Serum PON1 arylesterase activity in relation to hyperhomocysteinaemia and oxidative stress in young adult central retinal venous occlusion patients.

AIM: To estimate the arylesterase activity of serum paraoxonase-1 (PON1-ARE), which is reported to have an antioxidant and antiatherogenic potential and to correlate with plasma homocysteine (Hcys) and plasma TBARS in young adult central retinal venous occlusion (CRVO) patients. METHODS: A case-control prospective study carried out in 10 CRVO patients (mean age 27+/-5 years; 7 males, 3 females) and 20 healthy controls (mean age 29+/-5 years; 15 males, 5 females). RESULTS: The CRVO patients showed a significantly lowered serum PON1-ARE activity (P=0.009) along with a significant increase in the levels of plasma Hcys (P=0.018) when compared to the control subjects. There was a negative correlation between serum PON1-ARE and plasma Hcys levels (P=0.058) as well as between PON1-ARE and plasma TBARS levels (P=0.001) in the CRVO patients. CONCLUSION: This is the first report of lowered serum PON1-ARE level as a risk factor for CRVO (OR= 1.108, CI=0.914, 1.314; P=0.296), which is found to correlate with oxidative stress.

Survival from primary breast cancer after routine clinical use of mammography.

Clinical trials indicate that mammography provides a substantial breast cancer survival benefit; however, there is a need to demonstrate that this benefit extends to clinical practice and to determine the extent that current reductions in mortality are attributable to regular screening or adjuvant systemic therapy. Mammography was used routinely at our institution across a broad age range, in an era when most patients received no adjuvant systemic therapy. We examined breast cancer survival for a cohort of 678 stage I-III primary invasive breast cancer patients accrued from 1971 to 1990, and followed to 1996; 18% received adjuvant hormonal therapy and 15% received adjuvant chemotherapy. There were 61 women less than 40 years old; 136, 40-49 years; 341, 50-69 years; 140, > or =70 years. Factors available for multivariate investigations were age (years), tumor size (cm), nodal status (N-, Nx, N+), ER (fmol/mg protein), PgR (fmol/mg protein), adjuvant radiotherapy (no, yes), adjuvant hormonal therapy (no, yes), and adjuvant chemotherapy (no, yes). Forward stepwise multivariate regression with log-normal survival analysis was used to examine the effects of these factors on disease-specific survival. Ten-year survival by tumor size was adjusted for the effects of other significant factors. For women less than 40 years of age, 10-year survival at the T1a, T1b, T1c, and T2 cut-points for tumor size is, respectively, 0.77, 0.74, 0.67, 0.44; for 40-49 years it is 0.92, 0.90, 0.85, 0.62; for 50-69 years it is 0.81, 0.79, 0.75, 0.62; for > or =70 years it is 0.84, 0.81, 0.73, 0.44. With routine use of clinical mammography and up to 26 years of follow-up, we found breast cancer survival to be significantly better (p< or = 0.05) for all women with smaller tumors and that survival indicated a change in natural disease history with early detection. The Canadian National Breast Screening Study (NBSS) controls had significantly smaller tumors (p < 0.001) than our patients, which may indicate access to mammography outside of the NBSS that reduced the apparent survival benefit for clinical trial mammography.

Automatic segmentation of mammographic density.

RATIONALE AND OBJECTIVES: The purpose of this study was to evaluate a completely automatic method, based on Kittler's optimal threshold, to estimate breast density by using the mammographers' definition. MATERIALS AND METHODS: Thirty-two normal, right-craniocaudal-view mammograms of women aged 37-86 years were digitized. The whole breast area was segmented by using Kittler's optimal threshold procedure, and the dense portions were then segmented by using a modified version of Kittler's method. Segmentation results were validated by three independent mammographers who provided a signed percentage (in steps of 5%) to indicate the difference between their own visual estimation of the dense portions and the results obtained with the algorithm. The difference between the algorithm measurements and the mammographers' measurements was compared to the interobserver differences. RESULTS: A high correlation was found between the algorithm measured density and the mammographers' measurements. Spearman correlations ranged from 0.92 to 0.95 (P < .001). Algorithm-measured density differed from the mammographers' measurements by an average of 6.9% (ie, average of the absolute differences). In contrast, mammographers' measurements differed between themselves by an average of 5.4%. CONCLUSION: The difference between density as measured with the algorithm and as measured by the mammographers is similar to the differences observed between mammographers. This algorithm could be useful in providing clinically accurate estimates of breast density.

Comparing the performance of mammographic enhancement algorithms: a preference study.

OBJECTIVE: The objective of this study was to compare the performance of four image enhancement algorithms on secondarily digitized (i.e., digitized from film) mammograms containing masses and microcalcifications of known pathology in a clinical soft-copy display setting. MATERIALS AND METHODS: Four different image processing algorithms (adaptive unsharp masking, contrast-limited adaptive histogram equalization, adaptive neighborhood contrast enhancement, and wavelet-based enhancement) were applied to one image of secondarily digitized mammograms of forty cases (10 each of benign and malignant masses and 10 each of benign and malignant microcalcifications). The four enhanced images and the one unenhanced image were displayed randomly across three high-resolution monitors. Four expert mammographers ranked the unenhanced and the four enhanced images from 1 (best) to 5 (worst). RESULTS: For microcalcifications, the adaptive neighborhood contrast enhancement algorithm was the most preferred in 49% of the interpretations, the wavelet-based enhancement in 28%, and the unenhanced image in 13%. For masses, the unenhanced image was the most preferred in 58% of cases, followed by the unsharp masking algorithm (28%). CONCLUSION: Appropriate image enhancement improves the visibility of microcalcifications. Among the different algorithms, the adaptive neighborhood contrast enhancement algorithm was preferred most often. For masses, no significant improvement was observed with any of these image processing approaches compared with the unenhanced image. Different image processing approaches may need to be used, depending on the type of lesion. This study has implications for the practice of digital mammography.

Detection of breast cancer at a smaller size can reduce the likelihood of metastatic spread: a quantitative analysis.

RATIONALE AND OBJECTIVES: The authors extrapolated the lognormal relationship between size of tumor and probability of metastasis to include small tumors. METHODS: Extrapolation was performed by using linear weighted regression analysis techniques to estimate prediction intervals for the predicted probabilities. RESULTS: Tumors detected at 1 cm in diameter had a 7.31% probability of metastasis (95% prediction interval [PI], 4.36% to 11.6%). Tumors detected at 5 mm in diameter had a 1.23% probability of metastasis (95% PI, 0.45% to 3.0%). Tumors detected at 2 mm had a 0.049% probability of metastasis (95% PI, 0.00705% to 0.267%). CONCLUSION: This analysis shows a major reduction in metastasis probability when tumors are detected at small sizes. These results suggest that detection of very early tumors can substantially reduce the likelihood of metastatic spread.

Separation of image parts using 2-D parallel form recursive filters.

This correspondence deals with a new technique to separate objects or image parts in a composite image. A parallel form extension of a 2-D Steiglitz-McBride method is applied to the discrete cosine transform (DCT) of the image containing the objects that are to be separated. The obtained parallel form is the sum of several filters or systems, where the impulse response of each filter corresponds to the DCT of one object in the original image. Preliminary results on an image with two objects show that the algorithm works well, even in the case where one object occludes another as well as in the case of moderate noise.