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  • 1
    Online Resource
    Online Resource
    Modeling interaction of Glioma cells and CAR T-cells considering multiple CAR T-cells bindings
    Elsevier BV ; 2023
    In:  ImmunoInformatics Vol. 9 ( 2023-03), p. 100022-
    Details
    In: ImmunoInformatics, Elsevier BV, Vol. 9 ( 2023-03), p. 100022-
    Type of Medium: Online Resource
    ISSN: 2667-1190
    URL: Article
    DOI: 10.1016/j.immuno.2023.100022
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
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  • 2
    Online Resource
    Online Resource
    Aging in a Relativistic Biological Space-Time
    Frontiers Media SA ; 2018
    In:  Frontiers in Cell and Developmental Biology Vol. 6 ( 2018-5-29)
    Details
    In: Frontiers in Cell and Developmental Biology, Frontiers Media SA, Vol. 6 ( 2018-5-29)
    Type of Medium: Online Resource
    ISSN: 2296-634X
    URL: Article
    DOI: 10.3389/fcell.2018.00055
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2018
    detail.hit.zdb_id: 2737824-X
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  • 3
    Online Resource
    Online Resource
    Early Changes in Tumor Perfusion from T1-Weighted Dynamic Contrast-Enhanced MRI following Neural Stem Cell-Mediated Therapy of Recurrent High-Grade Glioma Correlate with Overall Survival
    Hindawi Limited ; 2018
    In:  Stem Cells International Vol. 2018 ( 2018), p. 1-9
    Details
    In: Stem Cells International, Hindawi Limited, Vol. 2018 ( 2018), p. 1-9
    Abstract: Background . The aim of this study was to correlate T1-weighted dynamic contrast-enhanced MRI- (DCE-MRI-) derived perfusion parameters with overall survival of recurrent high-grade glioma patients who received neural stem cell- (NSC-) mediated enzyme/prodrug gene therapy. Methods . A total of 12 patients were included in this retrospective study. All patients were enrolled in a first-in-human study (NCT01172964) of NSC-mediated therapy for recurrent high-grade glioma. DCE-MRI data from all patients were collected and analyzed at three time points: MRI#1—day 1 postsurgery/treatment, MRI#2— day 7 ± 3 posttreatment, and MRI#3—one-month follow-up. Plasma volume ( V p ), permeability ( K t r ), and leakage ( λ t r ) perfusion parameters were calculated by fitting a pharmacokinetic model to the DCE-MRI data. The contrast-enhancing (CE) volume was measured from the last dynamic phase acquired in the DCE sequence. Perfusion parameters and CE at each MRI time point were recorded along with their relative change between MRI#2 and MRI#3 (Δ 32 ). Cox regression was used to analyze patient survival. Results . At MRI#1 and at MRI#3, none of the parameters showed a significant correlation with overall survival (OS). However, at MRI#2, CE and λ t r were significantly associated with OS ( p 〈 0.05 ). The relative λ t r and V p from timepoint 2 to timepoint 3 (Δ 32 λ t r and Δ 32 V p ) were each associated with a higher hazard ratio ( p 〈 0.05 ). All parameters were highly correlated, resulting in a multivariate model for OS including only CE at MRI#2 and Δ 32 V p , with an R 2 of 0.89. Conclusion . The change in perfusion parameter values from 1 week to 1 month following NSC-mediated therapy combined with contrast-enhancing volume may be a useful biomarker to predict overall survival in patients with recurrent high-grade glioma.
    Type of Medium: Online Resource
    ISSN: 1687-966X , 1687-9678
    URL: Article
    DOI: 10.1155/2018/5312426
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2018
    detail.hit.zdb_id: 2573856-2
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  • 4
    Online Resource
    Online Resource
    Synthetic Apparent Diffusion Coefficient for High b -Value Diffusion-Weighted MRI in Prostate
    Hindawi Limited ; 2020
    In:  Prostate Cancer Vol. 2020 ( 2020-02-10), p. 1-7
    Details
    In: Prostate Cancer, Hindawi Limited, Vol. 2020 ( 2020-02-10), p. 1-7
    Abstract: Purpose . It has been reported that diffusion-weighted imaging (DWI) with ultrahigh b -value increases the diagnostic power of prostate cancer. DWI with higher b -values is challenging as it commonly suffers from low signal-to-noise ratio (SNR), distortion, and longer scan time. The aim of our study was to develop a technique for quantification of apparent diffusion coefficient (ADC) for higher b -values from lower b -value DW images. Materials and Methods . Fifteen patients (7 malignant and 8 benign) were included in this study retrospectively with the institutional ethical committee approval. All images were acquired at a 3T MR scanner. The ADC values were calculated using a monoexponential model. Synthetic ADC (sADC) for higher b -value was computed using a log-linear model. Contrast ratio (CR) between prostate lesion and normal tissue on synthetic DWI (sDWI) was computed and compared with original DWI and ADC images. Results . No significant difference was observed between actual ADC and sADC for b -2000 in all prostate lesions. However, CR increased significantly ( p = 0.002 , paired t -test) in sDWI as compared to DWI. Malignant lesions showed significantly lower sADC as compared to benign lesions ( p = 0.0116 , independent t -test). Mean (±standard deviation) of sADC of malignant lesions was 0.601 ± 0.06 and for benign lesions was 0.92 ± 0.09 (10 −3  mm 2 /s). Discussion / Conclusion . Our initial investigation suggests that the ADC values corresponding to higher b -value can be computed using log-linear relationship derived from lower b -values ( b  ≤ 1000). Our method might help clinicians to decide the optimal b -value for prostate lesion identification.
    Type of Medium: Online Resource
    ISSN: 2090-3111 , 2090-312X
    URL: Article
    DOI: 10.1155/2020/5091218
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2020
    detail.hit.zdb_id: 2627965-4
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  • 5
    Online Resource
    Online Resource
    Towards integration of 64Cu-DOTA-trastuzumab PET-CT and MRI with mathematical modeling to predict response to neoadjuvant therapy in HER2 + breast cancer
    Springer Science and Business Media LLC ; 2020
    In:  Scientific Reports Vol. 10, No. 1 ( 2020-11-25)
    Details
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 10, No. 1 ( 2020-11-25)
    Abstract: While targeted therapies exist for human epidermal growth factor receptor 2 positive (HER2 +) breast cancer, HER2 + patients do not always respond to therapy. We present the results of utilizing a biophysical mathematical model to predict tumor response for two HER2 + breast cancer patients treated with the same therapeutic regimen but who achieved different treatment outcomes. Quantitative data from magnetic resonance imaging (MRI) and 64 Cu-DOTA-trastuzumab positron emission tomography (PET) are used to estimate tumor density, perfusion, and distribution of HER2-targeted antibodies for each individual patient. MRI and PET data are collected prior to therapy, and follow-up MRI scans are acquired at a midpoint in therapy. Given these data types, we align the data sets to a common image space to enable model calibration. Once the model is parameterized with these data, we forecast treatment response with and without HER2-targeted therapy. By incorporating targeted therapy into the model, the resulting predictions are able to distinguish between the two different patient responses, increasing the difference in tumor volume change between the two patients by  〉  40%. This work provides a proof-of-concept strategy for processing and integrating PET and MRI modalities into a predictive, clinical-mathematical framework to provide patient-specific predictions of HER2 + treatment response.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    URL: Article
    DOI: 10.1038/s41598-020-77397-0
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2615211-3
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  • 6
    Online Resource
    Online Resource
    Mathematical deconvolution of CAR T-cell proliferation and exhaustion from real-time killing assay data
    The Royal Society ; 2020
    In:  Journal of The Royal Society Interface Vol. 17, No. 162 ( 2020-01), p. 20190734-
    Details
    In: Journal of The Royal Society Interface, The Royal Society, Vol. 17, No. 162 ( 2020-01), p. 20190734-
    Abstract: Chimeric antigen receptor (CAR) T-cell therapy has shown promise in the treatment of haematological cancers and is currently being investigated for solid tumours, including high-grade glioma brain tumours. There is a desperate need to quantitatively study the factors that contribute to the efficacy of CAR T-cell therapy in solid tumours. In this work, we use a mathematical model of predator–prey dynamics to explore the kinetics of CAR T-cell killing in glioma: the Chimeric Antigen Receptor T-cell treatment Response in GliOma (CARRGO) model. The model includes rates of cancer cell proliferation, CAR T-cell killing, proliferation, exhaustion, and persistence. We use patient-derived and engineered cancer cell lines with an in vitro real-time cell analyser to parametrize the CARRGO model. We observe that CAR T-cell dose correlates inversely with the killing rate and correlates directly with the net rate of proliferation and exhaustion. This suggests that at a lower dose of CAR T-cells, individual T-cells kill more cancer cells but become more exhausted when compared with higher doses. Furthermore, the exhaustion rate was observed to increase significantly with tumour growth rate and was dependent on level of antigen expression. The CARRGO model highlights nonlinear dynamics involved in CAR T-cell therapy and provides novel insights into the kinetics of CAR T-cell killing. The model suggests that CAR T-cell treatment may be tailored to individual tumour characteristics including tumour growth rate and antigen level to maximize therapeutic benefit.
    Type of Medium: Online Resource
    ISSN: 1742-5689 , 1742-5662
    URL: Article
    DOI: 10.1098/rsif.2019.0734
    Language: English
    Publisher: The Royal Society
    Publication Date: 2020
    detail.hit.zdb_id: 2156283-0
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  • 7
    Online Resource
    Online Resource
    Utilizing Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to Analyze Interstitial Fluid Flow and Transport in Glioblastoma and the Surrounding Parenchyma in Human Patients
    MDPI AG ; 2021
    In:  Pharmaceutics Vol. 13, No. 2 ( 2021-02-04), p. 212-
    Details
    In: Pharmaceutics, MDPI AG, Vol. 13, No. 2 ( 2021-02-04), p. 212-
    Abstract: Background: Glioblastoma (GBM) is the deadliest and most common brain tumor in adults, with poor survival and response to aggressive therapy. Limited access of drugs to tumor cells is one reason for such grim clinical outcomes. A driving force for therapeutic delivery is interstitial fluid flow (IFF), both within the tumor and in the surrounding brain parenchyma. However, convective and diffusive transport mechanisms are understudied. In this study, we examined the application of a novel image analysis method to measure fluid flow and diffusion in GBM patients. Methods: Here, we applied an imaging methodology that had been previously tested and validated in vitro, in silico, and in preclinical models of disease to archival patient data from the Ivy Glioblastoma Atlas Project (GAP) dataset. The analysis required the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which is readily available in the database. The analysis results, which consisted of IFF flow velocity and diffusion coefficients, were then compared to patient outcomes such as survival. Results: We characterized IFF and diffusion patterns in patients. We found strong correlations between flow rates measured within tumors and in the surrounding parenchymal space, where we hypothesized that velocities would be higher. Analyzing overall magnitudes indicated a significant correlation with both age and survival in this patient cohort. Additionally, we found that neither tumor size nor resection significantly altered the velocity magnitude. Lastly, we mapped the flow pathways in patient tumors and found a variability in the degree of directionality that we hypothesize may lead to information concerning treatment, invasive spread, and progression in future studies. Conclusions: An analysis of standard DCE-MRI in patients with GBM offers more information regarding IFF and transport within and around the tumor, shows that IFF is still detected post-resection, and indicates that velocity magnitudes correlate with patient prognosis.
    Type of Medium: Online Resource
    ISSN: 1999-4923
    URL: Article
    DOI: 10.3390/pharmaceutics13020212
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2527217-2
    SSG: 15,3
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