Adaptive SPECT: personalizing medical imaging

We develop modern techniques for image quality evaluation and optimization of imaging systems, and use them to control adaptive SPECT systems. Our results should contribute to the development of more personalized and efficient medical imaging

Efficient optimization based on local shift-invariance for adaptive SPECT systems

Adaptive SPECT systems automatically change some of their settings to maximize the image quality for a given subject and purpose. This approach has a lot of potential, and could lead to drastic improvements in performance. In particular, it would be very useful in high resolution pinhole SPECT, where the low sensitivity requires higher radiation doses or longer imaging times compared to other systems. In order to have adaptation in real-time, we need a fast method for optimizing the adaptive settings according to a given figure of merit. This is still a big challenge. Based on previous work, we address in this paper the issue of fast evaluation of image quality and optimization, for a class of adaptive SPECT systems. We evaluate the image quality in a voxel of interest, reconstructed using post- filtered MLEM, with the contrast-to-noise ratio (CNR). The CNR is computed analytically, using an approximation based on the Fisher information matrix and assuming local shift-invariance on the Fisher information matrices per adaptation parameter. We maximize the CNR with a gradient based optimization approach. We then test this method in the optimization of the angular sampling of a single-head SPECT system which rotates around a phantom. In this case, the method proved to be very efficient, and at the same time showed good agreement with previous results in literature and with the outcome from reconstructions

CAPG and GIPC1: Breast Cancer Biomarkers for Bone Metastasis Development and Treatment.

Bone is the predominant site of metastasis from breast cancer, and recent trials have demonstrated that adjuvant bisphosphonate therapy can reduce bone metastasis development and improve survival. There is an unmet need for prognostic and predictive biomarkers so that therapy can be appropriately targeted.Potential biomarkers for bone metastasis were identified using proteomic comparison of bone-metastatic, lung-metastatic, and nonmetastatic variants of human breast cancer MDA-MB-231 cells. Clinical validation was performed using immunohistochemical staining of tumor tissue microarrays from patients in a large randomized trial of adjuvant zoledronic acid (zoledronate) (AZURE-ISRCTN79831382). We used Cox proportional hazards regression, the Kaplan-Meier estimate of the survival function, and the log-rank test to investigate associations between protein expression, clinical variables, and time to distant recurrence events. All statistical tests were two-sided.Two novel biomarker candidates, macrophage-capping protein (CAPG) and PDZ domain-containing protein GIPC1 (GIPC1), were identified for clinical validation. Cox regression analysis of AZURE training and validation sets showed that control patients (no zoledronate) were more likely to develop first distant recurrence in bone (hazard ratio [HR] = 4.5, 95% confidence interval [CI] = 2.1 to 9.8, P < .001) and die (HR for overall survival = 1.8, 95% CI = 1.01 to 3.24, P = .045) if both proteins were highly expressed in the primary tumor. In patients with high expression of both proteins, zoledronate had a substantial effect, leading to 10-fold hazard ratio reduction (compared with control) for first distant recurrence in bone (P = .008).The composite biomarker, CAPG and GIPC1 in primary breast tumors, predicted disease outcomes and benefit from zoledronate and may facilitate patient selection for adjuvant bisphosphonate treatment

Regulation of gene expression in ovarian cancer cells by luteinizing hormone receptor expression and activation

<p>Abstract</p> <p>Background</p> <p>Since a substantial percentage of ovarian cancers express gonadotropin receptors and are responsive to the relatively high concentrations of pituitary gonadotropins during the postmenopausal years, it has been suggested that receptor activation may contribute to the etiology and/or progression of the neoplasm. The goal of the present study was to develop a cell model to determine the impact of luteinizing hormone (LH) receptor (LHR) expression and LH-mediated LHR activation on gene expression and thus obtain insights into the mechanism of gonadotropin action on ovarian surface epithelial (OSE) carcinoma cells.</p> <p>Methods</p> <p>The human ovarian cancer cell line, SKOV-3, was stably transfected to express functional LHR and incubated with LH for various periods of time (0-20 hours). Transcriptomic profiling was performed on these cells to identify LHR expression/activation-dependent changes in gene expression levels and pathways by microarray and qRT-PCR analyses.</p> <p>Results</p> <p>Through comparative analysis on the LHR-transfected SKOV-3 cells exposed to LH, we observed the differential expression of 1,783 genes in response to LH treatment, among which five significant families were enriched, including those of growth factors, translation regulators, transporters, G-protein coupled receptors, and ligand-dependent nuclear receptors. The most highly induced early and intermediate responses were found to occupy a network impacting transcriptional regulation, cell growth, apoptosis, and multiple signaling transductions, giving indications of LH-induced apoptosis and cell growth inhibition through the significant changes in, for example, tumor necrosis factor, Jun and many others, supportive of the observed cell growth reduction in <it>in vitro </it>assays. However, other observations, e.g. the substantial up-regulation of the genes encoding the endothelin-1 subtype A receptor, stromal cell-derived factor 1, and insulin-like growth factor II, all of which are potential therapeutic targets, may reflect a positive mediation of ovarian cancer growth.</p> <p>Conclusion</p> <p>Overall, the present study elucidates the extensive transcriptomic changes of ovarian cancer cells in response to LH receptor activation, which provides a comprehensive and objective assessment for determining new cancer therapies and potential serum markers, of which over 100 are suggested.</p

Updates in Gastrointestinal Oncology – insights from the 2008 44th annual meeting of the American Society of Clinical Oncology

We have reviewed the pivotal presentations rcelated to colorectal cancer (CRC) and other gastrointestinal malignancies from 2008 annual meeting of the American Society of Clinical Oncology (ASCO). We have discussed the scientific findings and the impact on practice guidelines and ongoing clinical trials. The report on KRAS status in patients with metastatic CRC receiving epidermal growth factor receptor (EGFR) targeted antibody treatment has led to a change in National Comprehensive Cancer Network guideline that recommends only patients with wild-type KRAS tumor should receive this treatment. The results of double biologics (bevacizumab and anti-EGFR antibody) plus chemotherapy as first-line treatment in patients with metastatic CRC has shown a worse outcome than bevacizumab-based regimen. Microsatellite Instability has again been confirmed to be an important predictor in patients with stage II colon cancer receiving adjuvant treatment

Targeting cancer metabolism: a therapeutic window opens

Genetic events in cancer activate signalling pathways that alter cell metabolism. Clinical evidence has linked cell metabolism with cancer outcomes. Together, these observations have raised interest in targeting metabolic enzymes for cancer therapy, but they have also raised concerns that these therapies would have unacceptable effects on normal cells. However, some of the first cancer therapies that were developed target the specific metabolic needs of cancer cells and remain effective agents in the clinic today. Research into how changes in cell metabolism promote tumour growth has accelerated in recent years. This has refocused efforts to target metabolic dependencies of cancer cells as a selective anticancer strategy.Burroughs Wellcome FundSmith Family FoundationStarr Cancer ConsortiumDamon Runyon Cancer Research FoundationNational Institutes of Health (U.S.