Estimating kidney depth among Filipino adults using Tonnesen, Taylor, and Inoue algorithms

Nuclear medicine departments use the camera-based method for determining glomerular filtration rate (GFR) with 99mTc-DPTA. Camera based techniques provide a fast and convenient way of determining GFR with excellent reproducubility however its accuracy remains in question. The accuracy of camera-based renal scintigraphy depends on an attenuation correlation from estimating for renal depth and an attenuation correction from estimating for renal depth and an attenuation coefficient. Algorithms were formulated by Tonnesen, Taylor, and Inoue to calculate the estimated renal depth through multiple stepwise linear regression analysis. The goal of this study was to analyze the accuracy of these algorithms in Filipino patients. Renal depth was determined from CT scans of 41 consecutive patients. We calculated the mean absolute error of the estimated kidney depths and compared them with each other to determine the accuracy of each algorithm. The Tonnesen algorithm had the highest mean absolute error of 1.25 cm plus minus 0.88 cm in the left kidney estimates while the Taylor algorithm had the lowest mean absolute error of 0.81 cm plus minus 0.58 cm in the left kidney estimate and 1.04 cm plus minus 0.82 cm in the right kidney estimate (p-value = 0.01 left kidney estimates and p-value = 0.02 right kidney estimates). The Tonnesen algorithm was the least accurate in predicting kidney depth. There was no significant difference between the Taylor and Inoue algorithms, which were more accurate in predicting kidney depth

Diagnostic accuracy of breast specific gamma imaging in the detection of breast cancer in high risk women: A meta-analysis

Mammography remains the mainstay of screening for primary breast cancer, however, some limitations persists in women with dense breast, in its inability to differentiate a benign from a malignant lesion, and in its heavy reliance on the radiologists' skill. Breast specific gamma imaging, which evaluates the functional images rather than anatomic images seen in mammography, addresses these limitations and can be a potential adjunct in screening for breast cancer. This meta-analysis aims to determine the diagnostic accuracy of breast specific gamma imaging for diagnosing breast cancer in women who are high risk. We searched PUBMED (1999-2009) and Google Scholar (1999-2009) for diagnostic accuracy studies that compared breast specific gamma imaging with histopathologic diagnosis of breast cancer in high risk women. Citation searches and screening of references of included studies were conducted. Two authors searched citations that correlated with the criteria using a data collection form. The methodological quality was then assessed by three authors using the QUADAS method. HSROC meta-analytical tool was used to estimate summary ROC curves. Four studies with 360 participants and 411 lesions were included. Breast specific gamma imaging has a high sensitivity (84%-97%) and specificity (60%-86%). SROC shows the included studies have high overall accuracy. Breast specific gamma imaging has high diagnostic accuracy in detecting breast cancer in women at high risk.