Apparent Diffusion Coefficient Histogram Analysis for the Preoperative Evaluation of Ki-67 Expression in Pituitary Macroadenoma

2022 ◽  
Author(s):  
Caiqiang Xue ◽  
Suwei Liu ◽  
Juan Deng ◽  
Xianwang Liu ◽  
Shenglin Li ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Preoperative Evaluation ◽  
Histogram Analysis ◽  
Pituitary Macroadenoma ◽  
Ki 67 ◽  
Apparent Diffusion

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.

scholarly journals The Benefit of Apparent Diffusion Coefficient in Evaluating the Invasiveness of Hepatocellular Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Mengyuan Jing ◽  
Yuntai Cao ◽  
Peng Zhang ◽  
Bin Zhang ◽  
Xiaoqiang Lin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Tumor Size ◽  
Preoperative Evaluation ◽  
Tumor Differentiation ◽  
Ki 67 ◽  
Adc Value ◽  
Apparent Diffusion ◽  
Auc Value

BackgroundThis study aimed to evaluate hepatocellular carcinoma (HCC) invasiveness using the apparent diffusion coefficient (ADC).MethodsEighty-one patients with HCC confirmed by pathology and examined by preoperative magnetic resonance imaging diffusion-weighted imaging from January 2015 to September 2020 were retrospectively analyzed. Clinical and pathological data were recorded. The minimum ADC (ADCmin), average ADC (ADCmean), and the ratio of ADCmean to normal-appearing hepatic parenchyma ADC (ADCnahp) were assessed. The associations between clinical information, ADC value, and HCC invasiveness (microvascular invasion [MVI], tumor differentiation, and Ki-67 expression) were evaluated statistically. Independent risk factors related to HCC invasiveness were screened using binary logistic regression, and the diagnostic efficiency was evaluated by the receiver operating characteristic curve and its area under the curve (AUC) value.ResultsTumor size was related to HCC MVI and tumor differentiation (P &lt; 0.05). HCC MVI was associated with ADCmin, ADCmean, and the ADCmean-to-ADCnahp ratio (all P &lt; 0.05) with AUC values of 0.860, 0.860, and 0.909, respectively. If these were combined with tumor size, the AUC value increased to 0.912. The degree of tumor differentiation was associated with ADCmin, ADCmean, and the ADCmean-to-ADCnahp ratio (all P &lt; 0.05) with AUC values of 0.719, 0.708, and 0.797, respectively. If these were combined with tumor size, the AUC value increased to 0.868. Ki-67 expression was associated with ADCmin, ADCmean, and the ADCmean-to-ADCnahp ratio (all P &lt; 0.05) with AUC values of 0.731, 0.747, and 0.746, respectively. Combined them, the AUC value increased to 0.763.ConclusionsThe findings indicated that the ADC value has significant potential for the non-invasive preoperative evaluation of HCC invasiveness.

Can whole-tumor apparent diffusion coefficient histogram analysis be helpful to evaluate breast phyllode tumor grades?

2019 ◽  
Vol 114 ◽  
pp. 25-31
Author(s):  
Yuan Guo ◽  
Wen-Jie Tang ◽  
Qing-cong Kong ◽  
Ying-ying Liang ◽  
Xiao-rui Han ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Phyllode Tumor ◽  
Histogram Analysis ◽  
Apparent Diffusion

scholarly journals Volumetric voxelwise apparent diffusion coefficient histogram analysis for differentiation of the fourth ventricular tumors

2018 ◽  
Vol 31 (6) ◽  
pp. 554-564 ◽  
Author(s):  
Seyedmehdi Payabvash ◽  
Tarik Tihan ◽  
Soonmee Cha
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Predictive Value ◽  
Fourth Ventricle ◽  
Histogram Analysis ◽  
Mri Findings ◽  
Patient Age ◽  
Patient Âgé ◽  
Pilocytic Astrocytomas ◽  
Apparent Diffusion

Purpose We applied voxelwise apparent diffusion coefficient (ADC) histogram analysis in addition to structural magnetic resonance imaging (MRI) findings and patients’ age for differentiation of intraaxial posterior fossa tumors involving the fourth ventricle. Participants and methods Pretreatment MRIs of 74 patients with intraaxial brain neoplasm involving the fourth ventricle, from January 1, 2004 to December 31, 2015, were reviewed. The tumor solid components were segmented and voxelwise ADC histogram variables were determined. Histogram-driven variables, structural MRI findings, and patient age were combined to devise a differential diagnosis algorithm. Results The most common neoplasms were ependymomas ( n = 21), medulloblastoma ( n = 17), and pilocytic astrocytomas ( n = 13). Medulloblastomas followed by atypical teratoid/rhabdoid tumors had the lowest ADC histogram percentile values; whereas pilocytic astrocytomas and choroid plexus papillomas had the highest ADC histogram percentile values. In a multivariable multinominal regression analysis, the ADC 10th percentile value from voxelwise histogram was the only independent predictor of tumor type ( p < 0.001). In separate binary logistic regression analyses, the 10th percentile ADC value, tumor morphology, enhancement pattern, extension into Luschka/Magendie foramina, and patient age were predictors of different tumor types. Combining these variables, we devised a stepwise diagnostic model yielding 71% to 82% sensitivity, 91% to 95% specificity, 75% to 78% positive predictive value, and 89% to 95% negative predictive value for differentiation of ependymoma, medulloblastoma, and pilocytic astrocytoma. Conclusion We have shown how the addition of quantitative voxelwise ADC histogram analysis of the tumor solid component to structural findings and patient age can help with accurate differentiation of intraaxial posterior fossa neoplasms involving the fourth ventricle based on pretreatment MRI.

Whole-tumor apparent diffusion coefficient (ADC) histogram analysis to differentiate benign peripheral neurogenic tumors from soft tissue sarcomas

2018 ◽  
Vol 48 (3) ◽  
pp. 680-686 ◽  
Author(s):  
Masanori Nakajo ◽  
Yoshihiko Fukukura ◽  
Hiroto Hakamada ◽  
Tomohide Yoneyama ◽  
Kiyohisa Kamimura ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Soft Tissue ◽  
Apparent Diffusion Coefficient ◽  
Soft Tissue Sarcomas ◽  
Histogram Analysis ◽  
Neurogenic Tumors ◽  
Apparent Diffusion

Value of whole-liver apparent diffusion coefficient histogram analysis for quantification of liver fibrosis stages

2019 ◽  
Vol 1 (1) ◽  
pp. 6-12
Author(s):  
Zhao-xia Yang ◽  
Xin-Xing Hu ◽  
Robert Grimm ◽  
Cai-xia Fu ◽  
Xu Yan ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Liver Fibrosis ◽  
Apparent Diffusion Coefficient ◽  
Histogram Analysis ◽  
Apparent Diffusion
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