Preoperative vascular heterogeneity and aggressiveness assessment of pituitary macroadenoma based on dynamic contrast-enhanced MRI texture analysis

Liu, YangYing Qiu; Gao, Bing; Dong, Bin; Cheriyath, Shesnia Salim Padikkalakandy; Song, Qing Wei; Xu, Bingying; Wei, Qiang; Xie, Lizhi; Guo, Yan; Yan, Miao

doi:10.1016/j.ejrad.2020.109125

Cited by 16 publications

(14 citation statements)

References 31 publications

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“…Thus, in order to discover more information about the relationship between AEF texture features and tumor response of HCC to TACE, we implemented a multi-variate logistic regression in which all the AEF textures were initially enrolled. However, consistent with other studies [ 34 , 47 , 48 ], it was necessary to apply some specific selection strategies to exclude redundant textures, in order to avoid exaggerating the importance of specific textures that had an interacting influence due to overlapping effect. In our research, two AEF based multi-texture models for predicting “Improved” and “Un-worsened” outcomes were successfully built, in which the IBS features, IBH features, GLCM features, and GLRLM features were all covered.…”

Section: Discussionmentioning

confidence: 71%

“…The novelty of the present study lies in a new methodology where texture analysis is conducted upon perfusion parameters, forming a combination of two sorts of functional imaging applications. Similar methodology was introduced in Liu’s study [ 47 ], but it was concerned with brain tumor (Pituitary macroadenoma). Kloth et al [ 67 ] revealed the value of specific enhanced CT textures in predicting tumor response of HCC to DEB-TACE (Drug eluting beads TACE), where the perfusion parameters were applied, however, only to assess the tumor response, which means no perfusion texture features were extracted.…”

Section: Discussionmentioning

confidence: 99%

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Applying arterial enhancement fraction (AEF) texture features to predict the tumor response in hepatocellular carcinoma (HCC) treated with Transarterial chemoembolization (TACE)

et al. 2021

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Background To evaluate the application of Arterial Enhancement Fraction (AEF) texture features in predicting the tumor response in Hepatocellular Carcinoma (HCC) treated with Transarterial Chemoembolization (TACE) by means of texture analysis. Methods HCC patients treated with TACE in Shengjing Hospital of China Medical University from June 2018 to December 2019 were retrospectively enrolled in this study. Pre-TACE Contrast Enhanced Computed Tomography (CECT) and imaging follow-up within 6 months were both acquired. The tumor responses were categorized according to the modified RECIST (mRECIST) criteria. Based on the CECT images, Region of Interest (ROI) of HCC lesion was drawn, the AEF calculation and texture analysis upon AEF values in the ROI were performed using CT-Kinetics (C.K., GE Healthcare, China). A total of 32 AEF texture features were extracted and compared between different tumor response groups. Multi-variate logistic regression was performed using certain AEF features to build the differential models to predict the tumor response. The Receiver Operator Characteristic (ROC) analysis was implemented to assess the discriminative performance of these models. Results Forty-five patients were finally enrolled in the study. Eight AEF texture features showed significant distinction between Improved and Un-improved patients (p < 0.05). In multi-variate logistic regression, 9 AEF texture features were applied into modeling to predict “Improved” outcome, and 4 AEF texture features were applied into modeling to predict “Un-worsened” outcome. The Area Under Curve (AUC), diagnostic accuracy, sensitivity, and specificity of the two models were 0.941, 0.911, 1.000, 0.826, and 0.824, 0.711, 0.581, 1.000, respectively. Conclusions Certain AEF heterogeneous features of HCC could possibly be utilized to predict the tumor response to TACE treatment.

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Section: Discussionmentioning

confidence: 71%

Section: Discussionmentioning

confidence: 99%

Applying arterial enhancement fraction (AEF) texture features to predict the tumor response in hepatocellular carcinoma (HCC) treated with Transarterial chemoembolization (TACE)

et al. 2021

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“…Despite the routine implementation of DCE-MRI as a preoperative MRI protocol for pituitary adenoma, quantitative pharmacokinetic analysis of pituitary DCE-MRI has rarely been reported. Zhai et al [20] and Liu et al [36] performed pharmacokinetic analysis of pituitary DCE-MRI using T1-weighted gradient-echo pulse sequences with temporal resolutions of 8 to 8.5 s and an in-plane resolution of <1 mm 2 but comparatively thicker slices ranging from 2.5 to 3 mm. In this study, we employed the compressed sensing incorporated in a 3D gradient-echo sequence to enable both higher temporal resolution (5 s) and submillimeter isotropic voxels (0.9 × 0.9 × 0.9 mm 3 ) [37].…”

Section: Discussionmentioning

confidence: 99%

Consistency of Pituitary Adenoma: Prediction by Pharmacokinetic Dynamic Contrast-Enhanced MRI and Comparison with Histologic Collagen Content

Kamimura

Nakajo

Bohara

et al. 2021

Cancers

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Prediction of tumor consistency is valuable for planning transsphenoidal surgery for pituitary adenoma. A prospective study was conducted involving 49 participants with pituitary adenoma to determine whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of adenomas. Pharmacokinetic parameters in the adenomas including volume of extravascular extracellular space (EES) per unit volume of tissue (ve), blood plasma volume per unit volume of tissue (vp), volume transfer constant between blood plasma and EES (Ktrans), and rate constant between EES and blood plasma (kep) were obtained. The pharmacokinetic parameters and the histologic percentage of collagen content (PCC) were compared between soft and hard adenomas using Mann–Whitney U test. Pearson’s correlation coefficient was used to correlate pharmacokinetic parameters with PCC. Hard adenomas showed significantly higher PCC (44.08 ± 15.14% vs. 6.62 ± 3.47%, p < 0.01), ve (0.332 ± 0.124% vs. 0.221 ± 0.104%, p < 0.01), and Ktrans (0.775 ± 0.401/min vs. 0.601 ± 0.612/min, p = 0.02) than soft adenomas. Moreover, a significant positive correlation was found between ve and PCC (r = 0.601, p < 0.01). The ve derived using DCE-MRI may have predictive value for consistency of pituitary adenoma.

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“…Despite the routine implementation of DCE-MRI as a preoperative MRI protocol for pituitary adenoma, quantitative pharmacokinetic analysis of pituitary DCE-MRI has rarely been reported. Zhai et al [20] and Liu et al [29] performed pharmacokinetic analysis of pituitary DCE-MRI using T1-weighted gradient-echo pulse sequences with temporal resolutions of 8 to 8.5 s and an in-plane resolution of < 1 mm 2 but comparatively thicker slices ranging from 2.5 to 3 mm. In this study, we employed the compressed sensing incorporated in a 3D gradient-echo sequence to enable both higher temporal resolution (5 s) and submillimeter isotropic voxels (0.9 × 0.9 × 0.9 mm 3 ) [30].…”

Section: Discussionmentioning

confidence: 99%

Consistency of Pituitary Adenoma: Prediction by Pharmacokinetic Dynamic Contrast-enhanced MRI and Comparison with Histologic Collagen Content

Kamimura

Nakajo

Bohara

et al. 2021

Preprint

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Prediction of tumor consistency is valuable for planning transsphenoidal surgery for pituitary adenoma. A prospective study was conducted involving 49 participants with pituitary adenoma to determine whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of adenoma. Pharmacokinetic parameters in the adenomas including volume of extravascular extracellular space (EES) per unit volume of tissue (ve), blood plasma volume per unit volume of tissue (vp), volume transfer constant between blood plasma and EES (Ktrans), and rate constant between EES and blood plasma (kep) were obtained. The pharmacokinetic parameters and the histologic percentage of collagen content (PCC) were compared between soft and hard adenomas using Mann–Whitney U test. Pearson’s correla-tion coefficient was used to correlate pharmacokinetic parameters with PCC. Hard adenomas showed significantly higher PCC (44.08 ± 15.14% vs. 6.62 ± 3.47%, p < 0.01), ve (0.332 ± 0.124% vs. 0.221 ± 0.104%, p = 0.02), and Ktrans (0.775 ± 0.401/min vs. 0.601 ± 0.612/min, p = 0.02) than soft adenomas. Moreover, a significant positive correlation was found between ve and PCC (r = 0.601, p < 0.01). The ve derived using DCE-MRI may have predictive value for consistency of pituitary adenoma.

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Preoperative vascular heterogeneity and aggressiveness assessment of pituitary macroadenoma based on dynamic contrast-enhanced MRI texture analysis

Cited by 16 publications

References 31 publications

Applying arterial enhancement fraction (AEF) texture features to predict the tumor response in hepatocellular carcinoma (HCC) treated with Transarterial chemoembolization (TACE)

Applying arterial enhancement fraction (AEF) texture features to predict the tumor response in hepatocellular carcinoma (HCC) treated with Transarterial chemoembolization (TACE)

Consistency of Pituitary Adenoma: Prediction by Pharmacokinetic Dynamic Contrast-Enhanced MRI and Comparison with Histologic Collagen Content

Consistency of Pituitary Adenoma: Prediction by Pharmacokinetic Dynamic Contrast-enhanced MRI and Comparison with Histologic Collagen Content

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