Clinical translation of a hand-held optical imager for breast cancer diagnostics: In vitro and in vivo tomography studies

Optical imaging is an emerging technology towards non-invasive breast cancer diagnostics. In recent years, portable and patient comfortable hand-held optical imagers are developed towards two-dimensional (2D) tumor detections. However, these imagers are not capable of three-dimensional (3D) tomography because they cannot register the positional information of the hand-held probe onto the imaged tissue. A hand-held optical imager has been developed in our Optical Imaging Laboratory with 3D tomography capabilities, as demonstrated from tissue phantom studies. The overall goal of my dissertation is towards the translation of our imager to the clinical setting for 3D tomographic imaging in human breast tissues. A systematic experimental approach was designed and executed as follows: (i) fast 2D imaging, (ii) coregistered imaging, and (iii) 3D tomographic imaging studies. (i) Fast 2D imaging was initially demonstrated in tissue phantoms (1% Liposyn solution) and in vitro (minced chicken breast and 1% Liposyn). A 0.45 cm3 fluorescent target at 1:0 contrast ratio was detectable up to 2.5 cm deep. Fast 2D imaging experiments performed in vivo with healthy female subjects also detected a 0.45 cm3 fluorescent target superficially placed ∼2.5 cm under the breast tissue. (ii) Coregistered imaging was automated and validated in phantoms with ∼0.19 cm error in the probe’s positional information. Coregistration also improved the target depth detection to 3.5 cm, from multi-location imaging approach. Coregistered imaging was further validated in-vivo , although the error in probe’s positional information increased to ∼0.9 cm (subject to soft tissue deformation and movement). (iii) Three-dimensional tomography studies were successfully demonstrated in vitro using 0.45 cm3 fluorescence targets. The feasibility of 3D tomography was demonstrated for the first time in breast tissues using the hand-held optical imager, wherein a 0.45 cm3 fluorescent target (superficially placed) was recovered along with artifacts. Diffuse optical imaging studies were performed in two breast cancer patients with invasive ductal carcinoma. The images showed greater absorption at the tumor cites (as observed from x-ray mammography, ultrasound, and/or MRI). In summary, my dissertation demonstrated the potential of a hand-held optical imager towards 2D breast tumor detection and 3D breast tomography, holding a promise for extensive clinical translational efforts.

Motion Correction Algorithm of Lung Tumors for Respiratory Gated PET Images

Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.