Dataset Information

Apparent Diffusion Coefficient (ADC) value: a potential imaging biomarker that reflects the biological features of rectal cancer.

ABSTRACT:

Objective

We elected to analyze the correlation between the pre-treatment apparent diffusion coefficient (ADC) and the clinical, histological, and immunohistochemical status of rectal cancers.

Materials and methods

Forty-nine rectal cancer patients who received surgical resection without neoadjuvant therapy were selected that underwent primary MRI and diffusion-weighted imaging (DWI). Tumor ADC values were determined and analyzed to identify any correlations between these values and pre-treatment CEA or CA19-9 levels, and/or the histological and immunohistochemical properties of the tumor.

Results

Inter-observer agreement of confidence levels from two separate observers was suitable for ADC measurement (k ?=? 0.775). The pre-treatment ADC values of different T stage tumors were not equal (p ?=? 0.003). The overall trend was that higher T stage values correlated with lower ADC values. ADC values were also significantly lower for the following conditions: tumors with the presence of extranodal tumor deposits (p ?=? 0.006) and tumors with CA19-9 levels ? 35 g/ml (p ?=? 0.006). There was a negative correlation between Ki-67 LI and the ADC value (r ?=? -0.318, p ?=? 0.026) and between the AgNOR count and the ADC value (r ?=? -0.310, p ?=? 0.030).

Conclusion

Significant correlations were found between the pre-treatment ADC values and T stage, extranodal tumor deposits, CA19-9 levels, Ki-67 LI, and AgNOR counts in our study. Lower ADC values were associated with more aggressive tumor behavior. Therefore, the ADC value may represent a useful biomarker for assessing the biological features and possible relationship to the status of identified rectal cancers.

SUBMITTER: Sun Y

PROVIDER: S-EPMC4193754 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Apparent Diffusion Coefficient (ADC) value: a potential imaging biomarker that reflects the biological features of rectal cancer.

Sun Yiqun Y Tong Tong T Cai Sanjun S Bi Rui R Xin Chao C Gu Yajia Y

PloS one 20141010 10

<h4>Objective</h4>We elected to analyze the correlation between the pre-treatment apparent diffusion coefficient (ADC) and the clinical, histological, and immunohistochemical status of rectal cancers.<h4>Materials and methods</h4>Forty-nine rectal cancer patients who received surgical resection without neoadjuvant therapy were selected that underwent primary MRI and diffusion-weighted imaging (DWI). Tumor ADC values were determined and analyzed to identify any correlations between these values a ...[more]

PMID: 25303288

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Project description:ObjectivesWe undertook a systematic review and meta-analysis of the diagnostic performance of mean apparent diffusion coefficient (ADC) values derived by diffusion-weighted (DW)-MRI in the characterization of solid benign and malignant liver lesions, and to assess their value in discriminating these lesions in daily routine practice.MethodsA systematic review of PubMed, Embase, Scopus, and Web of Science was conducted to retrieve studies that used ADC values for differentiating solid benign/dysplastic nodules and malignant liver lesions. A bivariate random-effects model with pooled sensitivity and specificity values with 95% CI (confidence interval) was used. This meta-analysis was performed on the per-lesion basis. Summary receiver operating characteristic (SROC) plot and area under curve (AUC) were created.ResultsA total of 14 original articles were retrieved. The combined (95% CI) sensitivity and specificity of mean ADC values for differentiating solid benign from malignant lesions were 78% (67-86%) and 74% (64-81%), respectively. The pooled (95% CI) positive and negative LRs were respectively 3 (2.3-3.8) and 0.3 (0.21-0.43). The DOR (95% CI) was 10 (7-15). The AUC (95% CI) of the SROC plot was 82% (78-85%). Reporting bias was negligible (p value of regression test = 0.36). Mean size of malignant lesions and breathing pattern of MRI were found to be sources of heterogeneity of pooled sensitivity.ConclusionADC measurement independently may not be an optimal diagnostic imaging method for differentiating solid malignant from solid benign hepatic lesions. The meta-analysis showed that ADC measurement had moderate diagnostic accuracy for characterizing solid liver lesions. Further prospective and comparative studies with pre-specified ADC thresholds could be performed to investigate the best MRI protocol and ADC threshold for characterizing solid liver lesions.Advances in knowledgeADC measurement by DW-MRI does not have a good diagnostic performance to differentiate solid malignant from solid benign lesions. Therefore, we suggest not using ADC values in clinical practice to evaluate solid liver lesions.

Project description:BackgroundBrain metastases are particularly common in patients with small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), with NSCLC showing a less aggressive clinical course and lower chemo- and radio sensitivity compared to SCLC. Early adequate therapy is highly desirable and depends on a reliable classification of tumor type. The apparent diffusion coefficient is a noninvasive neuroimaging marker with the potential to differentiate between major histological subtypes. Here we determine the sensitivity and specificity of the apparent diffusion coefficient to distinguish between NSCLC and SCLC.MethodsWe enrolled all NSCLC and SCLC patients diagnosed between 2008 and 2019 at the University Medical Center Göttingen. Cranial MR scans were visually inspected for brain metastases and the ratio of the apparent diffusion coefficient (ADC) was calculated by dividing the ADC measured within the solid part of a metastasis by a reference ADC extracted from an equivalent region in unaffected tissue on the contralateral hemisphere.ResultsOut of 411 enrolled patients, we detected 129 patients (83 NSCLC, 46 SCLC) with sufficiently large brain metastases with histologically classified lung cancer and no hemorrhage. We analyzed 185 brain metastases, 84 of SCLC and 101 of NSCLC. SCLC brain metastases showed an ADC ratio of 0.68 ± 0.12 SD, and NSCLC brain metastases showed an ADC ratio of 1.47 ± 0.31 SD. Receiver operating curve statistics differentiated brain metastases of NSCLC from SCLC with an area under the curve of 0.99 and a 95% CI of 0.98 to 1, p < 0.001. Youden's J cut-point is 0.97 at a sensitivity of 0.989 and a specificity of 0.988.ConclusionsIn patients with lung cancer and brain metastases with solid tumor parts, ADC ratio enables an ad hoc differentiation of SCLC and NSCLC, easily achieved during routine neuroradiological examination. Non-invasive MR imaging enables an early-individualized management of brain metastases from lung cancer.Trial registrationThe study was registered in the German Clinical Trials Register (DRKS00023016).

Project description:ObjectiveTo evaluate the predictive value of the apparent diffusion coefficient (ADC) for pathologic complete response (pCR) to neoadjuvant chemoradiotherapy (NCRT) in locally advanced rectal cancer.MethodsA total of 265 patients with rectal adenocarcinoma, whole Diffusion-Weighted MRI (DWI-MRI) images, clinically stage II to III (cT3-4 and/or cN+) and treated with NCRT followed by TME were screened. Fifty patients with pCR and another 50 patients without pCR with similar clinical charcacters and treatment regimens were selected for statistical analysis. All the patients' pre-CRT and post-CRT average ADC values were calculated from the coefficient maps created by DWI-MRI and recorded independently. The difference in the ADC values between the pCR and non-pCR was analyzed by the Mann-Whitney U test. The cut-off ADC value of the receiver operating characteristic (ROC) curve with pCR was then established.ResultsThe mean pre- and post-ADC values in all patients, and in pCR patients and non-pCR patients were 0.879±0.06 and 1.383±0.11, 0.859±0.04 and 1.440±0.10, 0.899±0.07 and 1.325±0.09 (×10(-3) mm(2)/s), respectively. The difference between the pre- and post-ADC values in all patients, pCR patients, and non-pCR patients were considered to be statistically significant. The pre-ADC value was significantly lower in the pCR patients than in the non-pCR patients (p = 0.003), whereas the post-ADC values were significantly higher in the pCR patients than in the non-pCR patients. The percentage increase of the ADC value (?ADC%) in the pCR and non-pCR patients were 68% and 48% respectively (p<0.001). The ROC curves of the cut-off value of the pre-CRT patient ADC value was 0.866×10(-3) mm(2)/s. The AUC, sensitivity, specificity, PPV, NPV, and accuracy of diagnosing pCR were 0.670 (95% CI 0.563-0.777), 0.600, 0.640, 60%, 60%, and 60%, respectively. The cut-off value of ?ADC% was 58%. The corresponding AUC, sensitivity, specificity, PPV, NPV, and accuracy of diagnosing pCR were 0.856 (95% CI 0.783-0.930), 0.800, 0.760, 76.9%, 79.2%, and 78%, respectively.ConclusionsDWI-MRI technology can be efficient for predicting pCR for LARC after NCRT. Although the mean pre-CRT ADC value and the ?ADC% are moderate predictors for pCR, the latter would be more accurate.

Project description:ObjectivesTo develop an intuitive and generally applicable system for the reporting, assessment, and documentation of ADC to complement standard BI-RADS criteria.MethodsThis was a multicentric, retrospective analysis of 11 independently conducted institutional review board-approved studies from seven institutions performed between 2007 and 2019. Breast Apparent Diffusion coefficient (ADC-B) categories comprised ADC-B0 (ADC non-diagnostic), ADC-B1 (no enhancing lesion), and ADC-B2-5. The latter was defined by plotting ADC versus cumulative malignancy rates. Statistics comprised ANOVA with post hoc testing and ROC analysis. p values ≤ 0.05 were considered statistically significant.ResultsA total of 1625 patients (age: 55.9 years (± 13.8)) with 1736 pathologically verified breast lesions were included. The mean ADC (× 10-3 mm2/s) differed significantly between benign (1.45, SD .40) and malignant lesions (.95, SD .39), and between invasive (.92, SD .22) and in situ carcinomas (1.18, SD .30) (p < .001). The following ADC-B categories were identified: ADC-B0-ADC cannot be assessed; ADC-B1-no contrast-enhancing lesion; ADC-B2-ADC ≥ 1.9 (cumulative malignancy rate < 0.1%); ADC-B3-ADC 1.5 to < 1.9 (0.1-1.7%); ADC-B4-ADC 1.0 to < 1.5 (10-24.5%); and ADC-B5-ADC < 1.0 (> 24.5%). At the latter threshold, a positive predictive value of 95.8% (95% CI 0.94-0.97) for invasive versus non-invasive breast carcinomas was reached.ConclusionsThe breast apparent diffusion coefficient system (ADC-B) provides a simple and widely applicable categorization scheme for assessment, documentation, and reporting of apparent diffusion coefficient values in contrast-enhancing breast lesions on MRI.Clinical relevance statementThe ADC-B system, based on diverse MRI examinations, is clinically relevant for stratifying breast cancer risk via apparent diffusion coefficient measurements, and complements BI-RADS for improved clinical decision-making and patient outcomes.Key points• The breast apparent diffusion coefficient category system (ADC-B) is a simple tool for the assessment, documentation, and reporting of ADC values in contrast-enhancing breast lesions on MRI. • The categories comprise ADC-B0 for non-diagnostic examinations, ADC-B1 for examinations without an enhancing lesion, and ADC-B2-5 for enhancing lesions with an increasing malignancy rate. • The breast apparent diffusion coefficient category system may be used to complement BI-RADS in clinical decision-making.

Dataset Information

Apparent Diffusion Coefficient (ADC) value: a potential imaging biomarker that reflects the biological features of rectal cancer.

Objective

Materials and methods

Results

Conclusion

Publications

Apparent Diffusion Coefficient (ADC) value: a potential imaging biomarker that reflects the biological features of rectal cancer.

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