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1. Automated Body Composition Analysis Using DAFS Express on 2D MRI Slices at L3 Vertebral Level

Author

Akella, Varun, Bagherinasab, Razeyeh, Li, Jia Ming, Nguyen, Long, Chow, Vincent Tze Yang, Lee, Hyunwoo, Popuri, Karteek, and Beg, Mirza Faisal

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Body composition analysis is vital in assessing health conditions such as obesity, sarcopenia, and metabolic syndromes. MRI provides detailed images of skeletal muscle (SKM), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT), but their manual segmentation is labor-intensive and limits clinical applicability. This study validates an automated tool for MRI-based 2D body composition analysis- (Data Analysis Facilitation Suite (DAFS) Express), comparing its automated measurements with expert manual segmentations using UK Biobank data. A cohort of 399 participants from the UK Biobank dataset was selected, yielding 423 single L3 slices for analysis. DAFS Express performed automated segmentations of SKM, VAT, and SAT, which were then manually corrected by expert raters for validation. Evaluation metrics included Jaccard coefficients, Dice scores, Intraclass Correlation Coefficients (ICCs), and Bland-Altman Plots to assess segmentation agreement and reliability. High agreements were observed between automated and manual segmentations with mean Jaccard scores: SKM 99.03%, VAT 95.25%, and SAT 99.57%; and mean Dice scores: SKM 99.51%, VAT 97.41%, and SAT 99.78%. Cross-sectional area comparisons showed consistent measurements with automated methods closely matching manual measurements for SKM and SAT, and slightly higher values for VAT (SKM: Auto 132.51 cm^2, Manual 132.36 cm^2; VAT: Auto 137.07 cm^2, Manual 134.46 cm^2; SAT: Auto 203.39 cm^2, Manual 202.85 cm^2). ICCs confirmed strong reliability (SKM: 0.998, VAT: 0.994, SAT: 0.994). Bland-Altman plots revealed minimal biases, and boxplots illustrated distribution similarities across SKM, VAT, and SAT areas. On average DAFS Express took 18 seconds per DICOM. This underscores its potential to streamline image analysis processes in research and clinical settings, enhancing diagnostic accuracy and efficiency.

Published
2024

8. Safety, tolerability, and effectiveness of the sodium-glucose cotransporter 2 inhibitor (SGLT2i) dapagliflozin in combination with standard chemotherapy for patients with advanced, inoperable pancreatic adenocarcinoma: a phase 1b observational study

Author

Park, Lauren K., Lim, Kian-Huat, Volkman, Jonas, Abdiannia, Mina, Johnston, Hannah, Nigogosyan, Zack, Siegel, Marilyn J., McGill, Janet B., McKee, Alexis M., Salam, Maamoun, Zhang, Rong M., Ma, Da, Popuri, Karteek, Chow, Vincent Tze Yang, Beg, Mirza Faisal, Hawkins, William G., Peterson, Linda R., and Ippolito, Joseph E.

Published
2023
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9. Comprehensive Validation of Automated Whole Body Skeletal Muscle, Adipose Tissue, and Bone Segmentation from 3D CT images for Body Composition Analysis: Towards Extended Body Composition

Author

Ma, Da, Chow, Vincent, Popuri, Karteek, and Beg, Mirza Faisal

Subjects
Computer Science - Computer Vision and Pattern Recognition, Quantitative Biology - Tissues and Organs
Abstract

The latest advances in computer-assisted precision medicine are making it feasible to move from population-wide models that are useful to discover aggregate patterns that hold for group-based analysis to patient-specific models that can drive patient-specific decisions with regard to treatment choices, and predictions of outcomes of treatment. Body Composition is recognized as an important driver and risk factor for a wide variety of diseases, as well as a predictor of individual patient-specific clinical outcomes to treatment choices or surgical interventions. 3D CT images are routinely acquired in the oncological worklows and deliver accurate rendering of internal anatomy and therefore can be used opportunistically to assess the amount of skeletal muscle and adipose tissue compartments. Powerful tools of artificial intelligence such as deep learning are making it feasible now to segment the entire 3D image and generate accurate measurements of all internal anatomy. These will enable the overcoming of the severe bottleneck that existed previously, namely, the need for manual segmentation, which was prohibitive to scale to the hundreds of 2D axial slices that made up a 3D volumetric image. Automated tools such as presented here will now enable harvesting whole-body measurements from 3D CT or MRI images, leading to a new era of discovery of the drivers of various diseases based on individual tissue, organ volume, shape, and functional status. These measurements were hitherto unavailable thereby limiting the field to a very small and limited subset. These discoveries and the potential to perform individual image segmentation with high speed and accuracy are likely to lead to the incorporation of these 3D measures into individual specific treatment planning models related to nutrition, aging, chemotoxicity, surgery and survival after the onset of a major disease such as cancer., Comment: This paper is based on concepts presented at the NIH Body Composition and Cancer Outcomes Research Webinar Series on December 17th, 2020 by Mirza Faisal Beg titled "Automating Body Composition from Routinely Acquired CT images - towards 3D measurements". The talk is archived [here](https://epi.grants.cancer.gov/events/body-composition/#past)

Published
2021

14. Deep Local Trajectory Replanning and Control for Robot Navigation

Author

Pokle, Ashwini, Martín-Martín, Roberto, Goebel, Patrick, Chow, Vincent, Ewald, Hans M., Yang, Junwei, Wang, Zhenkai, Sadeghian, Amir, Sadigh, Dorsa, Savarese, Silvio, and Vázquez, Marynel

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence
Abstract

We present a navigation system that combines ideas from hierarchical planning and machine learning. The system uses a traditional global planner to compute optimal paths towards a goal, and a deep local trajectory planner and velocity controller to compute motion commands. The latter components of the system adjust the behavior of the robot through attention mechanisms such that it moves towards the goal, avoids obstacles, and respects the space of nearby pedestrians. Both the structure of the proposed deep models and the use of attention mechanisms make the system's execution interpretable. Our simulation experiments suggest that the proposed architecture outperforms baselines that try to map global plan information and sensor data directly to velocity commands. In comparison to a hand-designed traditional navigation system, the proposed approach showed more consistent performance.

Published
2019
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18. A phase 1, first-in-human study of AMG 900, an orally administered pan-Aurora kinase inhibitor, in adult patients with advanced solid tumors

Author

Carducci, Michael, Shaheen, Montaser, Markman, Ben, Hurvitz, Sara, Mahadevan, Daruka, Kotasek, Dusan, Goodman, Oscar B, Rasmussen, Erik, Chow, Vincent, Juan, Gloria, Friberg, Gregory R, Gamelin, Erick, Vogl, Florian D, and Desai, Jayesh

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Cancer, Clinical Trials and Supportive Activities, Clinical Research, Evaluation of treatments and therapeutic interventions, 6.1 Pharmaceuticals, 6.2 Cellular and gene therapies, Administration, Oral, Adult, Aged, Aurora Kinases, Biomarkers, Tumor, Cohort Studies, Dose-Response Relationship, Drug, Female, Humans, Male, Maximum Tolerated Dose, Middle Aged, Neoplasm Staging, Neoplasms, Phthalazines, Progression-Free Survival, Protein Kinase Inhibitors, Treatment Outcome, AMG 900, Antimitotic, Aurora kinase, pan-Aurora kinase inhibitor, Pharmacology and Pharmaceutical Sciences, Oncology & Carcinogenesis, Oncology and carcinogenesis, Pharmacology and pharmaceutical sciences
Abstract

Background Aurora kinase overexpression or amplifications are associated with high proliferation, poor prognosis, and therapeutic resistance in human tumors. AMG 900 is an investigational, oral, selective pan-Aurora kinase inhibitor. Methods This first-in-human trial included dose-escalation and dose-expansion phases ( ClinicalTrials.gov : NCT00858377). Dose escalation evaluated the safety, tolerability, and pharmacokinetics of AMG 900 in advanced solid tumors and determined the maximum tolerated dose (MTD) with/without granulocyte colony-stimulating factor (G-CSF) prophylaxis. Dose expansion evaluated clinical activity in three tumor types: taxane- and platinum-resistant ovarian cancer, taxane-resistant triple-negative breast cancer (TNBC), and castration-resistant and taxane- or cisplatin/etoposide-resistant prostate cancer (CRPC). AMG 900 was administered 4 days on/10 days off at 1-50 mg/day during escalation and at the MTD with G-CSF during expansion. Results AMG 900 showed rapid absorption with fast clearance, supporting once-daily dosing. The MTD was 25 mg/day, increasing to 40 mg/day with G-CSF. Grade ≥ 3 treatment-related adverse events included neutropenia (37%), anemia (23%), leukopenia (14%), and thrombocytopenia (12%). During dose expansion, 3/29 (10.3%, 95% CI: 2.0%-28.0%) evaluable patients with ovarian cancer experienced partial response by central imaging per RECIST 1.1; median duration of response was 24.1 weeks (95% CI: 16.1-34.1). Seven patients (24.1%, 95% CI: 10.3%-43.5%) experienced partial response per Gynecologic Cancer InterGroup criteria; 5/9 patients positive for p53 expression responded to treatment. No objective responses were observed in patients with TNBC or CRPC per RECIST 1.1. Conclusions AMG 900 40 mg/day with G-CSF had manageable toxicity and demonstrated single-agent activity in patients with heavily pretreated, chemotherapy-resistant ovarian cancer.

Published
2018

39. Differential effects of microRNAs miR‐21, miR‐99 and miR‐145 on lung regeneration and inflammation during recovery from influenza pneumonia

Author

Ong, Joe Wee Jian, primary, Tan, Kai Sen, additional, Lee, Joseph Jing Xian, additional, Seet, Ju Ee, additional, Choi, Hyung Won, additional, Ler, Siok Ghee, additional, Gunaratne, Jayantha, additional, Narasaraju, Teluguakula, additional, Sham, Lok‐To, additional, Patzel, Volker, additional, and Chow, Vincent T., additional

Published
2023
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45. Online Health Education on SARS to University Students during the SARS Outbreak

Author

Wong, Mee Lian, Koh, David, Iyer, Prasad, Seow, Adeline, Goh, Lee Gan, Chia, Sin Eng, Lim, Meng Kin, Ng, Daniel, Ong, Choon Nam, Phua, Kai Hong, Tambyah, Paul, Chow, Vincent T K, Chew, Suok Kai, Chandran, Ravi, and Lee, Hin Peng

Abstract

Little is known about how online learning may be used to disseminate health information rapidly and widely to large university populations if there is an infectious disease outbreak. During the SARS outbreak in Singapore in 2003, a six-lesson elearning module on SARS was developed for a large university population of 32,000 students. The module was developed within 2 months by 12 academic staff from medicine, economics, basic science, health promotion, microbiology, epidemiology and public health with support from 2 IT experts and 2 support staff. To ensure coverage of the entire student population, all students were required to complete the module within 9 months of its implementation to fulfill the graduation requirement. About 5,000 (16%) students read the module within the first month and almost all (96%) within 9 months of its implementation. The majority (86%) of the students who took the module for credits passed the module. Using this online format, health information was disseminated rapidly and efficiently to all university students during the SARS outbreak. This module could be adapted to other institutions with Internet support to disseminate timely health messages efficiently should an infectious disease outbreak occur. (Contains 1 table and 5 figures.)

Published
2005

46. SARS-CoV-2 and Influenza Co-Infection: Fair Competition or Sinister Combination?

Author

Teluguakula, Narasaraju, Chow, Vincent T. K., Pandareesh, Mirazkar Dasharatharao, Dasegowda, Venkatesha, Kurrapotula, Vidyasagar, Gopegowda, Shivaramu M., and Radic, Marko

Subjects
*INFLUENZA, *SARS-CoV-2, *MIXED infections, *COVID-19, *INFLUENZA viruses
Abstract

The COVID-19 pandemic remains a serious public health problem globally. During winter influenza seasons, more aggressive SARS-CoV-2 infections and fatalities have been documented, indicating that influenza co-infections may significantly impact the disease outcome of COVID-19. Both influenza and SARS-CoV-2 viruses share many similarities in their transmission and their cellular tropism for replication in the human respiratory tract. However, the complex intricacies and multi-faceted dynamics of how the two pathogens interact to ensure their survival in the same lung microenvironment are still unclear. In addition, clinical studies on influenza co-infections in COVID-19 patients do not provide conclusive evidence of how influenza co-infection mechanistically modifies disease outcomes of COVID-19. This review discusses various viral as well as host factors that potentially influence the survival or synergism of these two respiratory pathogens in the infected lung microenvironment. [ABSTRACT FROM AUTHOR]

Published
2024
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47. EV71:TLLcho virus murine model of enterovirus A71 neurological disease does not exhibit neurogenic pulmonary oedema.

Author

VICTORIO, Carla Bianca LUENA, I-Ly CHUA, Yishi XU, Qimei NG, Beng Hooi CHUA, CHOW, Vincent T. K., and Kaw Bing CHUA

Abstract

Small animal models play an important role in investigating and revealing the molecular determinants and mechanisms underlying neuro-virulence of enterovirus A71 (EV-A71). In our previous study, we successfully developed two mouse cell-line replication competent EV-A71 strains (EV71:TLLm and EV71:TLLmv) which were capable of inducing neuro-invasion in BALB/c mice. The more virulent EV71:TLLmv exhibited ability to induce acute encephalomyelitis accompanied by neurogenic pulmonary oedema. EV71:TLLcho virus strain was generated from EV71:TLLm by a series of passages in CHO-K1 cells. EV71:TLLcho demonstrated a broader range of infectivity across various mammalian cell lines and exhibited complete cytopathic effects (CPE) within 48 hours post-inoculation in comparison to EV71:TLLm or EV71:TLLmv. EV71:TLLcho consistently yielded higher levels of viral replication at all time points examined. In comparison to EV71:TLLm, EV71:TLLcho consistently induced more severe disease and increased mortality in one-week old BALB/c mice. However, unlike mice challenged with EV71:TLLmv, none of the mice challenged with EV71:TLLcho progressed to severe acute encephalomyelitis and developed neurogenic pulmonary oedema. [ABSTRACT FROM AUTHOR]

Published
2024

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