scholarly journals Relation of apparent diffusion coefficient with Ki-67 proliferation index in meningiomas

2016 ◽  
Vol 89 (1057) ◽  
pp. 20140842 ◽  
Author(s):  
Ozdil Baskan ◽  
Gokalp Silav ◽  
Fatih Han Bolukbasi ◽  
Ozlem Canoz ◽  
Serdar Geyik ◽  
...  
2021 ◽  
Author(s):  
Shenglin Li ◽  
Qing Zhou ◽  
Peng Zhang ◽  
Shize Ma ◽  
Caiqiang Xue ◽  
...  

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.


2014 ◽  
Vol 202 (6) ◽  
pp. 1303-1308 ◽  
Author(s):  
Yi Tang ◽  
Sathish K. Dundamadappa ◽  
Senthur Thangasamy ◽  
Thomas Flood ◽  
Richard Moser ◽  
...  

2020 ◽  
pp. 197140092098016
Author(s):  
Mustafa Bozdağ ◽  
Ali Er ◽  
Akın Çinkooğlu ◽  
Sümeyye Ekmekçi

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.


2020 ◽  
Vol 71 (1) ◽  
pp. 5-11 ◽  
Author(s):  
Weiqun Ao ◽  
Xiangdong Bao ◽  
Guoqun Mao ◽  
Guangzhao Yang ◽  
Jian Wang ◽  
...  

Purpose: To explore the value of the apparent diffusion coefficient (ADC) in assessing preoperative T staging of low rectal cancer and the correlation between ADC value and Ki-67 expression. Methods: Data on 77 patients with a proven pathology of low rectal cancer were retrospectively analyzed. All patients underwent a magnetic resonance imaging scan 1 week prior to operation, and the mean ADC value was measured. All tumors were fully removed, and pathologic staging was determined. The Ki-67 expression was determined using immunohistochemical methods in all patients. The correlation between Ki-67 expression and ADC features was studied. Results: A total of 77 patients with low rectal cancer were included in the study. The pathology type was adenocarcinoma. The numbers of patients with pathological stages T1, T2, T3, and T4 were 9, 23, 32, and 13, respectively. The ADC value of all tumors ranged from 0.60 to 1.20 mm2/s. The average Ki-67 proliferation index was 55.3% ± 20.2%. A significant difference was observed between the preoperative ADC value and pathological T staging of low rectal cancer ( P < .01). The more advanced the T stage, the lower the detected ADC values were. A negative correlation was noted between the preoperative ADC value and Ki-67 proliferation index of rectal cancer ( r = −0.71, P < .01). When the Ki-67 proliferation index increased, lower ADC values were detected. Conclusion: The ADC values can provide useful information on preoperative tumor staging and may facilitate evaluation of the biological behavior of low rectal cancer. The ADC values should be considered a sensitive image biomarker of rectal cancer.


2020 ◽  
Vol 13 (12) ◽  
Author(s):  
Nguyen Duy Hung ◽  
Nguyen Minh Duc ◽  
Ta Hong Nhung ◽  
Le Thanh Dung ◽  
Bui Van Giang ◽  
...  

Background: Central nervous system (CNS) lymphoma presents as the dense infiltration of tumor cells in the perivascular space and blood-brain barrier disruption, on histopathological examination. The Ki-67 expression has been significantly correlated with tumor proliferation and is considered to be a prognostic factor. Objectives: This study aimed at analyzing the correlations among the apparent diffusion coefficient (ADC), the relative cerebral blood volume (rCBV), and the Ki-67 proliferation index in CNS lymphoma. Methods: From August 2019 to March 2020, 26 patients (14 men and 12 women) who underwent biopsy or surgery and were histologically confirmed as CNS lymphoma were included in this retrospective study. Diffusion and perfusion acquisitions were performed in 26 and 10 examinations, respectively. The Ki-67 proliferation index was available for all cases. Results: The mean tADC, rADC, and rCBV values were 0.61 ± 0.12 × 10-3 mm2/s, 0.73 ± 0.14, and 1.1 ± 0.32, respectively. Negative correlations were identified between both tADC and rADC and the Ki-67 proliferation index (r = -0.656, P < 0.01 and r = -0.540, P < 0.01, respectively). No significant correlations were found between rCBV values and the Ki-67 proliferation index, between rCBV and rADC, or between rCBV and tADC. Conclusions: tADC and rADC values can be used as noninvasive indicators to predict cell proliferation in CNS lymphoma.


PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249878
Author(s):  
Georg Gihr ◽  
Diana Horvath-Rizea ◽  
Elena Hekeler ◽  
Oliver Ganslandt ◽  
Hans Henkes ◽  
...  

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.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yuan Guo ◽  
Qing-cong Kong ◽  
Li-qi Li ◽  
Wen-jie Tang ◽  
Wan-li Zhang ◽  
...  

Objectives. To evaluate the value of the whole volume apparent diffusion coefficient (ADC) histogram in distinguishing between benign and malignant breast lesions and differentiating different molecular subtypes of breast cancers and to assess the correlation between ADC histogram parameters and Ki-67 expression in breast cancers. Methods. The institutional review board approved this retrospective study. Between September 2016 and February 2019, 189 patients with 84 benign lesions and 105 breast cancers underwent magnetic resonance imaging (MRI). Volumetric ADC histograms were created by placing regions of interest (ROIs) on the whole lesion. The relationships between the ADC parameters and Ki-67 were analysed using Spearman’s correlation analysis. Results. Of the 189 breast lesions included, there were significant differences in patient age ( P < 0.001 ) and lesion size ( P = 0.006 ) between the benign and malignant lesions. The results also demonstrated significant differences in all ADC histogram parameters between benign and malignant lesions (all P < 0.001 ). The median and mean ADC histogram parameters performed better than the other ADC histogram parameters (AUCs were 0.943 and 0.930, respectively). The receiver operating characteristic (ROC) analysis revealed that the 10th percentile ADC value and entropy could determine the human epidermal growth factor receptor 2 (HER-2) status (both P = 0.001 ) and estrogen receptor (ER)/progesterone receptor (PR) status ( P = 0.020 and P = 0.041 , respectively). Among all breast cancer lesions, 35 tumours in the low-proliferation group ( Ki − 67 < 14 % ) and 70 tumours in the high-proliferation group ( Ki − 67 ≥ 14 ) were analysed with ROC curves and correlation analyses. The ROC analysis revealed that entropy and skewness could determine the Ki-67 status ( P = 0.007 and P < 0.001 , respectively), and there were weak correlations between ADC entropy ( r = 0.383 ) and skewness ( r = 0.209 ) and the Ki-67 index. Conclusion. The volumetric ADC histogram could serve as an imaging marker to determine breast lesion characteristics and may be a supplemental method in predicting tumour proliferation in breast cancer.


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