Thursday, March 3, 2016, 1:00–3:00pm
Room 105, Cummings Hall
“Optimizing near-infrared spectral tomography (NIRST) for diagnostic imaging and treatment monitoring of cancer of the breast”
Near-infrared spectral tomography (NIRST) continues to be intensively investigated for clinical application in breast imaging, by supplying functional details about physiologically related biomarkers for example oxy- and deoxy-hemoglobin, water, fat and scatter component. Within this thesis, a number of studies on system development and renovation formula were completed to be able to enhance the imaging quality of MR-guide NIRST and also to predicate cancer of the breast reaction to neo-adjuvant chemotherapy. To optimize image recovery which maximizes distinction between malignant and benign lesions, non-straight line iterative reconstructions of MR-Led NIST images are retrieved utilizing an L-curve based formula, and put on medical trial data. The record analyses have proven the new approach dramatically improved the record importance to differentiating malignant from benign lesions. While MRI guide NIRST was used to identify cancer of the breast, NIRST can also be accustomed to predicate and monitor breast tumor responses in patients with in your area advanced cancer of the breast undergoing neoadjuvant treatment. According to a current hybrid NIRST system developed at Dartmouth, a concise and portable NIRST system continues to be produced for imaging patients within the infusion unit while people are waiting for or undergoing infusion. This technique can buy frequency-domain and continuous-wave data concurrently within the wave length selection of 660nm to 1064nm, with total imaging time under 90s.
As the functionality of the present system and renovation approach happen to be validated through the phantom, normal subject and abnormal subject studies, two key facets of the studies is going to be transported in the ultimate phase of the thesis. First, systematic optimization from the image renovation workflow and also the source-detector array design is going to be investigated on existing dataset, to steer the style of next-generation MR-guide NIRST system. Various nonlinear image renovation strategies is going to be also applied and investigated to enhance the diagnostic performance. Second, another sub-source system with a lot more wavelengths is going to be added in to the portable NIRST system, and also the adjustable breast interface is going to be re-made to fit different sized breasts and tumor locations. With the ongoing patient study, key optical biomarkers is going to be identified to distinguish complete from incomplete response patient groups to neoadjuvant chemotherapy.
- Shudong Jiang, PhD (Chair)
- John Pogue, PhD (Co-chair)
- Keith Paulsen, PhD
- Bruce Tromberg, PhD (Exterior)
To learn more, contact Daryl Laware at firstname.lastname@example.org .
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