EP-2024 Assessment of ADC value when comparing two methods to reduce geometrical distortion in DWMRI

Abstract Background There are many causes of pleural disease including variable benign and malignant etiologies. DWI is a non-enhanced functional MRI technique that allows qualitative and quantitative characterization of tissues based on their water molecules diffusivity. The aim of this study was to evaluate the diagnostic value of DWI-MRI in detection and characterization of pleural diseases and its capability in differentiating benign from malignant pleural lesions. Results Conventional MRI was able to discriminate benign from malignant lesions by using morphological features (contour and thickness) with sensitivity 89.29%, specificity 76%, positive predictive value 89%, negative predictive value 76.92%, and accuracy 85.37%. ADC value as a quantitative parameter of DWI found that ADC values of malignant pleural diseases were significantly lower than that of benign lesions (P < 0.001). Hence, we discovered that using ADC mean value of 1.68 × 10-3 mm2/s as a cutoff value can differentiate malignant from benign pleural diseases with sensitivity 89.3%, specificity 100%, positive predictive value 100%, negative predictive value 81.2%, and accuracy 92.68% (P < 0.001). Conclusion Although DWI-MRI is unable to differentiate between malignant and benign pleural effusion, its combined morphological and functional information provide valid non-invasive method to accurately characterize pleural soft tissue diseases differentiating benign from malignant lesions with higher specificity and accuracy than conventional MRI.

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Baseline apparent diffusion coefficients: Validation study of new predictor of survival in patients with unresectable hepatocellular carcinoma following chemoembolization

Journal of X-Ray Science and Technology ◽

10.3233/xst-200827 ◽

2021 ◽

pp. 1-10

Author(s):

Lichao Xu ◽

Shiqin Wang ◽

Shengping Wang ◽

Ying Wang ◽

Wentao Li ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Roc Curve ◽

Cox Regression ◽

Response To Treatment ◽

Roc Curve Analysis ◽

Adc Value ◽

Apparent Diffusion Coefficients ◽

Apparent Diffusion ◽

Response Biomarker ◽

The Difference

OBJECTIVES: To investigate whether the baseline apparent diffusion coefficient (ADC) can predict survival in the hepatocellular carcinoma (HCC) patients receiving chemoembolization. MATERIALS AND METHODS: Diffusion-weighted MR imaging of HCC patients is performed within 2 weeks before chemoembolization. The ADC of the largest index lesion is recorded. Responses are assessed by mRECIST after the start of the second course of chemoembolization. Receiver operating characteristic (ROC) curve analysis is performed to evaluate the diagnostic performance and determine optimal cut-off values. Cox regression and Kaplan–Meier survival analyses are used to explore the differences in overall survival (OS) between the responders and non-responders. RESULTS: The difference is statistically significant in the baseline ADC between the responders and non-responders (P < 0.001). ROC analyses indicate that the baseline ADC value is a good predictor of response to treatment with an area under the ROC curve (AUC) of 0.744 and the optimal cut-off value of 1.22×10–3 mm2/s. The Cox regression model shows that the baseline ADC is an independent predictor of OS, with a 57.2% reduction in risk. CONCLUSION: An optimal baseline ADC value is a functional imaging response biomarker that has higher discriminatory power to predict tumor response and prolonged survival following chemoembolization in HCC patients.

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Quantitative 3-tesla multiparametric MRI in differentiation between renal cell carcinoma subtypes

Egyptian Journal of Radiology and Nuclear Medicine ◽

10.1186/s43055-020-00405-w ◽

2021 ◽

Vol 52 (1) ◽

Author(s):

Ali Elsorougy ◽

Hashim Farg ◽

Dalia Bayoumi ◽

Mohamed Abou El-Ghar ◽

Magda Shady

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Multiparametric Mri ◽

Histopathological Analysis ◽

Adc Value ◽

Intensity Index ◽

Apparent Diffusion ◽

The Mean

Abstract Background MRI provides several distinct quantitative parameters that may better differentiate renal cell carcinoma (RCC) subtypes. The purpose of the study is to evaluate the diagnostic accuracy of apparent diffusion coefficient (ADC), chemical shift signal intensity index (SII), and contrast enhancement in differentiation between different subtypes of renal cell carcinoma. Results There were 63 RCC as regard surgical histopathological analysis: 43 clear cell (ccRCC), 12 papillary (pRCC), and 8 chromophobe (cbRCC). The mean ADC ratio for ccRCC (0.75 ± 0.13) was significantly higher than that of pRCC (0.46 ± 0.12, P < 0.001) and cbRCC (0.41 ± 0.15, P < 0.001). The mean ADC value for ccRCC (1.56 ± 0.27 × 10−3 mm2/s) was significantly higher than that of pRCC (0.96 ± 0.25 × 10−3 mm2/s, P < 0.001) and cbRCC (0.89 ± 0.29 × 10−3 mm2/s, P < 0.001). The mean SII of pRCC (1.49 ± 0.04) was significantly higher than that of ccRCC (0.93 ± 0.01, P < 0.001) and cbRCC (1.01 ± 0.16, P < 0.001). The ccRCC absolute corticomedullary enhancement (196.7 ± 81.6) was significantly greater than that of cbRCC (177.8 ± 77.7, P < 0.001) and pRCC (164.3 ± 84.6, P < 0.001). Conclusion Our study demonstrated that multiparametric MRI is able to afford some quantitative features such as ADC ratio, SII, and absolute corticomedullary enhancement which can be used to accurately distinguish different subtypes of renal cell carcinoma.

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Role of Quantitative Diffusion-Weighted Imaging in Differentiating Benign and Malignant Orbital Masses

Indian Journal of Radiology and Imaging ◽

10.1055/s-0041-1730120 ◽

2021 ◽

Author(s):

Preeti Mundhada ◽

Sudarshan Rawat ◽

Ullas Acharya ◽

Dhananjay Raje

Keyword(s):

Roc Curve ◽

Diffusion Weighted Imaging ◽

Care Hospital ◽

Adc Value ◽

Diffusion Weighted ◽

Significant Difference ◽

Orbital Masses ◽

Adc Values ◽

Orbital Lesions

Abstract Aim To determine the role of diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) values in differentiating benign and malignant orbital masses. Materials and Methods After obtaining institutional ethical board approval and informed consent from all patients, an observational study was done for a period of 24 months in the radiology department of a tertiary care hospital in South India. Conventional magnetic resonance imaging and DWI using a 3T scanner was done for all patients with suspected orbital mass lesion. ADC value and clinicohistopathological correlation were studied for every patient. Chi-square test was used to compare the signal characteristics of DWI and ADC maps between benign and malignant lesions. A comparison of mean ADC values for benign and malignant masses was performed using Student’s t-test for independent samples. The cut-off value for ADC was obtained using the receiver operating characteristic (ROC) curve. Results Of 44 patients with orbital lesions, 70% were benign and 30% were malignant. There was a significant difference in the mean ADC values of benign and malignant orbital masses. Using ROC curve analysis, an optimal ADC threshold of 1.26 × 10−3 mm2/s was calculated for the prediction of malignancy with 100% sensitivity, 80.65% specificity, and 86.36% accuracy (95% confidence interval: 0.872, 1.00, p < 0.0001). Two ADC thresholds were used to characterize the orbital masses with more than 90% confidence. Conclusion Quantitative assessment of ADC is a useful noninvasive diagnostic tool for differentiating benign and malignant orbital masses. Malignant orbital lesions demonstrate significantly lower ADC values as compared with benign lesions.

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Correlative study between ADC value and grading of invasive breast cancer

Egyptian Journal of Radiology and Nuclear Medicine ◽

10.1186/s43055-019-0124-6 ◽

2020 ◽

Vol 51 (1) ◽

Author(s):

Heba Azzam ◽

Sahar Mansour ◽

Noha Salem ◽

Hany El-Assaly

Keyword(s):

Breast Cancer ◽

Invasive Breast Cancer ◽

Adc Value ◽

Correlative Study

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MRI Spectrum of Japanese Encephalitis in Northeast India: A Cross-Sectional Study

Journal of Neurosciences in Rural Practice ◽

10.1055/s-0041-1722820 ◽

2021 ◽

Vol 12 (02) ◽

pp. 281-289

Author(s):

Pranjal Phukan ◽

Kalyan Sarma ◽

Barun Kumar Sharma ◽

Deb K. Boruah ◽

Bidyut Bikash Gogoi ◽

...

Keyword(s):

Japanese Encephalitis ◽

Statistical Significance ◽

Tertiary Care ◽

Care Hospital ◽

Mri Findings ◽

Mri Scan ◽

Cross Sectional ◽

Adc Value ◽

Group 2 ◽

Group 1

Abstract Objective Japanese encephalitis (JE) is an arthropod-borne flavivirus infection having high mortality and morbidity. This study was performed to evaluate the conventional magnetic resonance imaging (MRI) findings in JE and to find out any difference between pediatric and adult JE. Materials and Methods This retrospective study was performed on serologically positive 54 JE patients presented to a tertiary care hospital with acute encephalitic symptoms between April 2016 and October 2019. Relevant neurological examination, cerebrospinal fluid analysis, and MRI scan of the brain were performed. Results Fifty-four JE patients (n = 31 males and n = 23 females) having 32 pediatric and 22 adult JE were included in the study sample. Group 1 JE (n = 16) patients had encephalitic symptoms with duration less than 15 days up to the day of MRI scan and group 2 JE (n = 38) had symptoms more than 15 days. Group 1 JE had mean apparent diffusion coefficient (ADC) value of 0.563 ± 0.109 (standard deviation [SD]) × 10–3 mm2/sec and group 2 JE had 1.095 ± 0.206 (SD) × 10–3 mm2/sec. The mean ADC value of pediatric JE was 0.907 ± 0.336 (SD) × 10–3 mm2/sec and adult JE was 0.982 ± 0.253 (SD) × 10–3 mm2/sec. Conclusion The majority of the JE patient shows abnormal signal alterations in bilateral thalami and substantia nigra. Diffusion-weighted imaging with ADC mapping helps in evaluating the stage of the JE. No statistical significance of the various conventional MRI findings was found between the pediatric JE and adult JE.

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Multiple b values of diffusion-weighted magnetic resonance imaging in evaluation of solid head and neck masses

Egyptian Journal of Radiology and Nuclear Medicine ◽

10.1186/s43055-019-0054-3 ◽

2019 ◽

Vol 50 (1) ◽

Cited By ~ 1

Author(s):

Rania Sobhy Abou khadrah ◽

Haytham Haroon Imam

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Head And Neck ◽

Resonance Imaging ◽

Adc Value ◽

Neck Masses ◽

Adc Values ◽

Weighted Magnetic Resonance Imaging ◽

The Mean ◽

Head And Neck Masses

Abstract Background Differentiation between malignant and benign masses is essential for treatment planning and helps in improving the prognosis of malignant tumors; the aim of this work is to determine the role of diffusion-weighted magnetic resonance imaging (DW-MRI) and the apparent diffusion coefficient (ADC) in the differentiation between benign and malignant solid head and neck masses by comparing diagnostic performance of low b values (0.50 and 400 s/mm2) versus high b values (800 and 1000 s/mm2) and comparing the result with histopathological finding. Results The study included 60 patients (34 male and 26 female) with solid head and neck masses > 1 cm who referred to radiodiagnosis department for MRI evaluation. Multiple b values were used 50, 400, 800, and 1000 s/mm2 (at least 2 b values). DWI and ADC value of all 60 patients were acquired. Mean ADC values of both malignant and benign masses were statistically measured and compared, and cut off value was determined. Solid head and neck masses in our study DWI with the use of high b value 800 and 1000 s/mm2 were of higher significance (P value 0.001*). There was a significant difference in the mean ADC value between benign and malignant masses (P < 0.01); solid masses were divided into 2 categories: (a) malignant lesions 46.7% (n = 28) with mean ADC value (0.82 ± 0.19) × 10−3 s/mm2 and (b) benign lesions 53.3% (n = 32) with mean ADC value (2.05 ± 0.46) × 10−3 s/mm2) with ADC cutoff value of 1.0 × 10−3 s/mm2 and 94% sensitivity, 93% specificity, negative predictive value (NPV) = 94%, positive predictive value (PPV) 93%, and an accuracy of 93.5%. Conclusion The DWI with ADC mapping were valuable as non-invasive tools in differentiating between benign and malignant solid head and neck masses. The use of high b value 800 and 1000 s/mm2 was of higher significance (P value 0.001*) in differentiation between benign and malignant lesion than that with low b values 0, 50, and 400 s/mm2 (0.01). The mean ADC values were significantly lower in malignant solid masses. Attention had to be paid to the choice of b values in MRI-DWI in the head and neck region.

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Can mean ADC value and ADC ratio of benign prostate tissue to prostate cancer assist in the prediction of clinically significant prostate cancer within the PI-RADSv2 scoring system?

Egyptian Journal of Radiology and Nuclear Medicine ◽

10.1186/s43055-020-00347-3 ◽

2020 ◽

Vol 51 (1) ◽

Author(s):

Samar Ramzy Ragheb ◽

Reem Hassan Bassiouny

Keyword(s):

Prostate Cancer ◽

Sensitivity And Specificity ◽

Gleason Score ◽

Treatment Strategies ◽

Serum Levels ◽

Prostatic Tissue ◽

Histopathological Analysis ◽

Adc Value ◽

The Mean ◽

Clinically Significant

Abstract Background The aim of this study is to investigate whether quantitative DW metrics can provide additive value to the reliable categorization of lesions within existing PI-RADSv2 guidelines. Fifty-eight patients with clinically suspicious prostate cancer who underwent PR examination, PSA serum levels, sextant TRUS-guided biopsies, and bi-parametric MR imaging were included in the study. Results Sixty-six lesions were detected by histopathological analysis of surgical specimens. The mean ADC values were significantly lower in tumor than non-tumor tissue. The mean ADC value inversely correlated with Gleason score of tumors with a significant p value < 0.001.Conversely, a positive relationship was found between the ADC ratio (ADC of benign prostatic tissue to prostate cancer) and the pathologic Gleason score with a significant elevation of the ADC ratio along with an increase of the pathologic Gleason score (p < 0.001). ROC curves constructed for the tumor ADC and ADC ratio helped to distinguish pathologically aggressive (Gleason score ≥ 7) from non-aggressive (Gleason score ≤ 6) tumors and to correlate it with PIRADSv2 scoring to predict the presence of clinically significant PCA (PIRADSv2 DW ≥ 4). The ability of the tumor ADC and ADC ratio to predict highly aggressive tumors (GS> 7) was high (AUC for ADC and ADC ratio, 0.946 and 0.897; p = 0.014 and 0.039, respectively). The ADC cut-off value for GS ≥ 7 was < 0.7725 and for GS ≤ 6 was > 0.8620 with sensitivity and specificity 97 and 94%. The cutoff ADC ratio for predicting (GS > 7) was 1.42 and for GS ≤ 6 was > 1.320 with sensitivity and specificity 97 and 92%. By applying this ADC ratio cut-off value the sensitivity and specificity of reader 1 for correct categorization of PIRADSv2 DW > 4 increased from 90 and 68% to 95 and 90% and that of reader 2 increased from 94 and 88% to 97 and 92%, respectively. Conclusion Estimation of DW metrics (ADC and ADC ratio between benign prostatic tissue and prostate cancer) allow the non-invasive assessment of biological aggressiveness of prostate cancer and allow reliable application of the PIRADSv2 scoring to determine clinically significant cancer (DW score > 4) which may contribute in planning initial treatment strategies.

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Apparent diffusion coefficient cannot discriminate metastatic and non-metastatic lymph nodes in rectal cancer: a meta-analysis

International Journal of Colorectal Disease ◽

10.1007/s00384-021-03986-8 ◽

2021 ◽

Author(s):

Alexey Surov ◽

Hans-Jonas Meyer ◽

Maciej Pech ◽

Maciej Powerski ◽

Jasan Omari ◽

...

Keyword(s):

Rectal Cancer ◽

Diffusion Coefficient ◽

Apparent Diffusion Coefficient ◽

Lymph Nodes ◽

Meta Analysis ◽

Adc Value ◽

Metastatic Lymph Nodes ◽

Metastatic Lymph ◽

Apparent Diffusion ◽

Adc Values

Abstract Background Our aim was to provide data regarding use of diffusion-weighted imaging (DWI) for distinguishing metastatic and non-metastatic lymph nodes (LN) in rectal cancer. Methods MEDLINE library, EMBASE, and SCOPUS database were screened for associations between DWI and metastatic and non-metastatic LN in rectal cancer up to February 2021. Overall, 9 studies were included into the analysis. Number, mean value, and standard deviation of DWI parameters including apparent diffusion coefficient (ADC) values of metastatic and non-metastatic LN were extracted from the literature. The methodological quality of the studies was investigated according to the QUADAS-2 assessment. The meta-analysis was undertaken by using RevMan 5.3 software. DerSimonian, and Laird random-effects models with inverse-variance weights were used to account the heterogeneity between the studies. Mean DWI values including 95% confidence intervals were calculated for metastatic and non-metastatic LN. Results ADC values were reported for 1376 LN, 623 (45.3%) metastatic LN, and 754 (54.7%) non-metastatic LN. The calculated mean ADC value (× 10−3 mm2/s) of metastatic LN was 1.05, 95%CI (0.94, 1.15). The calculated mean ADC value of the non-metastatic LN was 1.17, 95%CI (1.01, 1.33). The calculated sensitivity and specificity were 0.81, 95%CI (0.74, 0.89) and 0.67, 95%CI (0.54, 0.79). Conclusion No reliable ADC threshold can be recommended for distinguishing of metastatic and non-metastatic LN in rectal cancer.

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