≤ 1 cm or >1 cm) and their T2W signal intensities. Seventy-four malignant lesions (77.9%) and 21 (22.1%) benign lesions were included. Twenty-two of the 95 (23.2%) masses measured ≤ 1 cm (mean 0.73 ± 0.4; range 0.51-0.8 cm) and 73/95 (76.9%) masses measured >1 cm (mean 2.11 ± 0.1; range 1.1-3.3 cm). The mean ADC was significantly lower for malignant than for benign lesions (mean for malignant lesion, 0.89 ± 0.29 × 10(-3) mm(2)/s; mean for benign lesions, 1.27 ± 0.42 × 10(-3) mm(2)/s; p<0.01). The optimal ADC cut-off for differentiating benign and malignant lesion was 1.088 × 10(-3) mm(2)/s with a sensitivity of 85.9% and specificity of 77% for lesions >1 cm. The sensitivity and specificity were lowered to 60% and 50%, respectively, for lesions of size ≤ 1. Maximal sensitivity and specificity were reached when the ADC value was used to evaluate T2-dark lesions. Diffusion-weighted MRI is useful for characterizing masses that are hypointense on T2-weighted images. Lower sensitivity and specificity were found for breast lesions ≤ 1 cm.

Comparison of utility of tumor size and apparent diffusion coefficient for differentiation of low- and high-grade clear-cell renal cell carcinoma

There is a significant correlation between tumor size and tumor grade for clear-cell renal cell carcinoma (RCC) in pathology. Thus, apparent diffusion coefficient (ADC) of clear-cell RCC might be influenced by tumor size. To compare the utility of tumor size and ADC for distinguishing low-grade from high-grade clear-cell RCC. Forty-nine patients undergoing preoperative magnetic resonance imaging were retrospectively assessed. ADC values were calculated using b-value combinations of 0 and 800 s/mm(2) at 1.5 T. Two radiologists in consensus measured ADC values via small region of interest (ROI) (mean ROI area, 88.8 mm(2); range, 80-108 mm(2)) placement on an area of solid tumor on a single slice. Maximum tumor diameter was measured at the maximum tumor area. A single pathologist reviewed all pathological slides to determine the nuclear grade according to the Fuhrman classification. The utility of ADC, tumor size, and ADC/size ratio for distinguishing low-grade from high-grade tumors was assessed. Receiver-operating characteristic (ROC) analysis and regression analysis of the each index were performed. The correlation between ADC and tumor size was also investigated. The 49 clear-cell RCC included 34 low-grade and 15 high-grade tumors. The differences of ADC, tumor size, and ADC/size ratio between high-grade and low-grade tumors were statistically significant (P <0.05). The area under the ROC curve of ADC, tumor size, and ADC/size ratio were 0.802, 0.763, and 0.804 respectively. However, using regression analysis, only ADC (P <0.05) was statistically significant index as independent risk factors for high-grade clear-cell RCC. Moreover, weak significant correlation was observed between tumor size and ADC (R(2) = 0.3865, P <0.01). There was a weak significant correlation between tumor size and ADC value of clear-cell RCC. Using ROC and regression analysis, ADC was statistically significant index for distinguishing low-grade from high-grade clear-cell RCC more than tumor size and ADC/size ratio.

Application value of apparent diffusion coefficient in differentiation of brain radiation-injuries and glioma recurrence.

To evaluate application value of apparent diffusion coefficient (ADC) in differentiating brain radiation-injuries and glioma recurrence. Totally 23 patients [18 men and 5 women aged 32 to 67 years (mean: 47 years)] with previously resected and irradiated glioma were examined by using a 3.0T MR Scanner, including conventional and diffusion weighted image (DWI) sequences. All the cases were proved by pathology or clinical follow-up. Postprocessing of ADC maps was performed by using Functool software (AW 4.3, GE Healthcare), and the regions of interest (ROIs) were manually drawn on ADC maps in the area corresponding to the contrast-enhancing area on post-contrast axial T1-weighted images, avoiding the hemorrhage or necrosis. The ADC values were calculated automatically. ADC values were measured 10 times in order to reduce errors, and mean ADC value, maximum ADC value, and minimum ADC value were acquired. Both recurrent glioma and irradiated necrosis tended to have hemorrhage, necrosis, and edema. The mean ADC value and maximum ADC value were lower in the recurrent tumor group than in the radiation-injuries group, but no statistical difference was achieved. However, the minimum ADC value was significantly lower in the recurrent tumor group than in the radiation-injuries group (P=0.016). The minimum ADC value can be used as an useful tool in differentiating tumor recurrence from radiation-injuries.

Malignant Astrocytic Tumors: Clinical Importance of Apparent Diffusion Coefficient in Prediction of Grade and Prognosis

To retrospectively assess the apparent diffusion coefficient (ADC) for prediction of malignancy and prognosis of malignant astrocytic tumors. The institutional review board approved this study and did not require patient informed consent. Findings from 37 consecutive patients (21 men, 16 women; mean age, 43 years) with pathologically proved malignant astrocytic tumors that included 22 glioblastomas (GBMs) and 15 anaplastic astrocytomas (AAs) were retrospectively evaluated. The minimum ADC value of each tumor was preoperatively determined from several regions of interest defined in the tumor, preferably with avoidance of cystic or necrotic components, on ADC maps derived from isotropic diffusion-weighted images. Surgical intervention, followed by radiation therapy, was undertaken in all cases according to hospital protocol. Immunohistologically, Ki-67 labeling index (LI), indicating cell proliferation, was also determined. The patients were classified into two groups, progressive and stable, according to the 2-year observation after the initial treatment. Correlation analysis (Pearson product moment correlation), Student t test, Welch test, receiver operating characteristic analysis, and Kaplan-Meier method with log-rank test were used for statistical evaluation. There was a significant negative correlation between minimum ADC and Ki-67 LI (r = -0.562, P < .001). The mean minimum ADC (0.834 x 10(-3) mm2 x sec(-1)) of GBM was significantly lower than that (1.06 x 10(-3) mm2 x sec(-1)) of AA (P < .001, Student t test). The mean minimum ADC (0.80 x 10(-3) mm2 x sec(-1)) of the progressive group was significantly lower than that (1.037 x 10(-3) mm2 x sec(-1)) of the stable group (P < .001). The cutoff value of 0.90 x 10(-3) mm2 x sec(-1) for minimum ADC for differentiation of patients with a favorable prognosis from those with a poor prognosis provided the best combination of sensitivity (79%) and specificity (81%) (receiver operating characteristic analysis). The significant difference in the prognosis between two groups classified by using this cutoff value of minimum ADC was noted (P = .002, log-rank test). The minimum ADC of malignant astrocytomas can provide additional information about their clinical malignancy related to posttreatment prognosis.