Clinical applications of imaging informatics: computer aided diagnosis of nasopharyngeal carcinoma based on PET-CTand multimedia electronic patient record system for neurosurgery

Abstract

Medical imaging informatics is one of the important research areas in radiology that studies how information available on medical images is retrieved, analyzed, and enhanced. Recent development in medical imaging informatics has resulted in improvement of diagnostic accuracy based on imaging examinations, as well as efficiency in clinical workflow. Computer aided diagnosis (CAD) and electronic patient record system (ePR) are both topics in medical imaging informatics that have matured from research concepts into commercially available computerized systems in clinical environment. The current challenges are to further broaden their scope of applications. In this thesis project, I developed a CAD system for interpreting PET/CT examinations and an ePR system for patient data integration in neurosurgery suites. Specifically, the CAD system in this project was designed to automatically diagnose nasopharyngeal carcinoma (NPC) on Positron emission tomography/computed tomography (PET/CT) examinations, which aimed to detect and classify both the primary NPC and its nodal metastasis. The regions of interests (ROIs) were segmented from the PET images and registered onto the CT in order to combine the imaging features from both modalities and the a priori anatomical knowledge of the suspicious lesion. These combined features were then classified by a support vector machine (SVM) to generate the final diagnosis result. The system was validated with 25 PET/CT examinations from 10 patients suffering from NPC, and the result produced by the system was compared to the gold standard of lesions manually contoured by experienced radiologists. The results confirmed that the system successfully distinguished all 53 genuine lesions from the mimickers due to normal physiological uptake and artifacts that also produced potentially confusing signals. The second part of the project involved development of an electronic patient record system (ePR) that integrated all the myriad of images and different types of clinical information before, during, and after neurosurgery operations, in order to enhance efficiency of work flow in this unique clinical environment. The system comprises of pre-, intra-, and post-operation modules which correspond to the different stages of the neurosurgery. The pre-op module was developed to store and categorize all images and data before the procedure to assist the surgeons in planning operation. The intra-op module integrates all the input signals, waveforms, images and videos that are produced by different imaging and physiological monitoring devices in the operation room during the surgery, and displays all the relevant information in a single large screen in real time to ease monitoring of the procedure. The post-op module helps surgeons to review all the data acquired from all the prior stages for follow-up of the treatment outcome. One-tumor case was utilized to test the pre-op module, and the signals and waveforms simulators were used to evaluate the performance of the intra-op module. In summary, two different medical informatics systems, a CAD and an ePR system were developed. Both showed promising results in laboratory tests. Future work would involve performance enhancement and feedback of the systems, and ultimately evaluation of these systems in the clinical environment.