Apparent Diffusion Coefficient Min Research Articles

Whole-Lesion Apparent Diffusion Coefficient Histogram Analysis for Assessing Normal-Sized Lymph Node Metastasis in Cervical Cancer: Comparison Between Readout-Segmented and Single-Shot Echo-Planar Diffusion-Weighted Imaging.

To compare the value of whole-lesion apparent diffusion coefficient (ADC) histogram analysis derived from readout-segmented echo-planar imaging (RS-EPI) and single-shot echo-planar imaging (SS-EPI) diffusion-weighted imaging (DWI) in evaluating normal-sized lymph node metastasis (LNM) in cervical cancer. Seventy-six pathologically confirmed cervical cancer patients (stages IB and IIA) were enrolled, including 61 patients with non-LNM (group A) and 15 patients with normal-sized LNM (group B). The recorded tumor volume on T2-weighted imaging was the reference against which both DWIs were evaluated. Each ADC histogram parameter (including ADC max , ADC 90 , ADC median , ADC mean , ADC 10 , ADC min , ADC skewness , ADC kurtosis , and ADC entropy ) was compared between SS-EPI and RS-EPI and between the 2 groups. There was no significant difference in tumor volume between the 2 DWIs and T2-weighted imaging (both P > 0.05). Higher ADC max and ADC entropy but lower ADC 10 , ADC min and ADC skewness were found in SS-EPI than those in RS-EPI (all P < 0.05). For SS-EPI, lower ADC 90 and higher ADC kurtosis were found in group B than those in group A (both P < 0.05). For RS-EPI, lower ADC 90 and higher ADC kurtosis and ADC entropy were found in group B than those in group A (all P < 0.05). Readout-segmented echo-planar imaging ADC kurtosis showed the highest area under the curve of 0.792 in the differentiation of the 2 groups (sensitivity, 80%; specificity, 73.77%). Compared with SS-EPI, the ADC histogram parameters derived from RS-EPI were more accurate, and ADC kurtosis held great potential in differentiating normal-sized LNM in cervical cancer.

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.

Volumetric apparent diffusion coefficient (ADC) histogram analysis of the brain in paediatric patients with hypoxic ischaemic encephalopathy.

To evaluate the whole brain, hippocampus, thalamus, and lentiform nucleus by volumetric apparent diffusion coefficient (ADC) histogram analysis in paediatric patients with hypoxic-ischaemic encephalopathy (HIE). This retrospective study included 25 patients with HIE and 50 patients as the control group. Diffusion-weighted imaging was obtained at b-values of 1000 mm2/s. The histogram parameters of ADC values, including the mean, minimum, maximum, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles, as well as skewness, kurtosis, and variance were determined. The interclass correlation coefficient (ICC) was used to assess the inter-observer agreement. ADCmin, ADCmean, and ADCmax, as well as the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC values for the HIE group were all lower than those of the control group (p < 0.001) in the volumetric histogram analysis of the hippocampus, thalamus, and lentiform nucleus. In the whole-brain histogram analysis, ADC min, and the 50th and 75th percentiles of ADC values did not differ significantly, while other parameters were lower in the HIE group. The ROC curve revealed that the ADC histogram parameters of the hippocampus provided the most accurate results for the diagnosis of HIE. The area under the curve (AUC) of the 95th percentile of ADC values was the highest (AUC = 0.915; cut-off 1.262 × 10-3 mm2/s; sensitivity 88% and specificity 84%). Volumetric ADC histogram analysis of the whole brain, hippocampus, thalamus, and lentiform nucleus with b-values of 1000 mm2/s can serve as an imaging marker for determining HIE.

Standard diffusion-weighted, diffusion kurtosis and intravoxel incoherent motion MR imaging of the whole placenta: a pilot study of volumetric analysis.

BackgroundUsing magnetic resonance imaging (MRI) to explore the changes in microvascular perfusion fraction and the heterogeneity of the placenta during pregnancy.MethodsWe retrospectively reviewed 24 patients with normal pregnancies who underwent standard diffusion-weighted, diffusion kurtosis, and intravoxel incoherent motion MRI. The mean, minimum and maximum parameters including the apparent diffusion coefficient (ADC) and exponential ADC (eADC) from standard diffusion-weighted imaging (DWI), the diffusion coefficient (MD) and diffusion kurtosis (MK) from diffusion kurtosis imaging (DKI), and the pure diffusion coefficient (D), pseudo-diffusion coefficient (D*) and perfusion fraction (f) from intravoxel incoherent motion MR imaging (IVIM) were calculated from the whole placenta volumetric analysis and correlated with gestational age (GA) and volume of the placenta.ResultsA significant positive correlation was found between eADC mean, eADC max, MK mean, MK max, the volume of the whole placenta, and GA, and a negative correlation was found between ADC mean, ADC min, MD min, D mean, D min, D* min and GA. The f mean and MK max values positively correlated with the volume of the whole placenta.ConclusionseADC mean, eADC max, MK mean, MK max values increased with GA, while ADC mean, ADC min, MD min, D mean, D min, D* min decreased with GA. Secondly, the f mean and MK max also increased with placental volume. These results suggest the potential of diffusion and perfusion parameters to evaluate the placenta during its development using different DWI models.

Interstitial Brachytherapy of the Liver for Renal Cell Carcinoma: ADC Measurements Do Not Predict Overall Survival.

To assess the influence of pre-treatment apparent diffusion coefficient (ADC) measurements on outcomes in patients undergoing interstitial brachytherapy (iBT) for liver metastases from renal cell carcinoma. Patients undergoing iBT for renal cell carcinoma (RCC) liver metastases were retrospectively identified. Patients were eligible for inclusion if they had a pre-treatment magnetic resonance imaging (MRI) with diffusion weighted imaging (DWI) sequences. For each lesion, a region of interest (ROI) was placed along the contours of the entire lesion across all slices. For each ROI, ADC minimum, mean and maximum as well as the lesion area were noted, and the average was calculated for each lesion. ADC measurements were correlated with overall survival. The analysis included 17 patients. Median overall survival was 36 months. Neither ADC measurement was significantly associated with overall survival. ADC min (HR=1.00, 95%CI=1.00-1.00, p=0.600), ADC max (HR=1.001, 95%CI=0.998-1.003, p=0.490), ADC mean (HR=0.999, 95%CI=0.996-1.003, p=0.638). ADC is not able to differentiate between groups with good and bad overall survival in patients undergoing iBT for RCC liver metastases.

Whole Tumor Histogram Analysis Using DW MRI in Primary Central Nervous System Lymphoma Correlates with Tumor Biomarkers and Outcome.

The ability to non-invasively predict outcomes and monitor treatment response in primary central nervous system lymphoma (PCNSL) is important as treatment regimens are constantly being trialed. The aim of this study was to assess the validity of using apparent diffusion coefficient (ADC) histogram values to predict Ki-67 expression, a tumor proliferation marker, and patient outcomes in PCNSL in both immunocompetent patients and patients living with HIV (PLWH). Qualitative PCNSL magnetic resonance imaging (MRI) characteristics from 93 patients (23 PLWH and 70 immunocompetent) were analyzed, and whole tumor segmentation was performed on the ADC maps. Quantitative histogram analyses of the segmentations were calculated. These measures were compared to PCNSL Ki-67 expression. Progression-free survival (PFS) and overall survival (OS) were analyzed via comparison to the International Primary Central Nervous System Lymphoma Collaboration Group Response Criteria. Associations between ADC measures and clinical outcomes were assessed using univariate and multivariate Cox proportional hazards models. Normalized ADC (nADC)Min, nADCMean, nADC1, nADC5, and nADC15 values were significantly associated with a poorer OS. nADCMax, nADCMean, nADC5, nADC15, nADC75, nADC95, nADC99 inversely correlated with Ki-67 expression. OS was also significantly associated with lesion hemorrhage. PFS was not significantly associated with ADC values but with lesion hemorrhage. ADC histogram values and related parameters can predict the degree of tumor proliferation and patient outcomes for primary central nervous system lymphoma patients and in both immunocompetent patients and patients living with HIV.

Conventional MR and diffusion-weighted imaging of musculoskeletal soft tissue malignancy: correlation with histologic grading.

To evaluate proven soft tissue musculoskeletal malignancies blinded to their Fédération Nationale des Centres de Lutte Contre le Cancer histologic grades to identify the predictive values of conventional MR findings and best fit region of interest (ROI) apparent diffusion coefficient (ADC) measurements. Fifty-one consecutive patients with different histologic grades were evaluated by four readers (R1-4) of different experience levels. Quantitatively, the maximum longitudinal size, tumor to muscle signal intensity ratios, and ADC measurements and, qualitatively, the spatial location of the tumor, its signal alterations, heterogeneity, intralesional hemorrhage or fat, and types of enhancement were assessed. Intraclass correlation, weighted kappa, ANOVA, and Fisher exact tests were used. There were 22/51 (43%) men (mean age ± SD = 52 ± 16years) and 29/51 (57%) women (mean age ± SD = 54± 17years), with the majority of tumors 38/51 (75%) in the lower extremities. Histologic grades were I in 8/51 (16%), II in 17/51 (33%), and III in 26/51 (51%), respectively. The longitudinal dimensions were different among three grades (p = 0.0015), largest with grade I. More central enhancements and deep locations were seen in grade III tumors (p = 0.0191, 0.0246). The ADC mean was significantly lower in grade III than in grade I or II (p < 0.0001 and p = 0.04). The ADC min was significantly lower in grade III than in grade I (p = 0.02). Good to excellent agreements were seen for T1/T2 tumor/muscle ratios, longitudinal dimension, and ADC (ICC = 0.60-0.98). Longitudinal tumor dimension, central enhancement, and ADC values differentiate histology grades in musculoskeletal soft tissue malignancy with good to excellent inter-reader reliability. • The longitudinal tumor dimension of grade III malignancy is smaller than that of grade I (p < 0.0001), and higher-grade tumors are located deeper (p = 0.0246). • The ADC mean is significantly lower in grade III than in grade I or grade II (p < 0.0001 and p = 0.04). • The ADC minimum is significantly lower in grade III than in grade I (p = 0.02).

The Application of Apparent Diffusion Coefficient and Chemical Shift Images in Differentiation of Benign and Malignant Vertebral Lesions

Background: One of the most common clinical problems is the differentiation of vertebral marrow lesions, particularly in the elderly patients. Since clinical staging, treatment strategy, and prognosis in malignant and benign lesions are different, it is very essential to determine the benign and malignant nature of vertebral pathologies. Objectives: The aim of this study was to assess the value of diffusion weighted magnetic resonance imaging and chemical shift in the diagnosis, characterization, and differentiation of benign and malignant vertebral bone marrow lesions and to define the sensitivity and the specificity in differentiating benign and malignant vertebral lesions according to the optimal cut-off Apparent-diffusion-coefficient (ADC) values and signal intensity ratio (SIR). Methods: This study included 39 patients with 86 untreated vertebral lesions that underwent the routine MRI sequences of the spine as well as the two non-routine sequences (DWI and in/opposed phase). The optimal cut-off ADC value and SIR were determined for the differentiation of benign and malignant lesions. We used the biopsy results and clinical follow-up, as the gold standard to classify the vertebral marrow lesions as benign and malignant. Results: Of the examined 39 patients, 67 focal lesions were included that 42 lesions proved to be malignant and 25 lesions diagnosed as benign. The results of this study showed that the ADC values of benign lesions were significantly (P < 0.001) higher than untreated metastatic lesions. SIR values were calculated 1.155 ± 0.183 in malignant lesions, while it was 0.649 ±0.341 in benign lesions. Threshold analysis yield optimal cut-off point that showed ADC min and ADC mean and SIR had high sensitivity, specificity, and accuracy in the discrimination of benign and malignant lesions. Conclusions: Quantitative diffusion weighted and chemical shift MR imaging are effective non-invasive technique in differentiating benign from malignant vertebral bone marrow lesions that provide additional information to the routine MRI sequences.

Associations between apparent diffusion coefficient and electromyography parameters in myositis-A preliminary study.

Objective MRI is widely used in several muscle disorders. Diffusion‐weighted imaging (DWI) is an emergent imaging modality sensitive to microstructural alterations in tissue. The apparent diffusion coefficient (ADC) is used to quantify the random motion of water molecules. Electromyography (EMG) is a clinically used diagnostic tool in myositis. The aim of this study was to elucidate possible associations between ADC values and EMG findings in myositis patients.MethodSeven patients (eight investigated muscles) with myositis (mean age 51.43 ± 19 years) were included in this study. The diagnosis was confirmed by histopathology in every case. DWI was obtained with a 1.5‐T scanner using two b‐values 0 and 1000 s/mm². In all patients, a needle electromyography (EMG) was performed within 3 days to the MRI. The following EMG parameters were studied: motor unit action potential (MUAP) amplitudes and durations, as well as pathological spontaneous activity. Spearman's correlation coefficient was used to analyze associations between investigated parameters.ResultsThe estimated mean ADC mean value was 1.51 ± 0.29 × 10−3 mm²/s, mean ADC min was 1.28 ± 0.27 × 10−3 mm²/s, and mean ADC max was 1.73 ± 0.28 × 10−3 mm²/s. Correlation analysis identified significant associations between ADC mean and duration of the MUAP (p = .78 P = .0279) and between ADC min and duration of the MUAP (p = .85, P = .01). There were no significant differences according to pathological spontaneous activity.Conclusion ADC mean and ADC min showed strong positive correlations with the duration of the MUAP in myositis patients. Both modalities might similarly reflect muscle fiber loss in myositis patients.

Diagnostic value of semi-quantitative and quantitative analysis of functional parameters in multiparametric MRI of the prostate.

To determine the diagnostic value of semi-quantitative and quantitative parameters of three functional techniques in multiparametric (mp)-MRI of the prostate. Mp-MRI was performed in 110 patients with suspicion of prostate cancer (PCA) before transrectal ultrasound (TRUS)-guided core biopsy. Peak-enhancement, initial and post-initial enhancement, initial area under gadolinium curve, Ktrans (forward rate constant), Kep (efflux rate constant), Ve (extracellular volume), ADC (apparent diffusion coefficient) and MR spectroscopy ratio were obtained for malignant and benign lesions. For iAUGC, Ktrans, Kep and Ve we evaluated median, mean and the difference (Diff) between mean and median. For ADC we evaluated mean, median, Diff between mean and median, and min. In addition, we evaluated these parameters in dependence of Gleason score in PCA. Receiver operating characteristic analysis and area under curve (AUC) were determined. ADC min and Kep Diff were the best predictors of malignancy in all lesions (AUC: 0.765). ADC min was the best predictor of malignancy for lesions in peripheral zone (PZ) (AUC: 0.7506) and Kep Diff was the best predictor of malignancy for lesions in transitional zone (AUC: 0.7514). Peak enhancement was the best parameter in differentiation of low-grade PCA with Gleason score 6 from high-grade PCA with Gleason score ≥ 7 (AUC: 0.7692). ADC min can differentiate PCA from benign prostate lesions in PZ. Kep Diff could possibly improve prostate cancer detection in. Peak enhancement might be able to differentiate low grade from high-grade PCA. Semi-quantitative and quantitative parameters may be useful for the functional techniques in mp-MRI. Advances in knowledge: ADC min can differentiate PCA from benign prostate lesions in PZ. Peak enhancement might be able to differentiate low grade from high-grade PCA.

Diagnostic Value of Diffusion Weighted Magnetic Resonance Imaging in Evaluation of Metastatic Axillary Lymph Nodes in a Sample of Iranian Women with Breast Cancer

Objective:To evaluate the diagnostic value of diffusion weighted magnetic resonance imaging (DW-MRI) in assessment of metastases in axillary lymph nodes (ALNs) in a sample of Iranian women with breast cancer.Methods:A total of 50 axillary lymph nodes from 30 female patients with histologically verified breast cancer were assessed by 1.5 T MRI. DWI was implemented at b-values of 50, 400 and 800 s/mm2. Short axis diameter, presence of fatty hilum and apparent diffusion coefficient (ADC) values (min, max and mean) of metastatic and non-metastatic ALNs was compared. Cutoff ADC values to discriminate between benign and malignant axillary lymph nodes were analyzed with receiver coefficient characteristic (ROC) curves.Result:The final histopathological examination revealed 46% (n=23) metastatic and 54% (n=27) non-metastatic ALNs. There was no statistically significant difference in short axis diameter between the two groups (p = 0.537). However there was significantly correlation between loss of fatty hilum and presence of metastases (p < 0.001) and ADC values (0.255 ± 0.19×10-3 mm2/s vs 0.616 ±0.3×10-3 mm2/s (ADC min), 1.088 ± 0.22×10-3 mm2/s vs 1.497 ± 0.24×10-3 mm2/s (ADC max) and 0.824 ± 0.103 ×10-3 mm2/s vs 1.098 ± 0.23 ×10-3 mm2/s (ADC mean)) of metastatic ALNs were significantly lower than those of non-metastatic ALNs (p < 0.001). The optimal mean ADC cut-off value for differentiation between metastatic and non-metastatic ALNs was 0.904×10-3 mm2/s which had a higher specificity (88.9%) and accuracy (91.8%) as compared with ADC min and ADC max.Conclusion:DWI-MRI and ADC values are promising imaging methods which can assess metastatic ALNs in breast cancer with high sensitivity, specificity and accuracy.

Molecular imaging using by diffusion-weighted imaging of brain tumor through signal intensity: Progress in molecular cancer imaging

Introduction: Characterizing variations of brain tumors has significant effect in the treatment process of the affected patients. Brain metastatic tumors are usually diagnosed following by the neurological symptoms in patients. Purpose of this article is to find role of diffusion-weighted magnetic resonance imaging (DW-MRI) and apparent diffusion coefficient (ADC) values in the evaluation of different benign and malignant brain mass lesions before surgery with histopathological correlation. Materials and Methods: MR examination of 54 patients with brain metastatic tumor referring to 7th-Tir Hospital (Tehran, Iran) were randomly selected and imaged with T2W Multi-echo sequences and GRE-EPI (DWI) in addition to taking the routine sequence of the brain. Diffusion parameters during treatment were evaluated for early non-invasive biomarkers. In analyzing the data, the min ADC values were measured within the tumors and the mean values were evaluated. The data was analyzed by ANOVA, Pairwise post-hoc, and Tukey's HSD test applying GraphPadPrism. Results: The ADC min values of low-grade gliomas (1.09±0.20×10-3 mm2/s) were significantly higher than those of other tumors (p<0.001). The obtained ADC value of 0.5613±0.0258 indicated BMT with lung origin, the value of 1.009±0.03820 revealed BMT with liver and breast origin, and the value of 1.556±0.035 showed BMT with colon and prostate origin. Conclusion: According to our results DW-MRI parameters during treatment were evaluated for early non-invasive biomarkers. The ADC changes from mid- to post-treatment suggest such a possible early non-invasive biomarker.

Combining standardized uptake value of FDG-PET and apparent diffusion coefficient of DW-MRI improves risk stratification in head and neck squamous cell carcinoma.

To assess the independent prognostic value of standardized uptake value (SUV) and apparent diffusion coefficient (ADC), separately and combined, in order to evaluate if the combination of these two variables allows further prognostic stratification of patients with head and neck squamous cell carcinomas (HNSCC). Pretreatment SUV and ADC were calculated in 57 patients with HNSCC. Mean follow-up was 21.3months. Semiquantitative analysis of primary tumours was performed using SUVmaxT/B, ADCmean, ADCmin and ADCmax. The prognostic value of SUVmaxT/B, ADCmean, ADCmin and ADCmax in predicting disease-free survival (DFS) was evaluated with log-rank test and Cox regression models. Patients with SUVmaxT/B ≥5.75 had an overall worse prognosis (p = 0.003). After adjusting for lymph node status and diameter, SUVmaxT/B and ADCmin were both significant predictors of DFS with hazard ratio (HR) = 10.37 (95% CI 1.22-87.95) and 3.26 (95% CI 1.20-8.85) for SUVmaxT/B ≥5.75 and ADCmin ≥0.58 × 10-3 mm2/s, respectively. When the analysis was restricted to subjects with SUVmaxT/B ≥5.75, high ADCmin significantly predicted a worse prognosis, with adjusted HR = 3.11 (95% CI 1.13-8.55). The combination of SUVmaxT/B and ADCmin improves the prognostic role of the two separate parameters; patients with high SUVmaxT/B and high ADCmin are associated with a poor prognosis. • High SUV maxT/B is a poor prognostic factor in HNSCC • High ADC min is a poor prognostic factor in HNSCC • In patients with high SUV maxT/B , high ADC min identified those with worse prognosis.

Performance of Apparent Diffusion Coefficient Values and Conventional MRI Features in Differentiating Tumefactive Demyelinating Lesions From Primary Brain Neoplasms.

Tumefactive demyelinating lesions (TDLs) remain one of the most common brain lesions to mimic a brain tumor, particularly primary CNS lymphoma (PCNSL) and high-grade gliomas. The purpose of our study was to evaluate the ability of apparent diffusion coefficient (ADC) values and conventional MRI features to differentiate TDLs from PCNSLs and high-grade gliomas. Seventy-five patients (24 patients with TDLs, 28 with PCNSLs, and 23 with high-grade gliomas) with 168 brain lesions (70 TDLs, 68 PCNSLs, and 30 high-grade gliomas) who underwent DWI before surgery or therapy were included in the study. Minimum ADC (ADC(min)) and average ADC (ADC(avg)) values were calculated for each lesion. ANOVA and ROC analyses were performed. ROC analyses were also performed for the presence of incomplete rim enhancement and for the number of lesions. Multiple-variable logistic regression with ROC analysis was then performed to evaluate performance in multiple-variable models. ADC(min) was statistically significantly higher (p < 0.01) in TDLs (mean, 0.886; 95% CI, 0.802-0.931) than in PCNSLs (0.547; 95% CI, 0.496-0.598) and high-grade gliomas (0.470; 95% CI, 0.385-0.555). (All ADC values in this article are reported in units of × 10(-3) mm(2)/s.) ADC(avg) was statistically significantly higher (p < 0.01) in TDLs (mean, 1.362; 95% CI, 1.268-1.456) than in PCNSLs (0.990; 95% CI, 0.919-1.061) but not in high-grade gliomas (1.216; 95% CI, 1.074-1.356). Multiple-variable models showed statistically significant individual effects and superior diagnostic performance on ROC analysis. TDLs can be diagnosed on preoperative MRI with a high degree of specificity; MRI features of incomplete rim enhancement, high ADC values, and a large number of lesions individually increase the probability and diagnostic confidence that a lesion is a TDL.

Relationship between apparent diffusion coefficient and tumour cellularity in lung cancer.

Background and objectiveTo prospectively investigate the relationship between the apparent diffusion coefficient (ADC) and cellularity in lung cancer.MethodsSixty patients histopathologically confirmed with lung cancer (41 men, 19 women) underwent diffusion-weighted magnetic resonance imaging of the chest (with b values of 50 and 1000 s/mm2). The median mean ADC (ADCmean) value and median minimum ADC (ADCmin) value within each primary tumour were calculated and compared with the median nucleo-cytoplasmic ratio (NCR), which was selected to represent the cellularity. The correlation between the NCR and ADCmean/ADCmin was calculated with SPSS 18.0 software.ResultsThe mean ADCmean values, ADCmin values and median NCR were (1.07±0.12)×10−3 mm2/s, (0.86±0.14)×10−3 mm2/s, and (14.9±2.6) %, respectively, in adenocarcinoma; (0.88±0.10)×10−3 mm2/s, (0.73±0.12)×10−3 mm2/s, and (20.6±4.4) %, respectively, in squamous cell carcinoma; and (0.89±0.13)×10−3 mm2/s, (0.67±0.13)×10−3 mm2/s, and (18.3±3.5) %, respectively in small cell lung cancer. The NCR of squamous cell carcinoma and small cell lung cancer is greater than that of adenocarcinoma (P<0.01 and P = 0.002, respectively). There was an inverse relationship between ADCmean/NCR and ADCmin/NCR (r = −0.60, P = 0.001 and r = −0.47, P<0.001, respectively).ConclusionThere is a significant inverse relationship between tumour cellularity and ADC in lung cancer. However, tumour cellularity most likely is not the sole determinant of the ADC.

Pilot study on evaluation of any correlation between MR perfusion (Ktrans) and diffusion (apparent diffusion coefficient) parameters in brain tumors at 3 Tesla

Purpose: To assess any correlation of volume transfer constant (Ktrans) with apparent diffusion coefficient (ADC) in different brain tumor types at 3 T magnetic resonance (MR) imaging. Materials and methods: Thirteen patients with brain tumors (8 men, 5 women; mean age 54.6 ± 17.7 years) were enrolled in this retrospective study. All patients underwent dynamic contrast-enhanced T1-weighted MR perfusion and diffusion-weighted imaging using a 3 T scanner. Ktrans was estimated by specially designed software. For each tumor, regions of interest (ROIs) were manually selected on corresponding Ktrans and ADC maps. Pearson correlation coefficients were obtained for maximum, mean and minimum values of Ktrans and ADC of all ROIs. Based on clinicopathologic results, the final diagnoses of patients were glioblastoma multiforme (3), low-grade to anaplastic gliomas (4), meningiomas (3) and metastatic tumors (3). Results: Ktrans(max) values were significantly inversely correlated with ADC(min) values (r = –0.536, P < 0.001) and ADC(mean) values (r = –0.465, P < 0.001). Ktrans(mean) and Ktrans(min) values were significantly inversely correlated with ADC(mean) (r = –0.228, P = 0.038) and ADC(max) values (r = –0.355, P = 0.001), respectively. Conclusion: We found that irrespective of brain tumor type, there is an inverse correlation between ADC and Ktrans. Our findings highlight an intricate relationship between vascular permeability and the tumor microenvironment, probably modulating and/or interacting with changes such as increased cellularity, ischemic insult and varying extracellular matrix composition.

Predicting survival in glioblastomas using diffusion tensor imaging metrics

To retrospectively correlate various diffusion tensor imaging (DTI) metrics in patients with glioblastoma multiforme (GBM) with patient survival analysis and also degree of tumor proliferation index determined histologically. Thirty-four patients with histologically confirmed treatment naive GBMs underwent DTI on a 3.0 Tesla (T) scanner. Region-of-interest was placed on the whole lesion including the enhancing as well as nonenhancing component of the lesion to determine the various DTI metrics. Kaplan-Meier estimates and Cox proportional hazards regression methods were used to assess the relationship of DTI metrics (minimum and mean values) and Ki-67 with progression free survival (PFS). To study the relationship between DTI metrics and Ki-67, Pearson's correlation coefficient was computed. Univariate analysis showed that patients with fractional anisotropy (FA)(mean) ≤ 0.2, apparent diffusion coefficient (ADC)(min) ≤ 0.6, planar anisotropy (CP)(min) ≤ 0.002, spherical anisotropy (CS)(mean) > 0.68 and Ki-67 > 0.3 had lower PFS rate. The multivariate analysis demonstrated that only CP(min) was the best predictor of survival in these patients, after adjusting for age, Karnofsky performance scale and extent of resection. No significant correlation between DTI metrics and Ki-67 were observed. DTI metrics can be used as a sensitive and early indicator for PFS in patients with glioblastomas. This could be useful for treatment planning as high-grade gliomas with lower ADC(min), FA(mean), CP(min), and higher CS(mean) values may be treated more aggressively.

Quantitative Assessment of Diffusion-Weighted MR Imaging in Patients with Primary Rectal Cancer: Correlation with FDG-PET/CT

PurposeThe aim of the study was to assess correlations between parameters on diffusion-weighted imaging and 2-deoxy-2-[18F]fluoro-d-glucose–positron emission tomography/computed tomography (FDG-PET/CT) in rectal cancer.ProceduresThirty-three consecutive patients with pathologically confirmed rectal adenocarcinoma were included in this study. Apparent diffusion coefficient (ADC) maps were generated to calculate ADCmean (average ADC), ADCmin (lowest ADC), tumor volume, and total diffusivity index (TDI). PET/CT exams were performed within 1 week of magnetic resonance imaging. Standardized uptake values (SUVs) were normalized to the injected FDG dose and body weight. SUVmax (maximum SUV), SUVmean (average SUV), tumor volume, and total lesion glycolysis (TLG) were calculated using a 50% threshold.ResultsSignificant negative correlations were found between ADCmin and SUVmax (r = −0.450, p = 0.009), and between ADCmean and SUVmean (r = −0.402, p = 0.020). A significant positive correlation was found between TDI and TLG (r = 0.634, p < 0.001).ConclusionThe significant negative correlations between ADC and SUV suggest an association between tumor cellularity and metabolic activity in primary rectal adenocarcinoma.

Role of PROPELLER diffusion-weighted imaging and apparent diffusion coefficient in the evaluation of pituitary adenomas

Objective The relationship between tumor consistency and apparent diffusion coefficient (ADC) values is controversial. We evaluated the role of the ADC using an advanced diffusion-weighted imaging (DWI) technique. We employed periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) DWI acquired on a 3-T magnetic resonance imaging (MRI) scanner to assess the consistency of pituitary adenomas and examined the relationship between the ADC and the hormone secretion status of the tumors and their MIB-1 labeling index (MIB-1 LI). Materials and methods The study protocol was approved by our institutional review board. We retrospectively studied 24 operated patients with pituitary adenomas who had undergone PROPELLER DWI on a 3-T MRI scanner. Conventional MRI findings were expressed as the ratio of the signal intensity (SI) in the lesions to the SI of the normal white matter and the degree of contrast enhancement. Minimum-, mean-, and maximum ADC (ADC min, ADC mean, ADC max) values were calculated. The consistency of the tumors was determined by neurosurgeons. All surgical specimens were submitted for histological study to calculate the MIB-1 LI and the percent collagen content. Preoperative MRI-, intraoperative-, and histological findings were analyzed by a statistician. Results Our study included 15 soft-, 5 fibrous-, and 4 hard tumors. Tumor consistency was strongly associated with the percent collagen content. However, neither the tumor consistency nor the percent collagen content was correlated with MRI findings or ADC values. The SI of growth hormone-producing adenomas on T2-WI was lower than of the other pituitary adenomas studied ( p < 0.01); no other significant difference was found in the ADC or on conventional MRI between pituitary adenomas with different secretory functions. The MIB-1 LI of pituitary adenomas was not correlated with their appearance on conventional MRI or their ADC values. Conclusion Using the PROPELLER DWI technique we confirmed that the ADC was not correlated with the consistency of pituitary adenomas. We also demonstrate that the ADC was not associated with the hormone-secreting status or the MIB-1 LI of pituitary adenomas.

Glioblastoma treated with postoperative radio-chemotherapy: Prognostic value of apparent diffusion coefficient at MR imaging

Purpose To retrospectively evaluate whether the mean, minimum, and maximum apparent diffusion coefficient (ADC) of glioblastomas obtained from pretreatment MR images is of prognostic value in patients with glioblastoma. Materials and methods The institutional review board approved our study and waived the requirement for informed patient consent. Between February 1998 and January 2006, 33 patients (24 males, 9 females; age range 10–76 years) with supratentorial glioblastoma underwent pretreatment magnetic resonance (MR) imaging. The values of the mean, minimum, and maximum ADC (ADC mean, ADC MIN, and ADC MAX, respectively) of each tumor were preoperatively determined from several regions of interest defined in the tumors. After surgical intervention, all patients underwent irradiation and chemotherapy performed according to our hospital protocol. The patient age, symptom duration, Karnofsky performance scale score, extent of surgery, and ADC were assessed using factor analysis of overall survival. Prognostic factors were evaluated using Kaplan–Meier survival curves, the log-rank test, and multiple regression analysis with the Cox proportional hazards model. Results Likelihood ratio tests confirmed that ADC MIN was the strongest among the three prognostic factors. Total surgical removal was the most important predictive factor for overall survival ( P < 0.01). ADC MIN was also statistically correlated with overall survival ( P < 0.05) and could be used to classify patients into different prognostic groups. Interestingly, ADC MIN was also the strongest prognostic factor ( P < 0.01) in the group of patients in whom total tumor removal was not possible. Conclusion The ADC MIN value obtained from pretreatment MR images is a useful clinical prognostic biomarker in patients with glioblastoma.