Diagnostic value of minimum apparent diffusion coefficient values in prediction of neuroepithelial tumor grading

Evaluation of preoperative magnetic resonance imaging features and diagnostic effectiveness of grades II and III intracranial solitary fibroma

OBJECTIVES

To explore the value of preoperative magnetic resonance imaging (MRI) characterization of intracranial solitary fibrous tumors (ISFT) and to evaluate the effectiveness of preoperative MRI features in predicting pathological grading.

MATERIALS AND METHODS

This retrospective analysis comprised the clinical and preoperative MRI characterization of 55 patients with ISFT in our hospital, including 27 grade II cases and 28 grade III cases confirmed by postoperative pathology. Variables included age, sex, tumor location, cross-midline status, signal characteristics of T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), T2-fluid-attenuated inversion recovery (T2-FLAIR), and diffusion‑weighted imaging (DWI), peritumoral edema, intralesional hemorrhage, focal necrosis/cystic degeneration, tumor empty vessel, maximum tumor diameter, maximum, minimum, and average values of apparent diffusion coefficient (ADCmax, ADCmin, and ADCmean), tumors enhancement mode, meningeal tail sign, skull invasion, cerebral parenchymal invasion, and venous sinus involvement. The independent samples t test or Mann-Whitney U test was performed to compare continuous data between the two groups, and the Pearson chi-squared test or Fisher's exact test was used to compare categorical data. In addition, bivariate logistic regression was performed to construct a comprehensive model, and receiver operating characteristic (ROC) curves were generated to calculate the areas under the curve (AUCs), thereby determining the value of each parameter in the differential diagnosis of grades II and III ISFT.

RESULTS

The mean age at onset was similar between patients with grades II and III ISFT (46.77 ± 14.66 years and 45.82 ± 12.07 years, respectively). The proportions of men among patients with grades II and III ISFT were slightly higher than those of female patients (male/female: 1.25 [15/12] and 1.33 [16/12], respectively). There were significant differences between grades II and III ISFT in the T2-FLAIR and DWI signal characteristics, maximum, minimum, and average values of the apparent diffusion coefficient (ADCmax, ADCmin, and ADCmean), tumor location, and skull invasion (P = 0.001, P = 0.018, P = 0.000, P = 0.000, P = 0.000, P = 0.010, and P = 0.032, respectively). However, no significant differences were noted between grades II and III ISFT in age, sex, cross-midline status, T1WI and T2WI signal characteristics, peritumoral edema, intralesional hemorrhage, focal necrosis/cystic degeneration, tumor empty vessel shadow, enhancement mode, meningeal tail sign, maximum tumor diameter, brain parenchyma invasion, or venous sinus involvement (all P > 0.05). Moreover, binary logistic regression analysis showed that the model accuracy was 89.1% when ADCmin was included in the regression equation. Moreover, ROC curve analysis showed that the AUC of ADCmin was 0.805 (0.688, 0.922), sensitivity was 74.1%, specificity was 75.0%, and the cutoff value was 672 mm2/s.

CONCLUSIONS

Grade III ISFT patients displayed more mixed T2-FLAIR signal characteristics and DWI signal characteristics than grade II patients, as shown by higher skull invasion and tumor mass collapse midline distribution and lower ADCmax, ADCmean, and ADCmin values. The ADCmin value was significant in the preoperative assignment of grades II and III ISFT, thereby contributing to enhanced accuracy in the imaging grading diagnosis of the disease.

Intra-tumoral susceptibility signal: a post-processing technique for objective grading of astrocytoma with susceptibility-weighted imaging

BACKGROUND

Susceptibility-weighted imaging (SWI) is sensitive to the accumulation of paramagnetic substances, such as hemorrhage and increased venous vasculature, both being frequently found in high-grade tumors. The purpose of this retrospective study is to differentiate high-grade and low-grade astrocytoma by objectively measuring quantitative intra-tumoral susceptibility signals (qITSS) on SWI.

METHODS

Precontrast SWI and 3D contrast-enhanced T1WI of 65 patients with astrocytoma were collected at 1.5 Tesla. All tumors were histologically confirmed and classified into two groups: high grade (WHO grade III and IV, n=50) and low grade (WHO grade II, n=15). After manual delineation of the tumor on T1WI, normalized contrast (NC) was calculated voxel by voxel within the tumor by using the concept of contrast to noise ratio. Thresholding on NC was applied to detect qITSS, and the volumetric percentage of qITSS can be obtained for each tumor. Two-sample t-test was applied to examine significant difference of qITSS percentage between high-grade and low-grade astrocytoma for different NC thresholds, ranging from 4 to 20. Receiver operating characteristic analysis was performed to evaluate the performance of differentiation.

RESULTS

P value was less than 0.01 for a large range of NC thresholds [4-20], reflecting significant difference of qITSS percentage between high-grade and low-grade astrocytoma. The area under the receiver operating characteristic curve was larger than 0.9 at NC thresholds from 8 to 16 and peaks at 0.949 with a NC threshold of 14. It was shown that astrocytoma grading by qITSS percentage is successful for a wide range of NC threshold, demonstrating robustness on threshold selection.

CONCLUSIONS

Without relying on the selection of slice position and at the same time providing objective identification of hypointense signal in SWI, the qITSS percentage can be used to distinguish high-grade and low-grade astrocytoma reliably.

Diagnostic role of apparent diffusion coefficient combined with intratumoral susceptibility signals in differentiating high-grade gliomas from brain metastases

OBJECTIVE

The aim of this study was to assess whether tumoral and peritumoral apparent diffusion coefficient values and intratumoral susceptibility signals on susceptibility-weighted imaging could distinguish between high-grade gliomas and brain metastases, and to investigate their associations with the Ki-67 proliferation index.

MATERIALS AND METHODS

Fifty-seven patients with pathologically confirmed diagnoses of either high-grade glioma or brain metastasis were enrolled in this study (23 with high-grade gliomas and 34 with brain metastases). The minimum and mean apparent diffusion coefficients in the enhancing tumoral region (ADC_min and ADC_mean) and the minimum apparent diffusion coefficient in the peritumoral region (ADC_edema) were measured from apparent diffusion coefficient maps, and intratumoral susceptibility signal grades acquired by susceptibility-weighted imaging were calculated. Ki-67 proliferation index values were obtained from the hospital database. These parameters were evaluated using the Mann-Whitney U test, independent-sample t-test, Spearman correlation analysis, receiver operating characteristic curve, and logistic regression analyses.

RESULTS

ADC_mean, ADC_min values, and intratumoral susceptibility signal grades in brain metastases were significantly lower than those in high-grade gliomas (all p < 0.05). Ki-67 proliferation index values showed significant correlations with ADC_mean, ADC_min, and intratumoral susceptibility signal grade in brain metastases (all p < 0.05), but no correlation was found in high-grade gliomas (all p > 0.05). According to receiver operating characteristic curve analysis, ADC_mean achieved the highest diagnostic performance for discriminating high-grade gliomas from brain metastases. Furthermore, the combination of tumoral apparent diffusion coefficient parameters with intratumoral susceptibility signal grade provided a higher area under the curve than univariate parameters.

CONCLUSION

The combination of tumoral apparent diffusion coefficient with intratumoral susceptibility signal grade can offer better diagnostic performances for differential diagnosis. Apparent diffusion coefficient and intratumoral susceptibility signal may reflect cellular proliferative activity in brain metastases, but not in high-grade gliomas.

Efficiency of High and Standard b Value Diffusion-Weighted Magnetic Resonance Imaging in Grading of Gliomas

Background

Glioma is the most common fatal malignant tumor of the CNS. Early detection of glioma grades based on diffusion-weighted imaging (DWI) properties is considered one of the most recent noninvasive promising tools in the assessment of glioma grade and could be helpful in monitoring patient prognosis and response to therapy.

Aim

This study aimed to investigate the accuracy of DWI at both standard and high b values (b = 1000 s/mm² and b = 3000 s/mm²) to distinguish high-grade glioma (HGG) from low-grade glioma (LGG) in clinical practice based on histopathological results.

Materials and Methods

Twenty-three patients with glioma had DWI at l.5 T MR using two different b values (b = 1000 s/mm² and b = 3000 s/mm²) at Al-Shifa Medical Complex after obtaining ethical and administrative approvals, and data were collected from March 2019 to March 2020. Minimum, maximum, and mean of apparent diffusion coefficient (ADC) values were measured through drawing region of interest (ROI) on a solid part at ADC maps. Data were analyzed by using the MedCalc analysis program, version 19.0.4, receiver operating characteristic (ROC) curve analysis was done, and optimal cutoff values for grading gliomas were determined. Sensitivity and specificity were also calculated.

Results

The obtained results showed the ADC_mean, ADC_ratio, ADC_max, and ADC_min were performed to differentiate between LGG and HGG at both standard and high b values. Moreover, ADC values were inversely proportional to glioma grade, and these differences are more obvious at high b value. Minimum ADC values using standard b value were 1.13 ± 0.17 × 10⁻³ mm²/s, 0.89 ± 0.85 × 10⁻³ mm²/s, and 0.82 ± 0.17 × 10⁻³ mm²/s for grades II, III, and IV, respectively. Concerning high b value, ADC_min values were 0.76 ± 0.07 × 10⁻³ mm²/s, 0.61 ± 0.01 × 10⁻³ mm²/s, and 0.48 ± 0.07 × 10⁻³ mm²/s for grades II, III, and IV, respectively. ADC values were inversely correlated with results of glioma grades, and the correlation was stronger at ADC₃₀₀₀ (r = −0.722, P ≤ 0.001). The ADC₃₀₀₀ achieved the highest diagnostic accuracy with an area under the curve (AUC) of 0.618, 100% sensitivity, 85.7% specificity, and 85.7% accuracy for glioma grading at a cutoff point of ≤0.618 × 10⁻³ mm²/s. The high b value showed stronger agreement with histopathology compared with standard b value results (k = 0.89 and 0.79), respectively.

Conclusion

The ADC values decrease with an increase in tumor cellularity. Meanwhile, high b value provides better tissue contrast by reflecting more tissue diffusivity. Therefore, ADC-derived parameters at high b value are more useful in the grading of glioma than those obtained at standard b value. They might be a better surrogate imaging sequence in the preoperative evaluation of gliomas.

Meta-analysis of the diagnostic performance of diffusion magnetic resonance imaging with apparent diffusion coefficient measurements for differentiating glioma recurrence from pseudoprogression

OBJECTIVE

The accurate differentiation of glioma recurrence from pseudoprogression (PSP) after therapy remains a considerable clinical challenge. Several studies have shown that diffusion magnetic resonance imaging (MRI) has potential value in distinguishing these 2 outcomes. The current meta-analysis examined the diagnostic accuracy of diffusion MRI with the apparent diffusion coefficient (ADC) in the differentiation of glioma recurrence from PSP.

METHOD

PubMed, Embase, Cochrane Library, and Chinese Biomedical databases were reviewed to identify studies that fulfilled our inclusion/exclusion criteria and were published on or before May 5, 2019. Threshold effects; heterogeneity; pooled sensitivity (SENS), specificity, positive likelihood ratio, and negative likelihood ratio; and diagnostic odds ratio were calculated. The overall diagnostic usefulness of diffusion MRI-derived ADC values was assessed by calculating the area under the curve (AUC) following summary receiver operating characteristic (SROC) analysis.

RESULTS

Six eligible studies examined a total of 214 patients. Calculation of pooled values indicated the SENS was 0.95 (95% confidence interval [CI] = 0.89-0.98), specificity was 0.83 (95% CI = 0.72-0.91), positive likelihood ratio was 4.82 (95% CI = 2.93-7.93), negative likelihood ratio was 0.08 (95% CI = 0.04-0.17), and diagnostic odds ratio was 59.63 (95% CI = 22.63-157.37). The SROC AUC was 0.9322. Publication bias was not significant, and SENS analysis indicated the results were relatively stable.

CONCLUSIONS

Our meta-analysis indicated that diffusion MRI with quantitative ADC is an effective approach for differentiation of glioma recurrence from PSP, and can be used as an auxiliary tool to diagnose glioma progression.

Accuracy of ADC derived from DWI for differentiating high-grade from low-grade gliomas: Systematic review and meta-analysis

OBJECTIVE

Quantitative apparent diffusion coefficient (ADC) values of diffusion weighted imaging (DWI) could be applied to grade gliomas. This meta-analysis was conducted to assess the accuracy of ADC analysis in differentiating high-grade (HGGs) from low-grade gliomas (LGGs).

METHODS

PubMed, Cochrane library, Science Direct, and Embase were searched to identify suitable studies up to September 1, 2018. The quality of studies was evaluated by the quality assessment of diagnostic accuracy studies (QUADAS 2). We estimated the pooled sensitivity, specificity, positive and negative likelihood ratios (LR), diagnostic accuracy ratio (DOR) with 95% confidence intervals (CI), and determined the accuracy of the data by using the summary receiver operating characteristic (SROC) and calculating the area under the curve (AUC) to identity the accuracy of ADC analysis in grading gliomas.

RESULTS

Eighteen studies including 1172 patients were included and analyzed. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC with 95% CIs of DWI with b values of 1000 s/mm for separating HGGs from LGGs were 0.81 (95% CI 0.75-0.86), 0.87 (95% CI 0.81-0.91), 6.1 (95% CI 4.2-8.9), 0.22 (95% CI 0.17-0.29), 28 (95% CI 17-45), and 0.91 (95% CI 0.88-0.93), respectively. DWI with b values of 3000 s/mm showed slightly higher accuracy than that of 1000 (sensitivity 0.80, specificity 0.90 and AUC 0.92). Meta-regression analyses showed that field strengths and b values had significant impacts on diagnostic efficacy. Deeks testing confirmed no significant publication bias in all studies.

CONCLUSIONS

This meta-analysis suggested that ADC analysis of DWI have high accuracy in differentiating HGGs from LGGs. Standardized methodology is warranted to guide the use of this technique for clinical decision-making.

Grading Gliomas Capability: Comparison between Visual Assessment and Apparent Diffusion Coefficient (ADC) Value Measurement on Diffusion-Weighted Imaging (DWI)

Background:

To compare diagnostic accuracy between DWI visual scale assessment and ADC value measurement of solid portion of the tumor in grading gliomas.

Methods:

This retrospective study included 38 patients who had pathologically proven gliomas between January 2013 and August 2018 with 18 low grade and 20 high grade tumors. All patients underwent MRI and biopsy. Two readers reviewed DWI visual scale independently. Disagreement was resolved by consensus. One reviewer measured ADC value of entire solid part of the tumor in single axial slice with greatest dimension of tumor which was chosen by consensus. Two data sets of visual scale and ADC value were analyzed and comparison of diagnostic accuracy in glioma grading was done by using area under the curve (AUC) of receiver operating characteristic curve (ROC).

Results:

Visual scale and ADC value could be used to distinguish between low and high grade gliomas with a statistically significant difference. (P-value 0.002 and <0.001). Almost all high grade gliomas had visual scale 5. The sensitivity, specificity, PPV NPV and accuracy were 50%, 100%, 100% , 64.3%,73.68% respectively. The cutoff level for the ADC value was determined to be 1119.48 x10^-6 mm²/s in differentiation between low and high grade gliomas with the sensitivity, specificity, PPV, NPV, accuracy of 90%, 88.89% , 90%, 88.9% and 89.47% respectively. There was no statistically significant difference(P-value = 0.163).

Conclusion:

Both Visual scale and ADC value were capable of differentiating between low and high grade gliomas. Although visual scale may not replace ADC measurement, larger scale prospective study is needed for validate this initial result.

Apparent diffusion coefficient values and non-homogeneity of diffusion in brain tumors in diffusion-weighted MRI

Background

The values that have been received from apparent diffusion coefficient (ADC) maps of diffusion-weighted magnetic resonance imaging (DW-MRI) might play a vital role in evaluating tumors and their grading scale.

Purpose

To investigate the predictive role of this heterogeneity in brain tumor pathologies and its correlation with Ki-67.

Material and Methods

A total of 124 patients with brain tumors underwent brain MRI with gadolinium injection. ADC and standard deviation of each lesion have been obtained from manual localization of the region of interest on the ADC map. A receiver operating characteristic analysis was conducted to determine the minimum cut-off values of the mean ADC and mean standard deviation of ADC maps having the highest sensitivity and specificity to differentiate high-grade and low-grade tumors.

Results

Mean ADC values in the region of interest were significantly lower for malignant tumors (grade IV and metastasis) than grade I brain tumors, while a higher mean standard deviation was observed. In a more detailed comparison of tumor groups, the mean standard deviation of the ADC for glioblastoma multiform was significantly higher than meningioma grade I ( P < 0.001) and metastasis was significantly higher than grade III and IV astrocytic tumors ( P = 0.004). The analysis of Ki-67 proliferation index and mean ADC values in gliomas showed a significant inverse correlation between the parameters (r = –0.0429, P < 0.001) and direct correlation between Ki-67 and mean standard deviation of the ADC (r = 0.551, P < 0.001). As an index for the ADC to differentiate high-grade and low-grade tumors, the cut-off values of 1.40*10−3 mm2/s for mean ADC and 45*10−3 mm2/s for mean standard deviation have the highest combination of sensitivity, specificity, and area under the curve.

Conclusion

The mean value and standard deviation of the ADC could be considered for differentiating between low-grade and high-grade brain tumors, as two available non-invasive methods.

Whole-tumor histogram analysis of apparent diffusion coefficient in differentiating intracranial solitary fibrous tumor/hemangiopericytoma from angiomatous meningioma

PURPOSE

To assess the role of histogram analysis of apparent diffusion coefficient (ADC) maps based on whole-tumor in differentiating intracranial solitary fibrous tumor/hemangiopericytoma (SFT/HPC) from angiomatous meningioma (AM).

MATERIALS AND METHODS

Pathologically confirmed intracranial SFT/HPC (n = 15) and AM (n = 20) were retrospectively collected and their clinical and conventional MRI features were analyzed. Diffusion-weighted (DW) images (b = 0 and 1000 s/mm²) were processed with the mono-exponential model. Regions of interest covering the whole tumor were drawn on all slices of the ADC maps to obtain histogram parameters, including mean ADC (ADCmean), median ADC (ADCmedian), maximum ADC (ADCmax), minimum ADC (ADCmin), skewness and kurtosis, as well as the 5th, 10th, 25th, 75th, 90th and 95th percentile ADC (ADC5, ADC10, ADC25, ADC75, ADC90 and ADC95). Differences of histogram parameters between SFT/HPC and AM were compared using Mann-Whitney U test. Receiver operating characteristic (ROC) curve was used to determine the diagnostic performance.

RESULTS

The ADCmin (P = 0.001) and ADC5 (P = 0.045) were significantly lower in SFT/HPCs than in AMs, while no significant difference was found in sex, age, conventional MRI features or any other histogram parameters between the two entities (P = 0.051-1.000). ADCmin showed the best diagnostic performance (area under curve [AUC], 0.86; sensitivity, 81.3%; specificity, 83.3%) in differentiating SFT/HPC from AM with optimal cutoff value being 569.00 × 10^-6  mm²/s, followed by ADC5 (AUC, 0.72; sensitivity, 68.8%; specificity, 75%) with optimal cutoff value being 781.97 × 10^-6  mm²/s.

CONCLUSION

SFT/HPC and AM share similar conventional MR appearances. Whole-tumor histogram analysis of ADC maps may be a useful tool for differential diagnosis, with ADCmin and ADC5 being potential parameters.

Apparent diffusion coefficient values in differential diagnosis and prognostic prediction of solitary of fibrous tumor/hemangiopericytoma (WHOII) and atypical meningioma

BACKGROUND

It is difficult to distinguish solitary of fibrous tumor/hemangiopericytoma (SFT/HPC) from atypical meningioma (AM) by conventional imaging.As far as we know,diffusion weighting imaging may identify them effectively.

OBJECTIVE

The purpose of this study was to determine the role of apparent diffusion coefficient (ADC) values to distinguish and predict prognosis of solitary of fibrous tumor/hemangiopericytoma (SFT/HPC) (WHOII) and atypical meningioma (AM).

METHODS

Preoperative diffusion-weighted imaging (DWI) of 30 cases with histopathologic and immunhistochemical testified SFT/HPC WHOII (n= 11) and AM (n= 19) were performed retrospectively. The ADC values of lesion, peritumoral edema, normal white matter and lesion NADC ratio (lesion ADC values/ADC values of normal white matter (NWN ADC)) were compared. The immunhistochemical markers (Ki-67, CD34, Vim, EMA, GFAP, S-100, PR, CD56) were compared. The correlation between the ADC values and Ki-67 index was evaluated.

RESULTS

The mean lesion ADC values of SFT/HPC (1.15 ± 0.04 × 10-3 mm2/s) was significantly higher than that of AM (0.80 ± 0.04 × 10-3 mm2/s) (t= 23.824, p< 0.05). The mean NADC ratio was lower for AM (1.03 ± 0.06) compared with SFT/HPC (1.51 ± 0.05) (t= 23.105, p< 0.05). The mean edema ADC for SFT/HPC (1.47 ± 0.06 × 10-3 mm2/s) was lower compared with AM (1.68 ± 0.05 × 10-3 mm2/s) (t=-9.926, p< 0.05 ). There was no statistical difference between the two groups of NWM ADC (t=-1.475, p> 0.05) . The mean Ki-67 of SFT/HPC (7.18 ± 2.60%) was lower than the mean Ki-67 of AM (13.58 ± 4.50%) (t=-4.934, p< 0.05). The CD34 showed statistically differences between two groups (X2= 13.659, p< 0.05). The EMA also showed statistically differences between two groups (X2= 4.474, p< 0.05). Vim,GFAP, S-100, PR, CD56 showed no statistical difference in the two group (p> 0.05). The pearson analysis indicated that there was a negative correlation between lesion ADC and Ki-67 in SFT/HPC group (r=-0.770, p< 0.05) and AM group (r=-0.727, p< 0.05). There was also a negative correlation between lesion NADC ratio and Ki-67 in SFT/HPC group (r=-0.673, p< 0.05) and AM group (r=-0.707, p< 0.05). There was a positive correlation between edema ADC and Ki-67 in SFT/HPC group (r= 0.819, p< 0.05) and AM group (r= 0.942, p< 0.05). Furthermore,there was no correlation between NWM A DC and Ki-67 in SFT/HPC group (r=-0.403, p> 0.05) and AM group (r= 0.202, p> 0.05).

CONCLUSIONS

The lesion ADC, lesion NADC ratio and edema ADC can distinguish the SFT/HPC WHO II from AM and be helpful to predict prognosis of the two tumors before operation. Further more, histopathologic and immunhistochemical can make a definite diagnosis of the two tumors.

Use of Apparent Diffusion Coefficient Histogram in Differentiating Between Medulloblastoma and Pilocytic Astrocytoma in Children

Background

This research aimed to investigate the value of apparent diffusion coefficient (ADC) histogram in differentiating between medulloblastoma and pilocytic astrocytoma in children.

Material/Methods

Thirty-three children with posterior cranial fossa tumor confirmed by operation and pathology participated in this retrospective study, including 18 children with medulloblastoma and 15 children with pilocytic astrocytoma. ADC images of the maximum lay of tumors were selected, and the region of interest was delineated by Mazda software and analyzed by histogram. Histogram characteristic parameters of the 2 tumors were statistically analyzed to determine the significantly different characteristic parameters between the 2 tumor types.

Results

There were significant differences in the mean value, variance, skewness, kurtosis, and 1^th, 10^th, 50^th, and 90^th percentiles of 9 characteristic parameters extracted by histogram (P<0.05). The corresponding receiver operating characteristic (ROC) curves were drawn, in which the mean value and 50^th percentile were best identified. When the maximum area under the ROC curve was 1 and the optimal threshold was 137.7 and 125.5, the specificity and sensitivity were both 100%.

Conclusions

ADC histograms can be used to differentiate between medulloblastoma and pilocytic astrocytoma in children and provide reliable and objective evidence for the differentiation.

Diagnostic performance of apparent diffusion coefficient parameters for glioma grading

This study was to evaluate the diagnostic performance of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) parameters derived from diffusion tensor imaging in the differentiation between grade II and III gliomas. The records of 60 patients (30 women, 30 men; mean age, 45.4 years) suspected of having gliomas who underwent an ADC image-guided stereotactic biopsy were retrospectively reviewed. The values of FA and ADC were measured, and the sensitivity, specificity, accuracy and area under the curve (AUC) of those parameters were calculated based on the receiver operating characteristic curve analysis. A predictive diagnostic equation was also constructed and evaluated. Significant differences in minimum ADC values were found in the quantitative analysis between the grade III and II glioma groups. The sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), accuracy and AUC for identifying grade III and II gliomas at the optimum cut-off value of 0.895 × 10^-3 mm²/s of minimum ADC were 81.0, 89.1, 77.3, 91.1, 86.6 and 0.87, respectively. The predictive diagnostic equation was superior to the single minimum ADC indicator with a sensitivity of 90.5%, a specificity of 84.8%, a PPV of 73.1%, an NPV of 95.1%, and an accuracy of 86.6%, respectively. The study provides evidence that minimum ADC values have a superior diagnostic performance in differentiating grade III and II gliomas, and the predictive diagnostic equation may be helpful in the differentiation.

Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. Part 2: ADCmin

The purpose of this part of the meta-analysis was to summarize data regarding associations between minimum apparent diffusion coefficient (ADC_min) and KI 67 in different tumors. MEDLINE library was screened for associations between ADC_min and KI 67 in different tumors up to April 2017. Overall, 23 studies with 944 patients were identified. Associations between ADC and KI 67 were analyzed by Spearman's correlation coefficient. The pooled correlation coefficient between ADC_min and KI 67 for all included tumors was ρ = -0.47. In detail, the correlation coefficients for separate tumors were as follows: cerebral lymphoma: ρ = -0.61 (95% CI = [-0.82; -0.41]); cervical cancer: ρ = -0.56 (95% CI = [-0.68;-0.43]); pituitary adenoma: ρ = -0.55 (95% CI = [-1.31; 0.22]); glioma: ρ = -0.40 (95% CI = [-0.55; -0.24]); breast cancer: ρ = -0.37 (95% CI = [-0.74; -0.01]); meningioma, ρ = -0.15 (95% CI = [-0.38; 0.07]).

Endometrial carcinoma: diffusion-weighted imaging diagnostic accuracy and correlation with Ki-67 expression

AIM

To evaluate the role of diffusion-weighted imaging (DWI) in the detection of endometrial carcinoma and to correlate the apparent diffusion coefficient (ADC) value with Ki-67 expression.

MATERIALS AND METHODS

Fifty-two patients with invasive cancer who underwent pelvic MRI were prospectively evaluated using DWI with b-values of 0 and 1000 s/mm^2.The ADC values from standard DWI were measured. The expression of Ki-67 in histological specimens was analysed using immunohistochemistry. The ADC values of endometrial carcinoma and normal endometrial parenchyma were compared. Relationships between ADC values and Ki-67 expression were determined using Wilcoxon's signed rank test and the Kruskal-Wallis test.

RESULTS

Endometrial carcinoma was detected at DWI as a hyperintense area in 92.3% (48/52) of patients. There was a significant difference in the mean ADC values between endometrial carcinoma and normal endometrial parenchyma (1.39±0.27×10^-3 versus 0.93±0.21×10^-3 mm²/s, p<0.001). The mean ADC values of grade 1 patients were significantly higher than those of grade 3 patients (1.01±0.16×10^-3 versus 0.83±0.21×10^-3 mm²/s, p<0.05). The mean ADC values of stage IB patients were significantly lower than those of stage IA patients (0.86±0.16×10^-3 versus 1.04±0.21×10^-3 mm²/s, p<0.01). The mean ADC values of high Ki-67 expression patients were significantly lower than those of low Ki-67 expression patients (0.82±0.12×10^-3 versus 1.16±0.12×10^-3 mm²/s, p<0.001). There was a significant negative correlation between the mean ADC value and Ki-67 expression (r=-0.82, p<0.001).

CONCLUSION

The ADC value was a helpful parameter for detecting the tumour grade, stage, and proliferation of endometrial carcinoma, and may further improve patient prognosis and contribute to the development of more effective treatment programmes.

The diagnostic value of high-frequency power-based diffusion-weighted imaging in prediction of neuroepithelial tumour grading

OBJECTIVES

To retrospectively evaluate the diagnostic value of high-frequency power (HFP) compared with the minimum apparent diffusion coefficient (MinADC) in the prediction of neuroepithelial tumour grading.

METHODS

Diffusion-weighted imaging (DWI) data were acquired on 115 patients by a 3.0-T MRI system, which included b0 images and b1000 images over the whole brain in each patient. The HFP values and MinADC values were calculated by an in-house script written on the MATLAB platform.

RESULTS

There was a significant difference among each group excluding grade I (G1) vs. grade II (G2) (P = 0.309) for HFP and among each group for MinADC. ROC analysis showed a higher discriminative accuracy between low-grade glioma (LGG) and high-grade glioma (HGG) for HFP with area under the curve (AUC) value 1 compared with that for MinADC with AUC 0.83 ± 0.04 and also demonstrated a higher discriminative ability among the G1-grade IV (G4) group for HFP compared with that for MinADC except G1 vs. G2.

CONCLUSIONS

HFP could provide a simple and effective optimal tool for the prediction of neuroepithelial tumour grading based on diffusion-weighted images in routine clinical practice.

KEY POINTS

• HFP shows positive correlation with neuroepithelial tumour grading. • HFP presents a good diagnostic efficacy for LGG and HGG. • HFP is helpful in the selection of brain tumour boundary.

Preoperative grading of supratentorial gliomas using high or standard b-value diffusion-weighted MR imaging at 3T

PURPOSE

The goal of this study was to compare diffusion-weighted magnetic resonance imaging (DW-MRI) using high b-value (b=3000s/mm²) to DW-MRI using standard b-value (b=1000s/mm²) in the preoperative grading of supratentorial gliomas.

MATERIALS AND METHODS

Fifty-three patients with glioma had brain DW-MRI at 3T using two different b-values (b=1000s/mm² and b=3000s/mm²). There were 35 men and 18 women with a mean age of 40.5±17.1 years (range: 18-79 years). Mean, minimum, maximum, and range of apparent diffusion coefficient (ADC) values for solid tumor ROIs (ADC_mean, ADC_min, ADC_max, and ADC_diff), and the normalized ADC (ADC_ratio) were calculated. A Kruskal-Wallis statistic with Bonferroni correction for multiple comparisons was applied to detect significant ADC parameter differences between tumor grades by including or excluding 19 patients with an oligodendroglioma. Receiver operating characteristic curve analysis was conducted to define appropriate cutoff values for grading gliomas.

RESULTS

No differences in ADC derived parameters were found between grade II and grade III gliomas. Mean ADC values using standard b-value were 1.17±0.27×10^-3mm²/s [range: 0.63-1.61], 1.05±0.22×10^-3mm²/s [range: 0.73-1.33], and 0.86±0.23×10^-3mm²/s [range: 0.52-1.46] for grades II, III and IV gliomas, respectively. Using high b-value, mean ADC values were 0.89±0.24×10^-3mm²/s [range: 0.42-1.25], 0.82±0.20×10^-3mm²/s [range: 0.56-1.10], and 0.59±0.17×10^-3mm²/s [range: 0.40-1.01] for grades II, III and IV gliomas, respectively. ADC_mean, ADC_ratio, ADC_max, and ADC_min were different between grade II and grade IV gliomas at both standard and high b-values. Differences in ADC_mean, ADC_max, and ADC_diff were found between grade III and grade IV only using high b-value.

CONCLUSION

ADC parameters derived from DW-MRI using a high b-value allows a better differential diagnosis of gliomas, especially for differentiating grades III and IV, than those derived from DW-MRI using a standard b-value.

The utility of diffusion MRI with quantitative ADC measurements for differentiating high-grade from low-grade cerebral gliomas: Evidence from a meta-analysis

OBJECTIVE

The aim of this meta-analysis was to predict the grades of cerebral gliomas using quantitative apparent diffusion coefficient (ADC) values.

MATERIALS AND METHODS

A comprehensive search of the PubMed, EMBASE, Web of Science, and Cochrane Library databases was performed up to 8, 2016. The quality assessment of diagnostic accuracy studies (QUADAS 2) was used to evaluate the quality of studies. Statistical analyses included pooling of sensitivity and specificity, positive likelihood ratio (PLR), negative likelihood ratio' (NLR), diagnostic odds ratio (DOR), and diagnostic accuracy values of the included studies using the summary receiver operating characteristic (SROC). All analyses were conducted using STATA (version 12.0), RevMan (version 5.3), and Meta-Disc 1.4 software programs.

RESULTS

Fifteen studies were analyzed and included a total of 821 patients and 821 lesions. In regards to the diagnostic accuracy of ADC maps, the pooled SEN, SPE, PLR, NLR, and DOR with 95%CIs were 0.82 [95%CI: 0.76, 0.87] and 0.75 [95%CI: 0.67, 0.81], 3.24 [95%CI: 2.48, 4.24], 0.24 [95%CI: 0.17, 0.33], and 13.60 [95%CI: 8.37, 22.07], respectively. The SROC curve showed an AUC of 0.85. Deeks testing confirmed no significant publication bias in all studies.

CONCLUSION

Our findings indicate that quantitative ADC values have high accuracy in separating high-grade from low-grade cerebral gliomas. Further studies using a standardized methodology may help guide the use of ADC values for clinical decision-making.

Alterations of diffusion tensor MRI parameters in the brains of patients with Parkinson's disease compared with normal brains: possible diagnostic use

OBJECTIVES

To investigate the diagnostic performance of diffusion tensor imaging in patients with Parkinson's disease (PD).

METHODS

We examined a total of 126 PD patients (68 males/58 females, mean age: 62.0 ±7.6 years) and 91 healthy controls (43 males/48 females, mean age: 59.8 ±7.2 years). Images were acquired on a 3 Tesla magnetic resonance scanner. The Camino software was used to normalize and parcellate diffusion-weighted images into 90 cerebral regions based on the automatic anatomical labelling template. The minimum, median, and maximum values of the mean/radial/axial diffusivity/fractional anisotropy were determined. The diagnostic performance was assessed by receiver operating characteristic analysis. The associations of imaging parameters with disease severity were tested using Pearson's correlation coefficients after adjustment for disease duration.

RESULTS

Compared with healthy controls, PD patients showed increased diffusivity in multiple cortical regions that extended beyond the basal ganglia. An area under curve of 85 % was identified for the maximum values of mean diffusivity in the ipsilateral middle temporal gyrus. The most significant intergroup difference was 26.8 % for the ipsilateral inferior parietal gyrus.

CONCLUSION

The measurement of water diffusion from the parcellated cortex may be clinically useful for the assessment of PD patients.

KEY POINTS

• Increased diffusivity was identified in multiple cortical regions of Parkinson's disease patients. • The area under the receiver operating curve was 85 % in the middle temporal gyrus. • The ipsilateral inferior parietal gyrus showed the most significant change.

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

OBJECTIVES

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).

METHODS

Pretreatment SUV and ADC were calculated in 57 patients with HNSCC. Mean follow-up was 21.3 months. Semiquantitative analysis of primary tumours was performed using SUV_maxT/B, ADC_mean, ADC_min and ADC_max. The prognostic value of SUV_maxT/B, ADC_mean, ADC_min and ADC_max in predicting disease-free survival (DFS) was evaluated with log-rank test and Cox regression models.

RESULTS

Patients with SUV_maxT/B ≥5.75 had an overall worse prognosis (p = 0.003). After adjusting for lymph node status and diameter, SUV_maxT/B and ADC_min 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 SUV_maxT/B ≥5.75 and ADC_min ≥0.58 × 10^-3 mm²/s, respectively. When the analysis was restricted to subjects with SUV_maxT/B ≥5.75, high ADC_min significantly predicted a worse prognosis, with adjusted HR = 3.11 (95 % CI 1.13-8.55).

CONCLUSIONS

The combination of SUV_maxT/B and ADC_min improves the prognostic role of the two separate parameters; patients with high SUV_maxT/B and high ADC_min are associated with a poor prognosis.

KEY POINTS

• 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.

Evaluation of astrocytoma cell proliferation using diffusion-weighted imaging: correlation with expression of proliferating cell nuclear antigen

The purpose of this study was to analyze if there is a significant correlation between the results of diffusion-weighted imaging (DWI) and the expression of proliferating cell nuclear antigen (PCNA) in astrocytomas. The DWI scans of 19 different-grade astrocytomas were obtained on a 3 T magnetic resonance scanner. The average regional apparent diffusion coefficients (ADC) were measured. The positive expression of PCNA was determined immunohistochemically by using streptavidin-peroxidase complex staining, and was quantified by calculating its calibrated opacity density (COD) using an image analysis system. The average regional ADC and PCNA COD of low grade and high grade astrocytomas were compared. Correlations between regional ADC and PCNA COD were analyzed. The average regional ADC of high grade astrocytomas was significantly (t = 10.169, P = 0.000) less (0.687 ± 0.225 × 10⁻³ mm²/s) than that of low grade astrocytomas (1.572 ± 0.333 × 10⁻³ mm²/s). The PCNA COD (0.343 ± 0.052) of high grade astrocytomas was significantly (t=−7.858, P=0.000) greater than that (0.194 ± 0.012) of low grade astrocytomas. There were strong negative correlations between regional ADC and PCNA COD (r = −0.801, P = 0.000). The results demonstrated that DWI is helpful in evaluating cell proliferation and preoperatively grading astrocytomas by measuring regional ADC.

Astrocytic tumour grading: a comparative study of three-dimensional pseudocontinuous arterial spin labelling, dynamic susceptibility contrast-enhanced perfusion-weighted imaging, and diffusion-weighted imaging

OBJECTIVES

We hypothesized that three-dimensional pseudocontinuous arterial spin labelling (pCASL) may have similar efficacy in astrocytic tumour grading as dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI), and the grading accuracy may be further improved when combined with apparent diffusion coefficient (ADC) values.

METHODS

Forty-three patients with astrocytic tumours were studied using diffusion weighted imaging (DWI), pCASL, and DSC-PWI. Histograms of ADC and normalized tumour cerebral blood flow values (nCBF on pCASL and nrCBF on DSC-PWI) were measured and analyzed.

RESULTS

The mean 10 % ADC value was the DWI parameter that provided the best differentiation between low-grade astrocytoma (LGA) and high-grade astrocytoma (HGA). The nCBF and nrCBF (1.810 ± 0.979 and 2.070 ± 1.048) in LGA were significantly lower than those (4.505 ± 2.270 and 5.922 ± 2.630) in HGA. For differentiation between LGA and HGA, the cutoff values of 0.764 × 10(-3) mm(2)/s for mean 10 % ADC, 2.374 for nCBF, and 3.464 for nrCBF provided the optimal accuracy (74.4 %, 86.1 %, and 88.6 %, respectively). Combining the ADC values with nCBF or nrCBF could further improve the grading accuracy to 97.7 % or 95.3 %, respectively.

CONCLUSIONS

pCASL is an alternative to DSC-PWI for astrocytic tumour grading. The combination of DWI and contrast-free pCASL offers a valuable choice in patients with risk factors.

KEY POINTS

• pCASL shows positive correlation with DSC-PWI in astrocytic tumour grading. • ADC values based on ADC histograms can be an objective method. • Combination of DWI and pCASL or DSC-PWI can improve grading accuracy.

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

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.

Use of apparent diffusion coefficient values for diagnosis of pediatric posterior fossa tumors

We prospectively compared the ability of neuroradiologists to diagnose medulloblastoma with novice raters using only apparent diffusion coefficient (ADC) values measured on ADC maps. One hundred and three pediatric patients with pre-operative magnetic resonance imaging scans showing a posterior fossa tumor with histological verification were retrospectively identified from a ten-year period at a tertiary care medical center. A single observer measured the lowest ADC values in all tumors to determine the mean minimum ADC (ADCmin) value that provided greatest accuracy in distinguishing medulloblastomas from other tumors, which was determined to be 0.66×10(-3) mm(2)/s. Imaging studies, including ADC maps, from 90 patients were provided to two neuroradiologists, who provided a diagnosis, which was later dichotomized as medulloblastoma or other. Two medical students measured ADCmin within tumors and those with ADCmin < 0.66×10(-3) mm(2)/s were recorded as medulloblastoma; any other value was recorded as other. Diagnostic accuracy was measured. ADCmin values allowed a correct identification of lesions as either medulloblastoma or other in 91% of cases. After diagnoses by the two neuroradiologists were categorized as either medulloblastoma or other, their diagnoses were correct in 90% and 84% of cases, respectively. In 19 cases, at least one neuroradiologist was incorrect; the addition of ADC values to clinical interpretation would have allowed a correct diagnosis in 63% of such cases. Diagnostic accuracy based on ADC values by medical students was comparable to that of subspecialty-trained neuroradiologists. Our findings suggest that the addition of ADC values to standard film interpretation may improve the diagnostic rate for these tumors.

Evaluation of apparent diffusion coefficient thresholds for diagnosis of medulloblastoma using diffusion-weighted imaging

We assess a diffusion-weighted imaging (DWI) analysis technique as a potential basis for computer-aided diagnosis (CAD) of pediatric posterior fossa tumors. A retrospective medical record search identified 103 children (mean age: 87 months) with posterior fossa tumors having a total of 126 preoperative MR scans with DWI. The minimum ADC (ADCmin) and normalized ADC (nADC) values [ratio of ADCmin values in tumor compared to normal tissue] were measured by a single observer blinded to diagnosis. Receiver operating characteristic (ROC) curves were generated to determine the optimal threshold for which the nADC and ADCmin values would predict tumor histology. Inter-rater reliability for predicting tumor type was evaluated using values measured by two additional observers. At histology, ten tumor types were identified, with astrocytoma (n=50), medulloblastoma (n=33), and ependymoma (n=9) accounting for 89%. Mean ADCmin (0.54 × 10(-3) mm(2)/s) and nADC (0.70) were lowest for medulloblastoma. Mean ADCmin (1.28 × 10(-3) mm(2)/s) and nADC (1.64) were highest for astrocytoma. For the ROC analysis, the area under the curve when discriminating medulloblastoma from other tumors using nADC was 0.939 and 0.965 when using ADCmin. The optimal ADCmin threshold was 0.66 × 10(-3) mm(2)/s, which yielded an 86% positive predictive value, 97% negative predictive value, and 93% accuracy. Inter-observer variability was very low, with near perfect agreement among all observers in predicting medulloblastoma. Our data indicate that both ADCmin and nADC could serve as the basis for a CAD program to distinguish medulloblastoma from other posterior fossa tumors with a high degree of accuracy.

Apparent diffusion coefficient value reflects invasive and proliferative potential of bladder cancer

PURPOSE

To elucidate a role of apparent diffusion coefficient (ADC) value as a biomarker of bladder cancer, we investigated its associations with Ki-67 labeling index (LI) along with classical clinicopathological prognosticators.

MATERIALS AND METHODS

Diffusion-weighted MRI (DW-MRI) at 1.5 Tesla using b-values of 0, 500, 1000, and 2000 s/mm(2) was prospectively taken before transurethral resection by 132 bladder cancer patients. ADC value of index tumors was measured and compared with clinicopathological prognosticators including Ki-67 LI.

RESULTS

ADC value was significantly lower in tumors with higher Ki-67 LIs, sessile tumors (versus papillary), larger tumors, higher grade disease, and higher T stage disease. ADC value inversely correlated with Ki-67 LI (ρ = -0.57; P < 0.0001). On multiple regression analysis, T stage and Ki-67 LI significantly correlated with ADC value. The Akaike information criterion confirms these two parameters constitute the best model for determining ADC value. Similarly, T stage and ADC value significantly correlated with Ki-67 LI and these two parameters composed the best model for predicting Ki-67 LI.

CONCLUSION

ADC value would reflect T stage and Ki-67 LI, representing invasive and proliferative potential, respectively. ADC value is likely to serve as a biomarker reflecting aggressiveness of bladder cancer.

Intracranial hemangiopericytoma: MR imaging findings and diagnostic usefulness of minimum ADC values

PURPOSE

To describe the clinical and magnetic resonance (MR) imaging features of primary intracranial hemangiopericytoma (HPC), and to assess the usefulness of minimum apparent diffusion coefficient (MinADC) value of HPC in the differential diagnosis from meningioma.

MATERIALS AND METHODS

From 2004 to 2010, fifteen patients with primary intracranial HPC were included. The clinical data, conventional MR findings (n = 15), and diffusion weighted image (DWI) features (n = 10) were retrospectively analyzed. MinADC value of the HPCs (n = 10) was measured on ADC map and was compared with that of meningiomas (n = 37).

RESULTS

In 15 cases of HPC, isointense signal was detected on both T1-weighted images (T1WI) and T2-weighted images (T2WI) in 11 cases, and heterogeneous signal was demonstrated in 4 cases. Isointensity (n = 9) and iso- and slight hyperintensity (n = 1) were shown on DWI. The mean MinADC value of HPC [(1.116 ± 0.127) × 10(-3) mm(2) /s] was significantly higher than that of meningioma [(0.875 ± 0.104) × 10(-3) mm(2) /s] (P < 0.01). For the differentiation between HPC and meningioma, the critical cutoff MinADC value was 0.991 × 10(-3) mm(2) /s, which provided the best combination of sensitivity (88.9%) and specificity (82.4%).

CONCLUSION

MinADC value may be an useful tool for the differentiation between HPC and meningioma.

Functional imaging of head and neck squamous cell carcinoma with diffusion-weighted MRI and FDG PET/CT: quantitative analysis of ADC and SUV

Purpose

Head and neck squamous cell carcinoma (HNSCC) may cause a decreased apparent diffusion coefficient (ADC) on diffusion-weighted magnetic resonance imaging (DW MRI) and an increased standardized uptake value (SUV) on fluorodeoxyglucose (FDG) positron emission tomography (PET/CT). We analysed the reproducibility of ADC and SUV measurements in HNSCC and evaluated whether these biomarkers are correlated or independent.

Methods

This retrospective analysis of DW MRI and FDG PET/CT data series included 34 HNSCC in 33 consecutive patients. Two experienced readers measured tumour ADC and SUV values independently. Statistical comparison and correlation with histopathology was done. Intra- and inter-observer agreement for ADC and SUV measurements was assessed.

Results

Intraclass correlation coefficient (ICC) analysis showed almost perfect reproducibility (>0.90) for ADC_mean, ADC_min, SUV_max and SUV_mean values for intra-observer and inter-observer agreement. Mean ADC_mean and ADC_min in HNSCC were 1.05 ± 0.34 × 10⁻³ mm²/s and 0.65 ± 0.29 × 10⁻³ mm²/s, respectively. Mean SUV_mean and mean SUV_max were 7.61 ± 3.87 and 12.8 ± 5.0, respectively. Although statistically not significant, a trend towards higher SUV and lower ADC was observed with increasing tumour dedifferentiation. Pearson’s correlation analysis showed no significant correlation between ADC and SUV measurements (r −0.103, −0.051; p 0.552, 0.777).

Conclusion

Our data suggest that ADC and SUV values are reproducible and independent biomarkers in HNSCC.

Functional imaging of head and neck squamous cell carcinoma with diffusion-weighted MRI and FDG PET/CT: quantitative analysis of ADC and SUV

PURPOSE

Head and neck squamous cell carcinoma (HNSCC) may cause a decreased apparent diffusion coefficient (ADC) on diffusion-weighted magnetic resonance imaging (DW MRI) and an increased standardized uptake value (SUV) on fluorodeoxyglucose (FDG) positron emission tomography (PET/CT). We analysed the reproducibility of ADC and SUV measurements in HNSCC and evaluated whether these biomarkers are correlated or independent.

METHODS

This retrospective analysis of DW MRI and FDG PET/CT data series included 34 HNSCC in 33 consecutive patients. Two experienced readers measured tumour ADC and SUV values independently. Statistical comparison and correlation with histopathology was done. Intra- and inter-observer agreement for ADC and SUV measurements was assessed.

RESULTS

Intraclass correlation coefficient (ICC) analysis showed almost perfect reproducibility (>0.90) for ADCmean, ADCmin, SUVmax and SUVmean values for intra-observer and inter-observer agreement. Mean ADCmean and ADCmin in HNSCC were 1.05 ± 0.34 × 10(-3) mm(2)/s and 0.65 ± 0.29 × 10(-3) mm(2)/s, respectively. Mean SUVmean and mean SUVmax were 7.61 ± 3.87 and 12.8 ± 5.0, respectively. Although statistically not significant, a trend towards higher SUV and lower ADC was observed with increasing tumour dedifferentiation. Pearson's correlation analysis showed no significant correlation between ADC and SUV measurements (r -0.103, -0.051; p 0.552, 0.777).

CONCLUSION

Our data suggest that ADC and SUV values are reproducible and independent biomarkers in HNSCC.

Quantifying heterogeneity in human tumours using MRI and PET

Most tumours, even those of the same histological type and grade, demonstrate considerable biological heterogeneity. Variations in genomic subtype, growth factor expression and local microenvironmental factors can result in regional variations within individual tumours. For example, localised variations in tumour cell proliferation, cell death, metabolic activity and vascular structure will be accompanied by variations in oxygenation status, pH and drug delivery that may directly affect therapeutic response. Documenting and quantifying regional heterogeneity within the tumour requires histological or imaging techniques. There is increasing evidence that quantitative imaging biomarkers can be used in vivo to provide important, reproducible and repeatable estimates of tumoural heterogeneity. In this article we review the imaging methods available to provide appropriate biomarkers of tumour structure and function. We also discuss the significant technical issues involved in the quantitative estimation of heterogeneity and the range of descriptive metrics that can be derived. Finally, we have reviewed the existing clinical evidence that heterogeneity metrics provide additional useful information in drug discovery and development and in clinical practice.

Value of Diffusion-Weighted Imaging in Grading Tumours Localized in the Fourth Ventricle Region by Visual and Quantitative Assessments

This study investigated visual and quantitative assessment of diffusion-weighted imaging (DWI) for grading tumours localized in the fourth ventricle region. Patients were diagnosed histopathologically and classified into two groups: those with high-grade (World Health Organization [WHO] grades III and IV) and those with low-grade tumours (benign, WHO grades I and II). DWI signal intensity was described using a five-point scale. Minimum apparent diffusion coefficient (ADC) values were obtained from areas with the lowest signal. The mean signal intensity was significantly higher in high-grade than in low-grade tumours. The mean minimum ADC value was significantly lower in high-grade than low-grade tumours. Marked hyperintensity had sensitivity, specificity, positive predictive value and negative predictive value of 89.7%, 100%, 100% and 94.2%, respectively, when used as a diagnostic tool for high-grade tumours compared with 96.6%, 97.9%, 96.6% and 97.9%, respectively, when using a minimum ADC of 0.9 × 10−3 mm2/s as a diagnostic marker. It was concluded that DWI is helpful in predicting the grades of tumours in the fourth ventricle region.

Diffusion-weighted magnetic resonance imaging for tumour response assessment: why, when and how?

Diffusion-weighted magnetic resonance imaging (DWI) is increasingly being used to assess tumour response to a variety of anticancer treatments. The technique is quick to perform without the need for administration of exogenous contrast medium, and enables the apparent diffusion coefficient (ADC) of tissues to be quantified. Studies have shown that ADC increases in response to a variety of treatments including chemotherapy, radiotherapy, minimally invasive therapies and novel therapeutics. In this article, we review the rationale of applying DWI for tumour assessment, the evidence for ADC measurements in relation to specific treatments and some of the practical considerations for using ADC to evaluate treatment response.