Volumetric analysis of lung nodules in computed tomography (CT): comparison of two different segmentation algorithm softwares and two different reconstruction filters on automated volume calculation.

BACKGROUND A precise detection of volume change allows for better estimating the biological behavior of the lung nodules. Postprocessing tools with automated detection, segmentation, and volumetric analysis of lung nodules may expedite radiological processes and give additional confidence to the radiologists. PURPOSE To compare two different postprocessing software algorithms (LMS Lung, Median Technologies; LungCARE®, Siemens) in CT volumetric measurement and to analyze the effect of soft (B30) and hard reconstruction filter (B70) on automated volume measurement. MATERIAL AND METHODS Between January 2010 and April 2010, 45 patients with a total of 113 pulmonary nodules were included. The CT exam was performed on a 64-row multidetector CT scanner (Somatom Sensation, Siemens, Erlangen, Germany) with the following parameters: collimation, 24x1.2 mm; pitch, 1.15; voltage, 120 kVp; reference tube current-time, 100 mAs. Automated volumetric measurement of each lung nodule was performed with the two different postprocessing algorithms based on two reconstruction filters (B30 and B70). The average relative volume measurement difference (VME%) and the limits of agreement between two methods were used for comparison. RESULTS At soft reconstruction filters the LMS system produced mean nodule volumes that were 34.1% (P < 0.0001) larger than those by LungCARE® system. The VME% was 42.2% with a limit of agreement between -53.9% and 138.4%.The volume measurement with soft filters (B30) was significantly larger than with hard filters (B70); 11.2% for LMS and 1.6% for LungCARE®, respectively (both with P < 0.05). LMS measured greater volumes with both filters, 13.6% for soft and 3.8% for hard filters, respectively (P < 0.01 and P > 0.05). CONCLUSION There is a substantial inter-software (LMS/LungCARE®) as well as intra-software variability (B30/B70) in lung nodule volume measurement; therefore, it is mandatory to use the same equipment with the same reconstruction filter for the follow-up of lung nodule volume.

Hormonal and Clinical Predictors for Post-egg Retrieval Pain in Women Undergoing Assisted Reproductive Technology Procedures

OBJECTIVES The intensity of post-egg retrieval pain is underestimated, with few studies examining post-procedural pain and predictors to identify women at risk for severe pain. We evaluated the influence of pre-procedural hormonal levels, ovarian factors, as well as mechanical temporal summation (mTS) as predictors for post-egg retrieval pain in women undergoing in vitro fertilization (IVF). METHODS Eighteen women scheduled for ultrasound-guided egg retrieval under standardized anesthesia and post-procedural analgesia were enrolled. Pre-procedural mTS, questionnaires, clinical data related to anesthesia and the procedure itself, post-procedural pain scores and pain medication for breakthrough pain were recorded. Statistical analysis included Pearson product moment correlations, Mann-Whitney U tests and multiple linear regressions. RESULTS Average peak post-egg retrieval pain during the first 24 hours was 5.0±1.6 on an NRS scale (0=no pain, 10=worst pain imaginable). Peak post-egg retrieval pain was correlated with basal antimullerian hormone (AMH) (r=0.549, P=0.018), pre-procedural peak estradiol (r=0.582, P=0.011), total number of follicles (r=0.517, P=0.028) and number of retrieved eggs (r=0.510, P=0.031). Ovarian hyperstimulation syndrome (OHSS) (n=4) was associated with higher basal AMH (P=0.004), higher peak pain scores (P=0.049), but not with peak estradiol (P=0.13). The mTS did not correlate with peak post-procedural pain (r=0.266, P=0.286), or peak estradiol level (r=0.090, P=0.899). DISCUSSION Peak post-egg retrieval pain intensity was higher than anticipated. Our results suggest that post-egg retrieval pain can be predicted by baseline AMH, high peak estradiol, and OHSS. Further studies to evaluate intra- and post-procedural pain in this population are needed, as well as clinical trials to assess post-procedural analgesia in women presenting with high hormonal levels.

Segmentation and Segregation Patterns of Women-Owned High-Tech Firms in Four Metropolitan Regions in the United States

Mayer H. Segmentation and segregation patterns of women-owned high-tech firms in four metropolitan regions in the United States, Regional Studies. The number of women starting and owning a business has increased dramatically and female entrepreneurs are entering non-traditional sectors such as high technology, construction and manufacturing. This paper investigates the trends in high-tech entrepreneurship by women in four US metropolitan regions (Silicon Valley, California; Boston, Massachusetts; Washington, DC; and Portland, Oregon). The research examines the sectoral and spatial segmentation patterns of women-owned high-tech firms. Although women are entering non-traditional sectors, the research finds that women entrepreneurs tend to own businesses in female-typed high-tech sectors. In established high-tech regions like Silicon Valley and Boston, male-typed and female-typed women-owned high-tech firms differ significantly in terms of sectoral and spatial segmentation regardless of firm age. While differences between male-typed and female-typed firms are not significant at the regional level for Washington, DC, the analysis shows significant intra-metropolitan differences for the female-typed high-tech firms. The paper concludes that sectoral and spatial segmentation are powerful dynamics that shape business ownership by women in high technology.