Simulation Study of Changes in Ultrasound Speckle Statistics With the System Point Spread Function

The intensity point signal-to-noise ratio, SNRI, characterizing the ultrasound speckle statistics, depends on the tissue scattering microstructure and the imaging systems point spread function. Both should be described in three-dimensional space. Therefore, a three-dimensional simulation model is used in this paper to generate a rf signal and study the variations in SNRI with the transducer center frequency and bandwidth. Results are in agreement with existing theoretical predictions. A possible method to analyze the SNRI data is also presented that can produce a straight line slope as a feature value that depends on the tissue scattering microstructure only. Such a feature may prove to be more useful than SNRI values in tissue characterization problems

Modeling Ultrasound Speckle Formation and its Dependence on Imaging System’s Impulse Response

Ultrasonic echoes, backscattered from an inhomogeneous medium have the character of a random signal, which is mainly responsible for the observed speckle in medical images. Such a medium can be modeled as a uniform matrix with scattering bodies distributed randomly. When the number of density of scatterers is high, the individual scatterers are not resolved by the imaging process, and a speckle pattern is produced as a result of interference of waves from many scatterers within the resolution cell volume. This cell volume depends on the beam profile and the pulse width of the interrogating pulse. We have used a 3 dimensional (3D) simulation phantom that takes into account the 3D distribution of scatterers and the 3D nature of the resolution cell volume. Several simulations were performed to study the effect of scatterer number density (SND) and resolution cell volume on the backscattered signal. Assuming the process is linear and the stochastic signal is ergodic and stationary, Kurtosis (K), which involves 2nd and 4th moments, was estimated in each case. We find that Kurtosis varies linearly with another parameter F that depends on the resolution cell volume. The results are analyzed in the light of theoretical predictions. Reasonable estimates of SND can be derived from the slope of Kurtosis vs. parameter F graph

Clinical application of biological markers for treatments of resectable non-small-cell lung cancers

We performed a clinical study to identify biological markers useful for the treatment of resectable non-small-cell lung cancers (NSCLCs). In all, 173 patients were studied. By immunohistochemistry, we evaluated the Ki-67 proliferation index, tumour vascularity, thymidylate synthase (TS), vascular endothelial growth factor (VEGF)-A, VEGF-C, and E (epithelial)-cadherin. Concerning the survival of NSCLC patients, tumour vascularity (P<0.01), VEGF-A status (P=0.03), VEGF-C status (P=0.03), and E-cadherin status (P=0.03) were significant prognostic factors in patients with stage I NSCLCs. The Ki-67 proliferation index (P=0.02) and TS status (P<0.01) were significant prognostic factors in patients with stage II–III NSCLCs. In patients with stage II–III NSCLCs, furthermore, the survival of UFT (a combination of tegafur and uracil)-treated patients with TS-negative tumours was significantly better than those of any other patients. Biological markers associated with tumour angiogenesis or metastasis are useful for the detection of aggressive tumours among early-stage NSCLCs. Postoperative chemotherapy might be necessary in such tumours even in stage I. In contrast, tumour proliferation rate and TS status are useful markers for identifying less aggressive tumours in locally advanced NSCLCs. Thymidylate synthase expression is also a useful marker to evaluate responsiveness of UFT-based chemotherapy for these tumours

Expression of thymidylate synthase in human cells is an early G1 event regulated by CDK4 and p16INK4A but not E2F

Thymidylate synthase (TS) is the enzyme that catalyses the last step in de novo thymidylate synthesis. It is of interest clinically because it is an effective target for drugs such as 5-fluorouracil, often used in combination therapy. Despite a number of earlier reports indicating that TS is a cell cycle-dependent enzyme, this remains equivocal. Here, we show that in HCT116 cells synchronised by serum starvation, there is a clear dissociation between the expression of cyclin E (a well-characterised cell-cycle protein) and TS. Although both cyclin E and TS mRNA and protein increased during G1, TS upregulation was delayed. Moreover, TS levels did not decrease following S-phase completion while cyclin E decreased sharply. Similarly, clear differences were seen between cyclin E and TS as asynchronously growing HCT116 cells were growth-inhibited by low-serum treatment. In contrast to previous reports using rodent cells, adenovirus-mediated over-expression of E2F1 and cyclin E in three human cell lines had no effect on TS. Cell-cycle progression was blocked by treatment of cells with pharmacological inhibitors of CDK2 and CDK4 and by ectopic expression of p16INK4A. Whereas CDK2 inhibition had no effect on TS levels, inhibition of CDK4 was associated with decreased TS protein levels. These results provide the first evidence that drugs targeting CDK4 may be useful with anti-TS drugs as combination therapy for cancer