Role Of Apparent Diffusion Coefficient Research Articles

Differentiation of solid and friable tumour thrombus in patients with renal cell carcinoma: The role of MRI apparent diffusion coefficient

PurposeInferior vena cava (IVC) involvement by renal cell carcinoma (RCC) is associated with a higher disease stage and is considered a risk factor for poor prognosis. This study aimed to investigate the role of the apparent diffusion coefficient (ADC) of MRI 3D texture analysis in the differentiation of solid and friable tumour thrombus in patients with RCC. Materials and methodsThe study involved 27 patients with RCC with tumour thrombus in the renal vein or IVC, surgically treated with nephrectomy and thrombectomy and in whom preoperatively abdominal MRI including the DWI sequence was conducted. For 3D texture analysis, the ADC map was used, and the first-order radiomic features were calculated from the whole volume of the thrombus. All tumour thrombi were histologically classified as solid or friable. ResultsThe solid and friable thrombus was detected in 51.9 ​% and 48.1 ​% of patients, respectively. No differences in mean values of range, 90th percentile, interquartile range, kurtosis, uniformity and variance were found between groups. Equal sensitivity and specificity (93 ​% and 69 ​%, respectively) of ADC mean, median and entropy in differentiation between solid and friable tumour thrombus, with the highest AUC for entropy (0.808), were observed. Applying the skewness threshold value of 0.09 allowed us to achieve a sensitivity of 86 ​% and a specificity of 92 ​%. ConclusionsIn patients with RCC and tumour thrombus in the renal vein or IVC, the 3D texture analysis based on ADC-map allows for precise differentiation of a solid from a friable thrombus.

Correlation of ADC values of adult brain tumors with the diagnosis and pathological grade: A cross-sectional multicenter study.

Brain tumors are common, requiring physicians to have a precise understanding of them for accurate diagnosis and treatment. Considering that various histological tumor types present different cellularity, we conducted this research to examine the role of apparent diffusion coefficient (ADC) values in the differential diagnosis and pathologic grading of brain tumor types. In this cross-sectional study, we gathered pathology reports of histological samples of adult brain tumors. The tissue sample of brain tumors were examined histologically by a pathologist. The magnetic resonance imaging data of these patients were interpreted by a neuroradiologist. The measured ADC values and ADC ratios were calculated. Standard mean ADC values were expressed as 10- 6 mm2/s. The findings were compared according to the histological diagnosis of each tumor. Sixty-eight patients were included in the study: 34 (50%) were male, and 34 (50%) were female. The average age of the patients was 51.69 + 16.40 years. In the examination of tumor type, 16 (23.5%) were astrocytoma, 9 (13.2%) were oligodendroglioma, 20 (29.4%) were glioblastoma, 4 (5.9%) were medulloblastoma, and 19 (27.9%) were metastatic tumors. the average value of ADC was statistically significantly different according to the pathological type of tumor (p < 0.001). The two-by-two comparison of average ADC among tumor types revealed significant differences, except for oligodendroglioma and glioblastoma (p-value = 0.87) and glioblastoma and medulloblastoma (p-value = 0.347). The average value of ADC and ADC ratio was statistically significantly different according to the pathological grade of the tumor (p < 0.001). In the two-by-two comparison of average ADC between all pathological grades of the tumor showed a significance difference except for Grade I and Grade II (p-value = 0.355). The mean value of ADC and ADC ratio for glioblastoma and metastatic tumors showed no significant difference. The assessment of brain tumor grade through ADC examination will help to estimate prognosis and devising suitable therapeutic strategies.

The role of apparent diffusion coefficient in the grading of adult isocitrate dehydrogenase-mutant astrocytomas: relationship with the Ki-67 proliferation index.

The grading of adult isocitrate dehydrogenase (IDH)-mutant astrocytomas is a crucial prognostic factor. To investigate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) in the grading of adult IDH-mutant astrocytomas, and to analyze the correlation between ADC and the Ki-67 proliferation index. The clinical and MRI data of 82 patients with adult IDH-mutant astrocytoma who underwent surgical resection and molecular genetic testing with IDH and 1p/19q were retrospectively analyzed. The conventional MRI features, ADCmin, ADCmean, and nADC of the tumors were compared using the Kruskal-Wallis single factor ANOVA and chi-square tests. Receiver operating characteristic (ROC) curves were drawn to evaluate conventional MRI and ADC accuracy in differentiating tumor grades. Pearson correlation analysis was performed to determine the correlation between ADC and the Ki-67 proliferation index. The difference in enhancement, ADCmin, ADCmean, and nADC among WHO grade 2, 3, and 4 tumors was statistically significant (all P <0.05). ADCmin showed the preferable diagnostic accuracy for grading WHO grade 2 and 3 tumors (AUC=0.724, sensitivity=63.4%, specificity=80%, positive predictive value (PPV)=62.0%; negative predictive value (NPV)=82.5%), and distinguishing grade 3 from grade 4 tumors (AUC=0.764, sensitivity=70%, specificity=76.2%, PPV=75.0%, NPV=71.4%). Enhancement + ADC model showed an optimal predictive accuracy (grade 2 vs. 3: AUC = 0.759; grade 3 vs. 4: AUC = 0.799). The Ki-67 proliferation index was negatively correlated with ADCmin, ADCmean, and nADC (all P <0.05), and positively correlated with tumor grade. Conventional MRI features and ADC are valuable to predict pathological grading of adult IDH-mutant astrocytomas.

Apparent diffusion coefficient histogram analysis for differentiating fibroblastic meningiomas from non-fibroblastic WHO grade 1 meningiomas

PurposeTo investigate the role of apparent diffusion coefficient (ADC) histogram analysis in differentiating fibroblastic meningiomas (FM) from non-fibroblastic WHO grade 1 meningiomas (nFM). MethodsThis retrospective study analyzed the histopathological and diagnostic imaging data of 220 patients with histopathologically confirmed FM and nFM. The whole tumors were delineated on axial ADC images, and histogram parameters (mean, variance, skewness, kurtosis, as well as the 1st, 10th, 50th, 90th, and 99th percentile ADC [ADCp1, ADCp10, ADCp50, ADCp90, and ADCp99, respectively]) were obtained. Multivariate logistic regression analysis was used to identify the most valuable variables for discriminating FM from nFM WHO grade 1 meningiomas, and their diagnostic efficacy in differentiating FM from nFM before surgery was assessed using receiver operating characteristic (ROC) curves. ResultsThe mean, variance, ADCp50, ADCp90, and ADCp99 of the FM group were all lower than those of the nFM group (P < 0.05), there was significant difference in location and sex (P < 0.05). Multivariate logistic regression showed ADCp99 (P < 0.001) and location (P = 0.007) were the most valuable parameters in the discrimination of FM and nFM WHO grade 1 meningiomas. The diagnostic efficacy was achieved an AUC of 0.817(95% CI, 0.759–0.866), the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 66.4%, 83.6%, 75.0%, 80.2%, and 71.3%, respectively. ConclusionADC histogram analysis is helpful in noninvasive differentiation of FM and nFM WHO grade 1 meningiomas, and combined ADCp99 and location have the best diagnostic efficacy.

ADC histogram parameters differentiating atypical from transitional meningiomas: correlation with Ki-67 proliferation index.

Preoperative differentiation of atypical meningioma (AtM) from transitional meningioma (TrM) is critical to clinical treatment. To investigate the role of apparent diffusion coefficient (ADC) histogram analysis in differentiating AtM from TrM and its correlation with the Ki-67 proliferation index (PI). Clinical, imaging, and pathological data of 78 AtM and 80 TrM were retrospectively collected. Regions of interest (ROIs) were delineated on axial ADC images using MaZda software and histogram parameters (mean, variance, skewness, kurtosis, 1st percentile [ADCp1], 10th percentile [ADCp10], 50th percentile [ADCp50], 90th percentile [ADCp90], and 99th percentile [ADCp99]) were generated. The Mann-Whitney U test was used to compare the differences in histogram parameters between the two groups; receiver operating characteristic (ROC) curves were used to assess diagnostic efficacy in differentiating AtM from TrM preoperatively. The correlation between histogram parameters and Ki-67 PI was analyzed. All histogram parameters of AtM were lower than those of TrM, and the variance, skewness, kurtosis, ADCp90, and ADCp99 were significantly different (P < 0.05). Combined ADC histogram parameters (variance, skewness, kurtosis, ADCp90, and ADCp99) achieved the best diagnostic performance for distinguishing AtM from TrM. Area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 0.800%, 76.25%, 67.95%, 70.15%, 70.93%, and 73.61%, respectively. All histogram parameters were negatively correlated with Ki-67 PI (r = -0.012 to -0.293). ADC histogram analysis is a potential tool for non-invasive differentiation of AtM from TrM preoperatively, and ADC histogram parameters were negatively correlated with the Ki-67 PI.

Role of Apparent Diffusion Coefficient in Evaluating Degeneration of the Intervertebral Disc: A Narrative Review.

Degeneration of the lumbar intervertebral disc is the most common cause of lower back pain. It is directly related to daily activities, mechanical stress, and other biological factors. We use imaging modalities to assess the degree of disc degeneration, out of which magnetic resonance imaging (MRI) is the most popular non-invasive modality. It is believed that early changes in disc degeneration are due to the biochemical events in the disc and can be evaluated by sequences in MRI involving the diffusion of water molecules. The apparent diffusion coefficient (ADC) is one such sequence that captures the signals based on the diffusion of water molecules. Ten articles were chosen from PubMed and Google Scholar using the MeSH terms 'lumbar spine degeneration' and 'apparent diffusion coefficient'.This review article has summarized various studies intending to gain a better understanding of the biochemical events leading to the development of disc degeneration. This study has also gathered the role of various sequences in MRI that can quantitatively assess disc degeneration.

Role of apparent diffusion coefficient in assessment of loco-regional nodal spread in cancer rectum: correlative study with histopathological findings

BackgroundRectal cancer is associated with high morbidity and mortality rates. Preoperative assessment and detection of nodal metastasis are crucial for selecting a proper treatment plan. Diffusion-weighted imaging is considered to be a crucial functional imaging technique that can aid in determining the condition of lymph nodes. This study aimed to assess the diagnostic utility of MRI functional images by use of apparent diffusion coefficient in regional nodal assessment in rectal cancer.ResultsThis study included 54 patients including 29 males (53.7%) and 25 females (46.3%) presented with pathologically proven rectal cancer. Regarding rectal adenocarcinoma, functional MRI imaging using ADC values found to have a better sensitivity (86.24%) in detection of regional nodal metastasis than conventional morphological MRI criteria with 1.05 × 10−3 mm2/s was employed as cutoff value to distinguish metastatic from non-metastatic lymph nodes with statistically significant P value (< 0.001); nevertheless, regarding the accuracy there was no difference (68.52%). As regards mucinous and signet ring cell carcinoma, morphological assessment using conventional MRI sequences were found to have a better accuracy (72.96%) and sensitivity (57.69%) than ADC value, with the latter showed low statistically significant results (P- value < 0.201) in distinguishing metastatic and non-metastatic nodes. This could be explained by extremely high ADC values of nodes for these pathological types owing to their high mucin content.ConclusionsMRI functional imaging using ADC values can be utilized to distinguish metastatic from non-metastatic lymph nodes in rectal adenocarcinoma employing diagnostic accuracy of 86.52%. However, morphological assessment using conventional MRI was found to be better in assessment of regional lymph nodes at mucinous and signet ring rectal carcinoma.

Diffusion-weighted imaging and apparent diffusion coefficient mapping of head and neck lymph node metastasis: a systematic review.

Head and neck squamous cell cancer (HNSCC) is the ninth most common tumor worldwide. Neck lymph node (LN) status is the major indicator of prognosis in all head and neck cancers, and the early detection of LN involvement is crucial in terms of therapy and prognosis. Diffusion-weighted imaging (DWI) is a non- invasive imaging technique used in magnetic resonance imaging (MRI) to characterize tissues based on the displacement motion of water molecules. This review aims to provide an overview of the current literature concerning quantitative diffusion imaging for LN staging in patients with HNSCC. This systematic review performed a literature search on the PubMed database (https://pubmed.ncbi.nlm.nih.gov/) for all relevant, peer-reviewed literature on the subject following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) criteria, using the keywords: DWI, MRI, head and neck, staging, lymph node. After excluding reviews, meta-analyses, case reports, and bibliometric studies, 18 relevant papers out of the 567 retrieved were selected for analysis. DWI improves the diagnosis, treatment planning, treatment response evaluation, and overall management of patients affected by HNSCC. More robust data to clarify the role of apparent diffusion coefficient (ADC) and DWI parameters are needed to develop models for prognosis and prediction in HNSCC cancer using MRI.

Role of diffusion-weighted MRI in differentiation between benign and malignant anterior mediastinal masses.

Diffusion-weighted imaging (DWI) is considered to be a useful biomarker to characterize the cellularity of lesions, yet its application in the thorax to evaluate anterior mediastinal lesions has not been well investigated. The aims of our study were to describe the magnetic resonance (MR) characteristics of anterior mediastinal masses and to assess the role of apparent diffusion coefficient (ADC) value in distinguishing benign from malignant lesions of the anterior mediastinum. We conducted a retrospective cross-sectional study including 55 patients with anterior mediastinal masses who underwent preinterventional MR scanning with the following sequences: T1 VIBE DIXON pre and post-contrast, T2 HASTE, T2 TIRM, DWI-ADC map (b values of 0 and 2000 sec/mm2). The ADC measurements were obtained by two approaches: hot-spot ROI and whole-tumor histogram analysis. The lesions were grouped by three distinct ways: benign versus malignant, group A (benign lesions and type A, AB, B1 thymoma) versus group B (type B2, B3 thymoma and other malignant lesions), lymphoma versus other malignancies. The study was composed of 55 patients, with 5 benign lesions and 50 malignant lesions. The ADCmean, ADCmedian, ADC10, ADC90 in the histogram-based approach and the hot-spot-ROI-based mean ADC of the malignant lesions were significantly lower than those of benign lesions (P values< 0.05). The hot-spot-ROI-based mean ADC had the highest value in differentiation between benign and malignant mediastinal lesions, as well as between group A and group B; the ADC cutoffs (with sensitivity, specificity) to differentiate malignant from benign lesions and group A from group B were 1.17 x 10-3 mm2/sec (80%, 80%) and 0.99 x 10-3 mm2/sec (78.4%, 88.9%), respectively. The ADC values obtained by using the hot-spot-ROI-based and the histogram-based approaches are helpful in differentiating benign and malignant anterior mediastinal masses.

Role of apparent diffusion coefficient measurement in differentiating histological subtypes of brain metastasis of lung cancer

SUMMARYOBJECTIVE:The aim of this study was to investigate the role of apparent diffusion coefficient of diffusion-weighted imaging in differentiating histological subtypes of brain metastasis of lung cancer.METHODS:Diffusion-weighted imaging of 158 patients (mean age: 61.2±10.68 years) with brain metastasis of lung cancer (36 small cell lung cancer and 122 non-small cell lung cancer) were retrospectively evaluated. The minimum and mean apparent diffusion coefficient values of the metastasis, apparent diffusion coefficient of edema around the metastasis, and apparent diffusion coefficient of contralateral brain parenchyma were measured. Normalized apparent diffusion coefficient was calculated by proportioning the mean apparent diffusion coefficient of the metastasis to the apparent diffusion coefficient of the contralateral brain parenchyma. Minimum and mean apparent diffusion coefficient of the metastasis, apparent diffusion coefficient of edema around metastasis, and normalized apparent diffusion coefficient were compared between small cell lung cancer and non-small cell lung cancer metastases.RESULTS:Minimum apparent diffusion coefficient, mean apparent diffusion coefficient, and normalized apparent diffusion coefficient values of small cell lung cancer metastases (0.43±0.19×10−3mm2/s, 0.63±0.20×10−3mm2/s, and 0.81 [0.55–1.44], respectively) were significantly lower than those of non-small cell lung cancer metastases (0.71±0.26×10−3mm2/s, 0.93±0.29×10−3mm2/s, and 1.30 [0.60–3.20], respectively; p<0.001). Mean apparent diffusion coefficient of edema of small cell lung cancer metastases (1.21±0.28×10−3mm2/s) was significantly lower than that of non-small cell lung cancer metastases (1.39±0.26×10−3mm2/s, p=0.020). The best cutoff values of minimum apparent diffusion coefficient, mean apparent diffusion coefficient, normalized apparent diffusion coefficient, and apparent diffusion coefficient of edema for the differentiation of small cell lung cancer and non-small cell lung cancer were found to be 0.56×10−3mm2/s, 0.82×10−3mm2/s, 1.085, and 1.21×10−3mm2/s, respectively. The area under the receiver operating characteristic curve, sensitivity, and specificity values were, respectively, 0.812, 80.6, and 73.8% for minimum apparent diffusion coefficient; 0.825, 91.7, and 61.5% for mean apparent diffusion coefficient; 0.845, 80.6, and 73.8% for normalized apparent diffusion coefficient; and 0.698, 75.0, and 67.7% for apparent diffusion coefficient of edema.CONCLUSIONS:Minimum apparent diffusion coefficient, mean apparent diffusion coefficient, normalized apparent diffusion coefficient, and apparent diffusion coefficient of edema around metastasis can differentiate histological subtypes of brain metastasis of lung cancer.

Role of Diffusion-Weighted Magnetic Resonance Imaging in Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer and Its Molecular Subtypes.

Purpose The aim of this study was to evaluate the role of apparent diffusion coefficient (ADC) and hence diffusion-weighted imaging in prediction of pathological complete response (pCR) to neoadjuvant chemotherapy (NACT) in locally advanced breast cancer (LABC) and its molecular subtypes. Methods In this tertiary hospital-based prospective study, 30 patients aged 30 to 65 years, having clinically/cytologically diagnosed LABC, were included. Magnetic resonance imaging (MRI) was done to obtain prechemotherapy ADC (ADC pre ), postchemotherapy ADC (ADC post ), change in ADC (ΔADC), and ΔADC% for each tumor and its subtype. Postsurgical pCR was used as the reference standard for determining tumor response. All four ADC parameters were compared between pCR and non-pCR groups. Results Of the 30 patients, 19 (63.3%) patients showed pCR, while 11 (36.7%) patients did not. The pCR group showed significantly lower mean ADC pre ( p < 0.001) and higher mean ADC post ( p < 0.05), ΔADC, and ΔADC% ( p = 0.000) than non-pCR group. The best cutoff values to differentiate responders from nonresponders with receiver operating characteristic curve analysis of ADC pre , ADC post , and ΔADC% were 0.98 × 10 −3 mm 2 /s (68.4% sensitivity, 63.6% specificity), 1.31×10 −3 mm 2 /s (68.4% sensitivity, 63.6% specificity), and 25% (84.2% sensitivity, 90.9% specificity), respectively. Human epidermal growth factor receptor 2 (HER2)-enriched subtype showed significant difference in mean ADC pre ( p = 0.045), while triple-negative subtype showed significant differences in mean ADC post ( p = 0.032) and mean ΔADC ( p = 0.019) between the two groups. Conclusion ADC pre , ADC post , and ΔADC can predict pCR to NACT in LABC. Among molecular subtypes, ADC pre was predictive only in HER2-enriched subtype, while ADC post and ΔADC were predictive only in triple-negative subtype.

The Role of Pretherapeutic Diffusion-Weighted MR Imaging Derived Apparent Diffusion Coefficient in Predicting Clinical Outcomes in Immunocompetent Patients with Primary CNS Lymphoma: A Systematic Review and Meta-Analysis.

This systematic review and meta-analysis aimed to confirm the role of Apparent Diffusion Coefficient (ADC) values in predicting the prognosis of PCNSL patients based on previous studies. A systematic review with meta-analysis was conducted on related articles PubMed, Scopus, Sciencedirect, Cochrane, DOAJ, and Embase databases with last updated search on November 30, 2021. This systematic review and meta-analysis included a total of four studies. All studies that examined the association between pretherapeutic ADC values and OS and PFS discovered that lower ADC values were associated with significantly shorter OS and PFS. The analysis revealed that patients with low ADC values had a higher risk of death than those with high ADC values, with a pooled HR of 0.24 (95% CI: 0.10-0.56; Z = 3.26; p = 0.001). A meta-analysis of five data from three studies examining the association between ADC values and PFS was also conducted using a fixed-effects model due to the low heterogeneity values (I2 = 4%; p = 0.38). The data analysis revealed that the pooled HR was 0.25 (95% confidence interval [CI]: 0.14-0.44, Z = 4.18; p 0.00001). Patients with low ADC values had significantly shorter overall survival and progression-free survival than those with high ADC values, so ADC values assessment prior to initial therapy administration can provide clinicians with valuable information about the prognosis of PCNSL.

Contribution of Diffusion-Weighted Imaging and ADC Values to Papillary Breast Lesions.

This study aimed to evaluate the role of apparent diffusion coefficient (ADC) values obtained from diffusion-weighted imaging (DWI) in the differentiation of malignant from benign papillary breast lesions. The magnetic resonance imaging (MRI) data of 94 breast papillary lesions confirmed by pathology were retrospectively analyzed. The differences in ADC values of papillary lesions under different enhancements in MRI and different pathological types were investigated, and the ADC threshold was determined by the receiver operating characteristic curve for its potential diagnostic value. The mean ADC values in borderline and malignant lesions (1.01 ± 0.20 × 10-3 mm2/s) were significantly lower compared to benign lesions (1.21 ± 0.27 × 10-3 mm2/s) (P < 0.05). The optimal threshold of the ADC value could be 1.00 × 10-3 mm2/s. The ADC values were statistically significant in differentiating between benign and malignant papillary lesions whether in mass or non-mass enhancement (P < 0.05). However, there were no statistical differences in the ADC values among borderline or any other histological subtypes of malignant lesions (P > 0.05). Measuring ADC values from DWI can be used to identify benign and malignant breast papillary lesions. The diagnostic performance of the ADC value in identifying benign and malignant breast lesions is not affected by the way of lesion enhancement. However, it shows no use for differential diagnosis among malignant lesion subtypes for now. The ADC value of 1.00 × 10-3 mm2/s can be used as the most appropriate threshold for distinguishing between benign and malignant breast papillary lesions.

The role of apparent diffusion coefficient in differentiating typical from atypical meningioma

Background: Differentiation of typical from atypical meningiomas would greatly improve surgical planning and further treatment options. Appparent diffusion coefficient (ADC) has the potential to characterize meningioma subtypes. This study aimed to assess the value of ADC in differentiating typical and atypical meningiomas. Method: A retrospective study was conducted using medical records at RSUD Dr. Soetomo Surabaya in January 2019 – September 2021. ADC values were obtained by placing three ROIs on tumors. We used receiver operating curve (ROC) analysis to determine the optimal cut-off ADC value to differentiate meningioma grading and Mann-Whitney U test to evaluate the difference in ADC values between the two groups. In addition, Chi-square was used to assess the correlation between ADC values and the type of meningioma. Results: The ADC values in typical meningiomas ranged from 1.12 - 2.47 × 10-3 mm2/s with an average of 1.45 ± 0.38 × 10-3 mm2/s, while in atypical meningiomas ranged from 0.64 – 1.12 × 10-3 mm2/s with an average of 0.81 ± 0.20 × 10-3 mm2/s. Based on ROC analysis to distinguish typical and atypical meningiomas, the cut-off mean ADC value is 1.12 × 10-3 mm2/s with a sensitivity of 100%, specificity of 96.87%, and area under the curve (AUC) of 0.996. The cut-off difference in the ADC value and the relationship between the ADC value and meningioma type based on histopathology were significant. Conclusion: Typical meningiomas have higher ADC values than atypical cases. ADC value can help differentiate typical from atypical meningiomas.

Whole-tumour apparent diffusion coefficient (ADC) histogram analysis to identify MYCN-amplification in neuroblastomas: preliminary results.

To determine the role of apparent diffusion coefficient (ADC) histogram analysis in the identification of MYCN-amplification status in neuroblastomas. We retrospectively evaluated imaging records from 62 patients with neuroblastomas (median age: 15 months (interquartile range (IQR): 7-24 months); 38 females) who underwent magnetic resonance imaging at our institution before the initiation of any therapy or biopsy. Fourteen patients had MYCN-amplified (MYCNA) neuroblastoma. Histogram parameters of ADC maps from the entire tumour was obtained from the baseline images and the normalised images. The Mann-Whitney U test was used to compare the absolute and normalised histogram parameters amongst neuroblastomas with and without MYCN-amplification. Receiver operating characteristic (ROC) curves and area under the curves (AUC) were generated for the statistically significant histogram parameters. Cut-offs obtained from the ROC curves were evaluated on an external validation set (n-15, MYCNA-6, F-7, age 24 months (10-60)). A logistic regression model was trained to predict MYCNA by combining statistically significant histogram parameters and was evaluated on the validation set. MYCN-amplified neuroblastomas had statistically significant higher maximum ADC and lower minimum ADC than non-amplified neuroblastomas. They also demonstrated higher entropy, variance, energy, and lower uniformity than non-amplified neoplasms (p > 0.05). Energy, entropy, and maximum ADC had AUC of 0.85, 0.79, and 0.82, respectively. Whole tumour ADC histogram analysis of neuroblastomas can differentiate between tumours with and without MYCN-amplification. These parameters can help identify areas for targeted biopsies or can be used to predict subtypes of these high-risk tumours before biopsy results are available. • MYCN-amplification significantly affects treatment decisions in neuroblastomas. • MYCN-amplified neuroblastomas had significantly different ADC histogram metrics as compared to tumours without amplification. • ADC histogram metrics can be used to predict MYCN-amplification status based on imaging.

Cystic Lesions of the Pancreas: Is Apparent Diffusion Coefficient Value Useful at 3 T Magnetic Resonance Imaging?

The objective of this study is to determine the role of apparent diffusion coefficient (ADC) value at 3T magnetic resonance imaging (MRI) in the characterization of pancreatic cystic lesions. We retrospectively selected a total number of 223 patients with a conclusive diagnosis of pancreatic cystic lesion, previously undergoing MR examination on a 3 T system. The MRI protocol first included axial T1/T2-weighted sequences and magnetic resonance cholangiopancreatography. Diffusion-weighted MRI was performed using a spin-echo echo-planar sequence with multiple b values (0, 150, 500, 1000, and 1500 s/mm2) in all diffusion directions, obtaining an ADC map. Contrast-enhanced T1-weighted sequences were performed during the initial work-up of a pancreatic cystic lesion and when signs of malignancy were suspected during the MRI follow-up. The ADC value of each pancreatic lesion was measured using a monoexponential curve fitting with all the multiple b. The final diagnosis of our study group included the following: serous cystadenomas (n = 42), mucinous cystadenomas (n = 14), intraductal papillary mucinous neoplasms (IPMNs) (n = 121), IPMNs with signs of malignancy at histopathologic examination (n = 24), pseudocysts (n = 9), other cystic lesions (n = 13). A statistically significant difference was observed between the ADC values of malignant IPMNs and those of each other group of pancreatic lesions (P < 0.001). The ADC value of benign IPMN was significantly higher than that of serous cystadenomas (P = 0.024). A statistically significant difference was observed between the ADCs of all mucinous cystic tumors (benign IPMNs together to mucinous cystadenomas) and the ADCs of serous cystadenomas (P = 0.014). Fitted ADC value obtained at 3T MRI may be helpful in the characterization of pancreatic cystic lesions with particular regards of differential diagnosis between mucinous and serous cystic tumors and between malignant and benign IPMNs.

The role of apparent diffusion coefficient (ADC) in the evaluation of lymph node status in patients with locally advanced cervical cancer: our experience and a review.

PurposeTo evaluate the role of apparent diffusion coefficient (ADC) value measurement in the diagnosis of meta-static lymph nodes (LNs) in patients with locally advanced cervical cancer (LACC) and to present a systematic review of the literature.Material and methodsMagnetic resonance imaging (MRI) exams of patients with LACC were retrospectively eva-luated. Mean ADC, relative ADC (rADC), and correct ADC (cADC) values of enlarged LNs were measured and compared between positron emission tomography (PET)-positive and PET-negative LNs. Comparisons were made using the Mann-Whitney U-test and Student’s t-test. ROC curves were generated for each parameter to identify the optimal cut-off value for differentiation of the LNs. A systematic search in the literature was performed, exploring several databases, including PubMed, Scopus, the Cochrane library, and Embase.ResultsA total of 105 LNs in 34 patients were analysed. The median ADC value of PET-positive LNs (0.907 × 10-3 mm2/s [0.780-1.080]) was lower than that in PET-negative LNs (1.275 × 10-3 mm2/s [1.063-1.525]) (p < 0.05). rADC and cADC values were lower in PET-positive LNs (rADC: 0.120 × 10-3 mm2/s [–0.060-0.270]; cADC: 1.130 [0.980-1.420]) than in PET-negative LNs (rADC: 0.435 × 10-3 mm2/s [0.225-0.673]; cADC: 1.615 [1.210-1.993]) LNs (p < 0.05). ADC showed the highest area under the curve (AUC 0.808).ConclusionsMean ADC, rADC, and cADC were significantly lower in the PET-positive group than in the PET-negative group. The ADC cut-off value of 1.149 × 10-3 mm2/s showed the highest sensitivity. These results confirm the usefulness of ADC in differentiating metastatic from non-metastatic LNs in LACC.

The role of apparent diffusion coefficient as a predictive factor for tumor recurrence in patients with cerebellopontine angle epidermoid tumor.

Intracranial epidermoid tumors are slowly growing benign tumors, but due to adjacent critical neurovascular structures, surgical resection is challenging, with the risk of recurrence. The apparent diffusion coefficient (ADC) has been used to evaluate the characteristics of brain tumors, but its utility for intracranial epidermoid tumors has not been specifically explored. This study analyzed the utility of preoperative ADC values in predicting tumor recurrence for patients with intracranial epidermoid tumors. Between 2008 and 2019, 21 patients underwent surgery for cerebellopontine angle (CPA) epidermoid tumor, and their preoperative ADC data were analyzed. The patients were divided into two groups: the recurrence group, defined by regrowth of the remnant tumor or newly developed mass after gross total resection on magnetic resonance imaging (MRI); and the stable group, defined by the absence of growth or evidence of tumor on MRI. Receiver operating characteristic (ROC) analysis was used to obtain the ADC cutoff values for predicting tumor recurrence. The prognostic value of the ADC was assessed using Kaplan-Meier curves. The minimum ADC values were significantly lower in the recurrence group than in the stable tumor group (P = 0.020). ROC analysis showed that a minimum ADC value lower than 804.5 × 10-6 mm2/s could be used to predict higher recurrence risk of CPA epidermoid tumors. Non-total resection and mean and minimum ADC values lower than the respective cutoffs were negative predictors of recurrence-free survival. Minimum ADC values could be useful in predicting the recurrence of CPA epidermoid tumors.

The Role of Diffusion-Weighted MRI and Apparent Diffusion Coefficient in Assessment of Diabetic Kidney Disease: Preliminary Experience Study.

BackgroundDiabetic kidney disease is the most common cause of ESRD. There is poor correlation between the degree of renal fibrosis and current screening markers. A noninvasive imaging technique is needed to assess the degree of structural changes in the kidney. The aim of this study was to assess the role of apparent diffusion coefficient (ADC) in the diagnosis of diabetic kidney disease. Forty adult diabetic patients with chronic kidney disease as well as 20 age- and sex-matched adult healthy controls were recruited from Nephrology Department of our University Hospital. All patients underwent renal MR-DWI and ADC mapping on a 1.5-T scanner (Philips Achieva) using phased array body coil.ResultsAmong the studied 40 diabetic patients, five groups of patients were resulted 8 patients for each and the ADC values were inversely correlated with advancement in renal parenchymal affection, ie, in late stages of the disease the ADC values were lower than in early stages. The mean ADC values of renal parenchyma in patients with diabetic kidney disease were considerably lower than that of healthy controls with normal renal function (2.1±0.3x10−3 mm2/s vs 2.4±0.1x10−3 mm2/s with p<0.001).ConclusionADC value is a possible noninvasive technique in evaluating the stage of renal dysfunction with assessment of disease progression.

Diffusion-Weighted MRI Imaging and ADC Map of Patellar Chondromalacia

Background: Chondromalacia patellae is damage to the cartilage at the back of the kneecap (patella). Magnetic resonance imaging is a valuable noninvasive technique with a unique ability to image soft tissue and has been used for cartilage evaluation.Objective: This study examines the role of apparent diffusion coefficient (ADC) map and diffusion-weighted imaging (DWI) techniques in diagnosing chondromalacia patella. Materials and Methods: The study consists of 31 participants, 19 patients with chondromalacia patella, and 12 healthy volunteers. The DWI imaging and ADC maps for all patients were recorded. Later the average amount of ADC for a lesion was calculated by drawing regions of interest. Results: The results of DWI imaging in patients with patellae chondromalacia were observed as a nonhomogeneous patella signal and with an increase in the signal intensity at the focal, thickening of cartilage with surface irregularities, reactive changes subchondral, and bone marrow edema. The mean ADC values of the chondromalacia group and the health group were 1.34 × 10–3 mm2/s and 1.07 × 10–3 mm2/s, respectively. Conclusion: Diffusion-weighted imaging can detect early-stage patellar chondromalacia. Besides, it may also help in the detection of cartilage defects