Publications by authors named "Enakshi D Sunassee"

2 Publications

  • Page 1 of 1

An Accessible Laparoscope for Surgery in Low- and Middle- Income Countries.

Ann Biomed Eng 2021 Jul 8;49(7):1657-1669. Epub 2021 Mar 8.

Duke Global Health Institute, Durham, NC, USA.

Laparoscopic surgery is the standard of care in high-income countries for many procedures in the chest and abdomen. It avoids large incisions by using a tiny camera and fine instruments manipulated through keyhole incisions, but it is generally unavailable in low- and middle-income countries (LMICs) due to the high cost of installment, lack of qualified maintenance personnel, unreliable electricity, and shortage of consumable items. Patients in LMICs would benefit from laparoscopic surgery, as advantages include decreased pain, improved recovery time, fewer wound infections, and shorter hospital stays. To address this need, we developed an accessible laparoscopic system, called the ReadyView laparoscope for use in LMICs. The device includes an integrated camera and LED light source that can be displayed on any monitor. The ReadyView laparoscope was evaluated with standard optical imaging targets to determine its performance against a state-of-the-art commercial laparoscope. The ReadyView laparoscope has a comparable resolving power, lens distortion, field of view, depth of field, and color reproduction accuracy to a commercially available endoscope, particularly at shorter, commonly-used working distances (3-5 cm). Additionally, the ReadyView has a cooler temperature profile, decreasing the risk for tissue injury and operating room fires. The ReadyView features a waterproof design, enabling sterilization by submersion, as commonly performed in LMICs. A custom desktop software was developed to view the video on a laptop computer with a frame rate greater than 30 frames per second and to white balance the image, which is critical for clinical use. The ReadyView laparoscope is capable of providing the image quality and overall performance needed for laparoscopic surgery. This portable low-cost system is well suited to increase access to laparoscopic surgery in LMICs.
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July 2021

Proliferation saturation index in an adaptive Bayesian approach to predict patient-specific radiotherapy responses.

Int J Radiat Biol 2019 10 19;95(10):1421-1426. Epub 2019 Mar 19.

Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute , Tampa , FL , USA.

Radiotherapy prescription dose and dose fractionation protocols vary little between individual patients having the same tumor grade and stage. To personalize radiotherapy a predictive model is needed to simulate radiation response. Previous modeling attempts with multiple variables and parameters have been shown to yield excellent data fits at the cost of non-identifiability and clinically unrealistic results. We develop a mathematical model based on a proliferation saturation index (PSI) that is a measurement of pre-treatment tumor volume-to-carrying capacity ratio that modulates intrinsic tumor growth and radiation response rates. In an adaptive Bayesian approach, we utilize an increasing number of data points for individual patients to predict patient-specific responses to subsequent radiation doses. Model analysis shows that using PSI as the only patient-specific parameter, model simulations can fit longitudinal clinical data with high accuracy (=0.84). By analyzing tumor response to radiation using daily CT scans early in the treatment, response to the remaining treatment fractions can be predicted after two weeks with high accuracy (c-index = 0.89). The PSI model may be suited to forecast treatment response for individual patients and offers actionable decision points for mid-treatment protocol adaptation. The presented work provides an actionable image-derived biomarker prior to and during therapy to personalize and adapt radiotherapy.
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October 2019