A new method for registrationbased medical image interpolation

Abstract—A new technique is presented for interpolating between grey-scale images in a medical data set. Registration between neighboring slices is achieved with a modified control grid interpolation algorithm that selectively accepts displacement field updates in a manner optimized for performance. A cubic interpolator is then applied to pixel intensities correlated by the displacement fields. Special considerations are made for efficiency, interpolation quality, and compression in the implementation of the algorithm. Experimental results show that the new method achieves good quality, while offering dramatic improvement in efficiency relative to the best competing method. Index Terms—Interpolation, reconstruction, registration. I

Predictive value of expression of p16INK4A, retinoblastoma and p53 proteins for the prognosis of non-small-cell lung cancers

The predictive value of expression of p16INK4A, retinoblastoma (Rb) and p53 proteins for prognosis was evaluated in 76 patients with non-small-cell lung cancers (NSCLCs) that were potentially curatively resected between 1990 and 1995, using the results of immunostaining analyses of these proteins as reported in our previous study (Kinoshita et al, 1996). Of these NSCLCs, 22 (29%) lacked p16 protein expression and eight (11%) Rb protein, while 30 (39%) showed positive (altered) p53 protein expression. Survival of patients with p16-negative tumours was not significantly different from that of patients with p16-positive tumours (5-year survival rates 67% and 72% respectively, P = 0.8), nor was survival of patients with Rb-negative tumours significantly different from that of patients with Rb-positive tumours (5-year survival rates 42% and 69% respectively, P = 0.9). Moreover, survival of patients with p16/Rb-negative (either p16- or Rb-negative) tumours was not significantly different from that of patients with p16/Rb-positive (both p16- and Rb-positive) tumours (5-year survival rates 67% and 68% respectively, P = 0.7). In contrast, survival of patients with p53-positive (altered) tumours tended to be shorter than that of patients with p53-negative (unaltered) tumours (5-year survival rates 56% and 78% respectively, P = 0.06). In univariate analysis of potential prognostic factors, p16, Rb and p16/Rb proteins were not significant prognostic factors in the present cohort of potentially curatively resected NSCLCs. Altered p53 protein status tended to be a negative prognostic factor (P = 0.06 by the univariate analysis). These results indicate that loss of p16 protein alone, or in combination with loss of Rb protein, does not predict the clinical outcome of patients with resected NSCLCs. © 1999 Cancer Research Campaig

On the Cost Structure of the Japanese Property-Casualty Insurance Industry

This article tests economies of scale and economies of scope for the property-casualty insurance companies in Japan. We fit a composite cost function to a set of Japanese firms over the period from 1980 to 1995 and employ an error components model. Our main findings are as follows. First, statistically significant economies of scale are observed in both Japanese firms and foreign firms operating in Japan. Second, economies of scope are also statistically significant for Japanese firms and most of the foreign insurers between the "third sector" products and the rest of the property-casualty insurance lines. Copyright The Journal of Risk and Insurance.

Targeting gene expression selectively in cancer cells by using the progression-elevated gene-3 promoter

One impediment to effective cancer-specific gene therapy is the rarity of regulatory sequences targeting gene expression selectively in tumor cells. Although many tissue-specific promoters are recognized, few cancer-selective gene promoters are available. Progression-elevated gene-3 (PEG-3) is a rodent gene identified by subtraction hybridization that displays elevated expression as a function of transformation by diversely acting oncogenes, DNA damage, and cancer cell progression. The promoter of PEG-3, PEG-Prom, displays robust expression in a broad spectrum of human cancer cell lines with marginal expression in normal cellular counterparts. Whereas GFP expression, when under the control of a CMV promoter, is detected in both normal and cancer cells, when GFP is expressed under the control of the PEG-Prom, cancer-selective expression is evident. Mutational analysis identifies the AP-1 and PEA-3 transcription factors as primary mediators of selective, cancer-specific expression of the PEG-Prom. Synthesis of apoptosis-inducing genes, under the control of the CMV promoter, inhibits the growth of both normal and cancer cells, whereas PEG-Prom-mediated expression of these genes kills only cancer cells and spares normal cells. The efficacy of the PEG-Prom as part of a cancer gene therapeutic regimen is further documented by in vivo experiments in which PEG-Prom-controlled expression of an apoptosis-inducing gene completely inhibited prostate cancer xenograft growth in nude mice. These compelling observations indicate that the PEG-Prom, with its cancer-specific expression, provides a means of selectively delivering genes to cancer cells, thereby providing a crucial component in developing effective cancer gene therapies