Integration of Patient Specific MRI Imaging Data Into a Stochastic Low-Grade Glioma Model

Background: To evaluate the diagnostic value of diffusion weighted imaging (DWI) and apparent diffusion coefficient measurement (ADC) in glioma. cient measurement (ADC) in glioma. Methods: Thirty two low-grade glioma patients and 31 high-grade glioma patients who were confirmed by pathology in Lanzhou University Second Hospital, Lanzhou, China from February 2016 to January 2019 were selected. The other 30 patients with brain metastases were selected as a control group. DWI imaging data of the three groups were collected, and ADC, relative ADC (rADC) values in tumor parenchyma, peritumor edema area, and contralateral normal white matter area were measured, and the levels of n-acetyl aspartic acid (NAA), choline (Cho), creatine (Cr) of tumor metabolites were analyzed. Results: rADC values in the peri-tumor edema areas of the high-grade glioma group were significantly lower than those in the low-grade group and the metastatic group （P=0.011）, and the low-grade group was significantly lower than that in the metastatic group (P < 0.05). NAA/Cho and NAA/Cr in parenchymal and peritumor edema areas of patients in the advanced group were significantly lower than those in the metastatic group (P < 0.05), and Cho /Cr was significantly higher than those in the metastatic group (P < 0.05). Conclusion: the rADC value, NAA/Cho, NAA/Cr and Cho/Cr in parenchymal and peritumor edema areas of the tumor can help to distinguish high-grade glioma, low-grade glioma and brain metastases.

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Abstract 235: Integration of Patient-specific Computational Hemodynamics and Vessel Wall Shear Stress Into MRI Diagnosis of Vascular Diseases

Circulation Research ◽

10.1161/res.119.suppl_1.235 ◽

2016 ◽

Vol 119 (suppl_1) ◽

Author(s):

Huidan W Yu ◽

Xi Chen ◽

Zhiqiang Wang ◽

Rou Chen ◽

Chen Lin ◽

...

Keyword(s):

Shear Stress ◽

Wall Shear Stress ◽

Carotid Arteries ◽

Vascular Diseases ◽

Patient Specific ◽

Imaging Data ◽

Mri Imaging ◽

Measured Velocity ◽

Tof Mra ◽

Wall Shear

The research objective is to expand the capability of current MRI imaging technique in assessing the overall risk and predicted outcomes of atherosclerotic diseases through the quantification of individual patient-specific hemodynamics, including flow, pressure, and wall-shear stress. A unique computational modeling technique, named InVascular, is integrated directly into clinical MRI scanners as the extension of the image reconstruction and post-processing pipeline so that velocity, pressure, vorticity, and WSS can be available immediately with other diagnostic images. InVascular is a unified and GPU accelerated computation platform to model and simulate patient-specific hemodynamics and flow-vessel interaction based on MRI imaging data. In this study, we validate the efficiency and accuracy of InVascular through quantitative hemodynamics in vertebral and carotid arteries. A group of five volunteers participated in the scanning of high resolution time-of-flight (TOF) and low resolution electrocardiogram (ECG) gated phase contrast (PC) MR angiogram (MRA) images. For each case, InVascular successively processes the images to get vessel geometry from TOF MRA and velocity slices from PC MRA and solve the fluid dynamics inside the carotid arteries with PC MRA measured velocity at the inlet and outlet (Fig. 1 a-c). The velocity profiles from Invascular and PC MRA are compared at the same location (Fig. 1 d-g ). We conclude that integration of MRAs and InVascular can well captured the velocity fields as MRI measures. InVascular can provide quantitative pressure and WSS (Fig. 1h ) information as well.

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Optimal Combinations of Chemotherapy and Radiotherapy in Low-Grade Gliomas: A Mathematical Approach

Journal of Personalized Medicine ◽

10.3390/jpm11101036 ◽

2021 ◽

Vol 11 (10) ◽

pp. 1036

Author(s):

Luis E. Ayala-Hernández ◽

Armando Gallegos ◽

Philippe Schucht ◽

Michael Murek ◽

Luis Pérez-Romasanta ◽

...

Keyword(s):

Radiation Therapy ◽

In Silico ◽

Treatment Options ◽

Patient Specific ◽

Low Grade ◽

Treatment Schedule ◽

Imaging Data ◽

Low Grade Gliomas ◽

Combination Treatments ◽

Longitudinal Imaging

Low-grade gliomas (LGGs) are brain tumors characterized by their slow growth and infiltrative nature. Treatment options for these tumors are surgery, radiation therapy and chemotherapy. The optimal use of radiation therapy and chemotherapy is still under study. In this paper, we construct a mathematical model of LGG response to combinations of chemotherapy, specifically to the alkylating agent temozolomide and radiation therapy. Patient-specific parameters were obtained from longitudinal imaging data of the response of real LGG patients. Computer simulations showed that concurrent cycles of radiation therapy and temozolomide could provide the best therapeutic efficacy in-silico for the patients included in the study. The patient cohort was extended computationally to a set of 3000 virtual patients. This virtual cohort was subject to an in-silico trial in which matching the doses of radiotherapy to those of temozolomide in the first five days of each cycle improved overall survival over concomitant radio-chemotherapy according to RTOG 0424. Thus, the proposed treatment schedule could be investigated in a clinical setting to improve combination treatments in LGGs with substantial survival benefits.

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