Enhanced diagnostic accuracy for quantitative bone scan using an artificial neural network system: A Japanese multi-center database project

Background Artificial neural network (ANN)-based bone scan index (BSI), a marker of the amount of bone metastasis, has been shown to enhance diagnostic accuracy and reproducibility but is potentially affected by training databases. The aims of this study were to revise the software using a large number of Japanese databases and to validate its diagnostic accuracy compared with the original Swedish training database. Methods The BSI was calculated with EXINIbone (EB; EXINI Diagnostics) using the Swedish training database (n = 789). The software using Japanese training databases from a single institution (BONENAVI version 1, BN1, n = 904) and the revised version from nine institutions (version 2, BN2, n = 1,532) were compared. The diagnostic accuracy was validated with another 503 multi-center bone scans including patients with prostate (n = 207), breast (n = 166), and other cancer types. The ANN value (probability of abnormality) and BSI were calculated. Receiver operating characteristic (ROC) and net reclassification improvement (NRI) analyses were performed. Results The ROC analysis based on the ANN value showed significant improvement from EB to BN1 and BN2. In men (n = 296), the area under the curve (AUC) was 0.877 for EB, 0.912 for BN1 (p = not significant (ns) vs. EB) and 0.934 for BN2 (p = 0.007 vs. EB). In women (n = 207), the AUC was 0.831 for EB, 0.910 for BN1 (p = 0.016 vs. EB), and 0.932 for BN2 (p < 0.0001 vs. EB). The optimum sensitivity and specificity based on BN2 was 90% and 84% for men and 93% and 85% for women. In patients with prostate cancer, the AUC was equally high with EB, BN1, and BN2 (0.939, 0.949, and 0.957, p = ns). In patients with breast cancer, the AUC was improved from EB (0.847) to BN1 (0.910, p = ns) and BN2 (0.924, p = 0.039). The NRI using ANN between EB and BN1 was 17.7% (p = 0.0042), and that between EB and BN2 was 29.6% (p < 0.0001). With respect to BSI, the NRI analysis showed downward reclassification with total NRI of 31.9% (p < 0.0001). Conclusion In the software for calculating BSI, the multi-institutional database significantly improved identification of bone metastasis compared with the original database, indicating the importance of a sufficient number of training databases including various types of cancers. © 2013 Nakajima et al

Identification of 45 New Neutron-Rich Isotopes Produced by In-Flight Fission of a 238U Beam at 345 MeV/nucleon

A search for new isotopes using in-flight fission of a 345 MeV/nucleon 238U beam has been carried out at the RI Beam Factory at the RIKEN Nishina Center. Fission fragments were analyzed and identified by using the superconducting in-flight separator BigRIPS. We observed 45 new neutron-rich isotopes: 71Mn, 73,74Fe, 76Co, 79Ni, 81,82Cu, 84,85Zn, 87Ga, 90Ge, 95Se, 98Br, 101Kr, 103Rb, 106,107Sr, 108,109Y, 111,112Zr, 114,115Nb, 115,116,117Mo, 119,120Tc, 121,122,123,124Ru, 123,124,125,126Rh, 127,128Pd, 133Cd, 138Sn, 140Sb, 143Te, 145I, 148Xe, and 152Ba

Reduced Myocardial Flow Reserve in Non–Insulin-Dependent Diabetes Mellitus

AbstractObjectives. We analyzed myocardial flow reserve (MFR) in patients with non–insulin-dependent (type II) diabetes mellitus (NIDDM) without symptoms and signs of ischemia.Background. Diminished MFR in diabetes has been suggested. However, it remains controversial whether MFR is related to glycemic control, mode of therapy or gender in NIDDM.Methods. Myocardial blood flow (MBF) was measured at baseline and during dipyridamole loading in 25 asymptomatic, normotensive, normocholesterolemic patients with NIDDM and 12 age-matched control subjects by means of positron emission tomography and nitrogen-13 ammonia, after which MFR was calculated.Results. Baseline MBF in patients with NIDDM ([mean ± SD] 74.0 ± 24.0 ml/min per 100 g body weight) was comparable to that in control subjects (73.0 ± 17.0 ml/min per 100 g). However, MBF during dipyridamole loading was significantly lower in patients with NIDDM (184 ± 99.0 ml/min per 100 g, p < 0.01) than in control subjects (262 ± 120 ml/min per 100 g), as was MFR (NIDDM: 2.77 ± 0.85; control subjects: 3.8 ± 1.0, p < 0.01). A significantly decreased MFR was seen in men (2.35 ± 0.84) compared with women with NIDDM (3.18 ± 0.79, p < 0.05); however, no significant differences were found in terms of age, hemoglobin a1c and baseline MBF. MFR was comparable between the diet (2.78 ± 0.80) and medication therapy groups (2.76 ± 0.77) and was inversely correlated with average hemoglobin A1c for 5 years (r = −0.55, p < 0.01) and fasting plasma glucose concentration (r = −0.57, p < 0.01) but not age or lipid fractions.Conclusions. Glycemic control and gender, rather than mode of therapy, is related to MFR in NIDDM