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.

4-hydroxy estradiol-induced oxidant-mediated signaling is involved in the development of breast cancer

Breast cancer is a disease associated with excess exposures to estrogens. While the mode of cancer causation is unknown, others have shown that oxidative stress induced by prolonged exposure to estrogens mediates renal, liver, endometrial and mammary tumorigenesis though the mechanism(s) underling this process is unknown. In this study, we show that 4-hydroxyl 17β-estradiol (4-OHE2), a catechol metabolite of estrogen, induces mammary tumorigenesis in a redox dependent manner. We found that the mechanism of tumorigenesis involves redox activations of nuclear respiratory factor-1 (NRF1); a transcriptions factor associated with regulation of mitochondria biogenesis and oxidative phosphorylation (OXPHOS), as well as mediation of cell survival and growth of cells during periods of oxidative stress. Key findings from our study are as follows: (i) Prolonged treatments of normal mammary epithelial cells with 4-OHE2, increased the formation of intracellular reactive oxygen species (ROS). (ii) Estrogen-induced ROS activates redox sensitive transcription factors NRF1. (iii) 4-OHE2 through activation of serine-threonine kinase and histone acetyl transferase, phosphorylates and acetylate NRF1 respectively. (iv) Redox mediated epigenetic modifications of NRF1 facilitates mammary tumorigenesis and invasive phenotypes of breast cancer cells via modulations of genes involved in proliferation, growth and metastasis of exposed cells. (v) Animal engraftment of transformed clones formed invasive tumors. (vi) Treatment of cells or tumors with biological or chemical antioxidants, as well as silencing of NRF1 expressions, prevented 4-OHE2 induced mammary tumorigenesis and invasive phenotypes of MCF-10A cells. Based on these observations, we hypothesize that 4-OHE2 induced ROS epigenetically activate NRF1 through its phosphorylation and acylation. This, in turn, through NRF1-mediated transcriptional activation of the cell cycle genes, controls 4-OHE2 induced cell transformation and tumorigenesis.^

A novel 3-D segmentation algorithm for anatomic liver and tumor volume calculations for liver cancer treatment planning

Three-Dimensional (3-D) imaging is vital in computer-assisted surgical planning including minimal invasive surgery, targeted drug delivery, and tumor resection. Selective Internal Radiation Therapy (SIRT) is a liver directed radiation therapy for the treatment of liver cancer. Accurate calculation of anatomical liver and tumor volumes are essential for the determination of the tumor to normal liver ratio and for the calculation of the dose of Y-90 microspheres that will result in high concentration of the radiation in the tumor region as compared to nearby healthy tissue. Present manual techniques for segmentation of the liver from Computed Tomography (CT) tend to be tedious and greatly dependent on the skill of the technician/doctor performing the task. ^ This dissertation presents the development and implementation of a fully integrated algorithm for 3-D liver and tumor segmentation from tri-phase CT that yield highly accurate estimations of the respective volumes of the liver and tumor(s). The algorithm as designed requires minimal human intervention without compromising the accuracy of the segmentation results. Embedded within this algorithm is an effective method for extracting blood vessels that feed the tumor(s) in order to plan effectively the appropriate treatment. ^ Segmentation of the liver led to an accuracy in excess of 95% in estimating liver volumes in 20 datasets in comparison to the manual gold standard volumes. In a similar comparison, tumor segmentation exhibited an accuracy of 86% in estimating tumor(s) volume(s). Qualitative results of the blood vessel segmentation algorithm demonstrated the effectiveness of the algorithm in extracting and rendering the vasculature structure of the liver. Results of the parallel computing process, using a single workstation, showed a 78% gain. Also, statistical analysis carried out to determine if the manual initialization has any impact on the accuracy showed user initialization independence in the results. ^ The dissertation thus provides a complete 3-D solution towards liver cancer treatment planning with the opportunity to extract, visualize and quantify the needed statistics for liver cancer treatment. Since SIRT requires highly accurate calculation of the liver and tumor volumes, this new method provides an effective and computationally efficient process required of such challenging clinical requirements.^