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

2020 ◽  
pp. 197140092098016
Author(s):  
Mustafa Bozdağ ◽  
Ali Er ◽  
Akın Çinkooğlu ◽  
Sümeyye Ekmekçi
Keyword(s):  
Diffusion Coefficient ◽  
Brain Metastases ◽  
Apparent Diffusion Coefficient ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Proliferation Index ◽  
High Grade ◽  
Ki 67 ◽  
Apparent Diffusion ◽  
High Grade Gliomas

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 (ADCmin and ADCmean) and the minimum apparent diffusion coefficient in the peritumoral region (ADCedema) 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 ADCmean, ADCmin 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 ADCmean, ADCmin, 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, ADCmean 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.

scholarly journals Diffusion weighted imaging in high-grade gliomas: A histogram-based analysis of apparent diffusion coefficient profile

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249878
Author(s):  
Georg Gihr ◽  
Diana Horvath-Rizea ◽  
Elena Hekeler ◽  
Oliver Ganslandt ◽  
Hans Henkes ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Standard Deviation ◽  
Apparent Diffusion Coefficient ◽  
Anaplastic Astrocytoma ◽  
Methylation Status ◽  
Proliferation Index ◽  
High Grade ◽  
Ki 67 ◽  
Significant Difference ◽  
Apparent Diffusion

Purpose Glioblastoma and anaplastic astrocytoma represent the most commonly encountered high-grade-glioma (HGG) in adults. Although both neoplasms are very distinct entities in context of epidemiology, clinical course and prognosis, their appearance in conventional magnetic resonance imaging (MRI) is very similar. In search for additional information aiding the distinction of potentially confusable neoplasms, histogram analysis of apparent diffusion coefficient (ADC) maps recently proved to be auxiliary in a number of entities. Therefore, our present exploratory retrospective study investigated whether ADC histogram profile parameters differ significantly between anaplastic astrocytoma and glioblastoma, reflect the proliferation index Ki-67, or are associated with the prognostic relevant MGMT (methylguanine-DNA methyl-transferase) promotor methylation status. Methods Pre-surgical ADC volumes of 56 HGG patients were analyzed by histogram-profiling. Association between extracted histogram parameters and neuropathology including WHO-grade, Ki-67 expression and MGMT promotor methylation status was investigated due to comparative and correlative statistics. Results Grade IV gliomas were more heterogeneous than grade III tumors. More specifically, ADCmin and the lowest percentile ADCp10 were significantly lower, whereas ADCmax, ADC standard deviation and Skewness were significantly higher in the glioblastoma group. ADCmin, ADCmax, ADC standard deviation, Kurtosis and Entropy of ADC histogram were significantly correlated with Ki-67 expression. No significant difference could be revealed by comparison of ADC histogram parameters between MGMT promotor methylated and unmethylated HGG. Conclusions ADC histogram parameters differ significantly between glioblastoma and anaplastic astrocytoma and show distinct associations with the proliferative activity in both HGG. Our results suggest ADC histogram profiling as promising biomarker for differentiation of both, however, further studies with prospective multicenter design are wanted to confirm and further elaborate this hypothesis.

Diagnostic value of apparent diffusion coefficient in differentiating between high-grade gliomas and brain metastases

2017 ◽  
Vol 59 (5) ◽  
pp. 599-605 ◽  
Author(s):  
Ionut Caravan ◽  
Cristiana Augusta Ciortea ◽  
Alexandra Contis ◽  
Andrei Lebovici
Keyword(s):  
Diffusion Coefficient ◽  
Brain Metastases ◽  
Apparent Diffusion Coefficient ◽  
Curve Analysis ◽  
High Grade ◽  
Peritumoral Edema ◽  
Roc Curve Analysis ◽  
Apparent Diffusion ◽  
Adc Values ◽  
The Mean

Background High-grade gliomas (HGGs) and brain metastases (BMs) can display similar imaging characteristics on conventional MRI. In HGGs, the peritumoral edema may be infiltrated by the malignant cells, which was not observed in BMs. Purpose To determine whether the apparent diffusion coefficient values could differentiate HGGs from BMs. Material and Methods Fifty-seven patients underwent conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) before treatment. The minimum and mean ADC in the enhancing tumor (ADCmin, ADCmean) and the minimum ADC in the peritumoral region (ADCedema) were measured from ADC maps. To determine whether there was a statistical difference between groups, ADC values were compared. A receiver operating characteristic (ROC) curve analysis was used to determine the cutoff ADC value for distinguishing between HGGs and BMs. Results The mean ADCmin values in the intratumoral regions of HGGs were significantly higher than those in BMs. No differences were observed between groups regarding ADCmean values. The mean ADCmin values in the peritumoral edema of HGGs were significantly lower than those in BMs. According to ROC curve analysis, a cutoff value of 1.332 × 10−3 mm2/s for the ADCedema generated the best combination of sensitivity (95%) and specificity (84%) for distinguishing between HGGs and BMs. The same value showed a sensitivity of 95.6% and a specificity of 100% for distinguishing between GBMs and BMs. Conclusion ADC values from DWI were found to distinguish between HGGs and solitary BMs. The peritumoral ADC values are better than the intratumoral ADC values in predicting the tumor type.

Differentiation of brain metastases originating from lung and breast cancers using apparent diffusion coefficient histogram analysis and the relation of histogram parameters with Ki-67

2021 ◽  
pp. 197140092110490
Author(s):  
Mustafa Bozdağ ◽  
Ali Er ◽  
Sümeyye Ekmekçi
Keyword(s):  
Lung Cancer ◽  
Diffusion Coefficient ◽  
Brain Metastases ◽  
Apparent Diffusion Coefficient ◽  
Roc Analysis ◽  
Small Cell ◽  
Histogram Analysis ◽  
Small Cell Lung ◽  
Ki 67 ◽  
Apparent Diffusion

Purpose A fast, reliable and non-invasive method is required in differentiating brain metastases (BMs) originating from lung cancer (LC) and breast cancer (BC). The aims of this study were to assess the role of histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating BMs originated from LC and BC, and then to investigate further the association of ADC histogram parameters with Ki-67 index in BMs. Methods A total of 55 patients (LC, N = 40; BC, N = 15) with BMs histopathologically confirmed were enrolled in the study. The LC group was divided into small-cell lung cancer (SCLC; N = 15) and non-small-cell lung cancer (NSCLC; N = 25) groups. ADC histogram parameters (ADCmax, ADCmean, ADCmin, ADCmedian, ADC10, ADC25, ADC75 and ADC90, skewness, kurtosis and entropy) were derived from ADC maps. Mann–Whitney U-test, independent samples t-test, receiver operating characteristic (ROC) analysis and Spearman correlation analysis were used for statistical assessment. Results ADC histogram parameters did not show significant differences between LC and BC groups ( p > 0.05). Subgroup analysis showed that various ADC histogram parameters were found to be statistically lower in the SCLC group compared to the NSCLC and BC groups ( p < 0.05). ROC analysis showed that ADCmean and ADC10 for differentiating SCLC BMs from NSCLC, and ADC25 for differentiating SCLC BMs from BC achieved optimal diagnostic performances. Various histogram parameters were found to be significantly correlated with Ki-67 ( p < 0.05). Conclusion Histogram analysis of ADC maps may reflect tumoural proliferation potential in BMs and can be useful in differentiating SCLC BMs from NSCLC and BC BMs.

Is the standard deviation of the apparent diffusion coefficient a potential tool for the preoperative prediction of tumor grade in endometrial cancer?

2020 ◽  
Vol 61 (12) ◽  
pp. 1724-1732
Author(s):  
Bin Yan ◽  
Xiufen Liang ◽  
Tingting Zhao ◽  
Caixia Ding ◽  
Ming Zhang
Keyword(s):  
Diffusion Coefficient ◽  
Endometrial Cancer ◽  
Standard Deviation ◽  
Apparent Diffusion Coefficient ◽  
Tumor Grade ◽  
Low Grade ◽  
High Grade ◽  
Ki 67 ◽  
Preoperative Prediction ◽  
Apparent Diffusion

Background The tumor histological grade is closely related to the prognosis of endometrial cancer (EC). The use of the apparent diffusion coefficient (ADC), tumor volume, and MRI-based texture analysis has allowed exciting advances in predicting EC grade before surgery. However, whether this constitutes a simple, convenient, and powerful diagnostic method remains unknown. Purpose To explore the utility of standard deviation (SD) of the ADC (ADCSD) for predicting the tumor grade in patients with EC. Material and Methods We retrospectively evaluated 138 patients with EC. All patients underwent unenhanced MRI and diffusion-weighted imaging (DWI). The mean ADC value (ADCmean) and SD were obtained using a freehand region of interest traced on the ADC map. Spearman’s linear correlation coefficients were calculated to analyze the correlations between the indexes (including ADCSD and the ADCmean) and the Ki-67 index. The Kruskal–Wallis and Mann–Whitney U tests were used to compare differences in the index results among tumor grades. Results A significant difference in ADCSD was observed among the tumor grades ( P=0.000), and the ADCSD value was significantly higher for high-grade EC than for low-grade tumors (289.7 vs. 216.3×10−6mm2 /s, P=0.000). A statistically significant positive correlation was observed between ADCSD and the Ki-67 index (r=0.364, P=0.000). According to the receiver operating characteristic curve, ADCSD ≥240.2×10−6mm2 /s predicted high-grade EC with a sensitivity, specificity, and accuracy of 73.1%, 80.2%, and 77.5%, respectively. Conclusion Based on the intratumor heterogeneity of EC, ADCSD represents a potential method for the preoperative prediction of high-grade EC, although further studies are needed.

scholarly journals The Relationship Between The Apparent Diffusion Coefficient and The Ki-67 Proliferation Index in Intracranial Solitary Fibrous Tumor/Hemangiopericytoma

2021 ◽  
Author(s):  
Shenglin Li ◽  
Qing Zhou ◽  
Peng Zhang ◽  
Shize Ma ◽  
Caiqiang Xue ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Solitary Fibrous Tumor ◽  
Proliferation Index ◽  
Ki 67 ◽  
Solitary Fibrous Tumors ◽  
Average Maximum ◽  
Apparent Diffusion ◽  
Grade Ii ◽  
Fibrous Tumor

Abstract Objiective: This study evaluated the value of the apparent diffusion coefficient (ADC) in distinguishing grade II and III intracranial solitary fibrous tumors /hemangiopericytomas and explored the correlation between ADC and Ki-67. Methods The preoperative MRIs of 37 patients treated for solitary fibrous tumor/hemangiopericytoma (grade II, n = 15 and grade III, n = 22) in our hospital from 2011 to October 2020 were retrospectively analyzed. We compared the difference between the minimum, average, maximum, and relative ADCs based on tumor grade and examined the correlation between ADC and Ki-67. Receiver operating characteristic curve analysis was used to analyze the diagnostic efficiency of the ADC. Results There were significant differences in the average, minimum, and relative ADCs between grade II and III patients. The optimal cutoff value for the relative ADC value to differentiate grade II and III tumors was 0.998, which yielded an area under the curve of 0.879. The Ki-67 proliferation indexes of grade II and III tumors were significantly different, and the average (r = -0.427), minimum (r = -0.356), and relative (r = -0.529) ADCs were significantly negatively correlated with the Ki-67 proliferation index. Conclusions ADC can be used to differentiate grade II and III intracranial solitary fibrous tumors/hemangiopericytomas. Our results can be used to formulate a personalized surgical treatment plan before surgery.

Diffusion-weighted MRI combined with susceptibility-weighted MRI: added diagnostic value for four common lateral ventricular tumors

2017 ◽  
Vol 59 (8) ◽  
pp. 980-987 ◽  
Author(s):  
Yuanlin Yu ◽  
Hua Zhang ◽  
Zebin Xiao ◽  
Dejun She ◽  
Zhen Xing ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Diagnostic Performance ◽  
The Other ◽  
High Grade ◽  
Diffusion Weighted ◽  
Significant Difference ◽  
Apparent Diffusion ◽  
Ventricular Tumors ◽  
High Grade Gliomas

Background Diffusion-weighted imaging (DWI) and susceptibility-weighted imaging (SWI) are reliable imaging modalities for brain tumors. However, the role of DWI and SWI in the diagnosis of common lateral ventricular tumors has not been systematically evaluated. Purpose To evaluate the diagnostic performance of DWI and SWI in common lateral ventricular tumors. Material and Methods Fifty-two patients with histopathologically confirmed lateral ventricular tumors were included in this study (18 with central neurocytomas, nine with ependymomas, seven with high-grade gliomas, and 18 with meningiomas). The relative minimum apparent diffusion coefficient (rADCmin) and relative average apparent diffusion coefficient (rADCave) measured by DWI and the intratumoral susceptibility signal intensity (ITSS) of hemorrhage acquired by SWI were calculated. These quantitative parameters were evaluated using the Mann–Whitney U test, receiver operating characteristic curve, and logistic regression analyses. Results The rADCmin and rADCave ratios of central neurocytomas were significantly lower than those of the other neoplasms. The rADCmin and rADCave ratios of ependymomas and the rADCave ratio of high-grade gliomas were significantly higher than those of meningiomas. The ITSS score of meningiomas was significantly lower than those of the other tumors, while the score of central neurocytomas was obviously lower than those of ependymomas and high-grade gliomas. The combination of the rADC ratio with the ITSS showed no significant difference, except in discriminating between meningiomas and high-grade glioma-ependymomas. Conclusion The rADC ratios and ITSS may be useful for differentiating common lateral ventricular tumors. The diagnostic performance may be improved with the use of the rADC ratios and ITSS scores.

Correlation of Apparent Diffusion Coefficient With Ki-67 Proliferation Index in Grading Meningioma

2014 ◽  
Vol 202 (6) ◽  
pp. 1303-1308 ◽  
Author(s):  
Yi Tang ◽  
Sathish K. Dundamadappa ◽  
Senthur Thangasamy ◽  
Thomas Flood ◽  
Richard Moser ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Proliferation Index ◽  
Ki 67 ◽  
Apparent Diffusion
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