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1.
Ann Nucl Med ; 33(5): 344-350, 2019 May.
Article in English | MEDLINE | ID: mdl-30746599

ABSTRACT

BACKGROUND: 68 Ga-PSMA-PET has an increasing importance in the evaluation of prostate cancer patients due to its high sensitivity and specificity in identifying neoplastic lesions in the clinical setting of elevated prostate-specific antigen (PSA). The objective of this study was to calculate the whole-body tumor burden using volumetric quantification of lesions detected in 68Ga-PSMA-PET of prostate cancer patients with biochemical recurrence and correlate these findings with clinical and image parameters. METHODS: Each patient had their 68Ga-PSMA-PET analyzed for the presence of neoplastic lesions. Their PSA levels and clinical information were recorded. In positive cases, the tumor burden (TL-PSMA) was calculated with a semi-automatic software and manually, and the results are analyzed and tested. RESULTS: We analyzed 100 prostate cancer patients, mean age of 69.9 ± 9.7 years and a median PSA of 1.73 ng/dL. 68Ga-PSMA-PET identified neoplastic lesions in 72% of them. The median TL-PSMA was 55.95 ml (1.1-28,080 ml). TL-PSMA and PSA were strongly correlated (rho = 0.71, p < 0.0001, 95% CI 0.60-0.80). TL-PSMA and PSA levels groups had a significant correlation and TL-PSMA and Gleason score were independent variables associated with PSA levels (p < 0.05). CONCLUSION: TL-PSMA strongly and independently correlates with PSA levels in prostate cancer patients and could be used as a biomarker to separate them into groups with high or low tumor burden, instead of considering only the number of lesions.


Subject(s)
Edetic Acid/analogs & derivatives , Oligopeptides , Positron Emission Tomography Computed Tomography , Prostatic Neoplasms/diagnostic imaging , Prostatic Neoplasms/pathology , Tumor Burden , Adult , Aged , Aged, 80 and over , Gallium Isotopes , Gallium Radioisotopes , Humans , Image Processing, Computer-Assisted , Male , Middle Aged , Prostatic Neoplasms/metabolism , Recurrence , Retrospective Studies
2.
Transplant Proc ; 43(4): 1351-6, 2011 May.
Article in English | MEDLINE | ID: mdl-21620127

ABSTRACT

BACKGROUND: In the future, an increasing number of female liver transplant recipients will reach the climacteric with osteoporosis as a common complication. We evaluated the factors associated with decreased bone mass among women after liver transplantation. METHODS: A prospective, cross-sectional study of 23 outpatient transplant recipients followed from February 2009 to March 2010 included women of age ≥35 years after liver transplantations ≥1 year prior. We recorded patient histories, liver enzyme levels, as well as bone mineral densities measured at the lumbar spine and femur. Statistical analysis used Fisher's exact test, simple odds ratio (OR), and Spearman's rank correlation coefficient. RESULTS: The mean patient age was 52.5 ± 11 years with 30.4% premenopausal, and 69.6% perimenopausal or postmenopausal. Approximately 21% showed osteoporosis and 35%, a low bone mass. Postmenopausal women: OR 69.0 (95% CI 2.89-1647.18; P<.0001), aged ≥49 years: OR 13.33 (95% CI 1.78-100.15; P=.0123) and receiving a transplant after 44 years of age: OR 49.50 (95% CI 3.84-638.43; P<.0001) were associated with a lower bone mass. Having undergone transplantation for more than 5.8 years lowered the risk of bone mass change: OR 0.11 (95% CI 0.02-0.78; P=.0361). Clinical and laboratory variables, including corticosteroid use, were not associated with decreased bone mass. CONCLUSION: Understanding the prevalence and factors associated with osteoporosis among female liver transplant recipients is important to enhance the strategies to diagnose and treat these women, seeking to improve their quality of life.


Subject(s)
Bone Density , Femur/pathology , Liver Transplantation/adverse effects , Lumbar Vertebrae/pathology , Osteoporosis/etiology , Absorptiometry, Photon , Adult , Age Factors , Aged , Brazil , Cross-Sectional Studies , Female , Humans , Middle Aged , Odds Ratio , Osteoporosis/pathology , Prospective Studies , Risk Assessment , Risk Factors , Time Factors , Treatment Outcome
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