Efficacy of radioactive iodine treatment of graves’ hyperthyroidism using a single calculated 131I dose

Abstract Objective To evaluate the success rate of therapeutic administration of a single calculated 131I activity for eliminating hyperthyroidism due to Graves’ disease. Methods and materials Patients with Graves’ hyperthyroidism underwent pinhole thyroid imaging, 24-h radioactive iodine uptake (RAIU) measurements and clinical examination and received a calculated 131I activity of 0.2 mCi per estimated gram of thyroid tissue, adjusted for the 24-h RAIU. The goal of RAI treatment was to achieve hypothyroidism within 3–6 months of 131I administration. Response to RAI therapy was assessed at 7 weeks and 3 months by clinical and biochemical follow-up. Results The study included 316 hyperthyroid patients with Graves’ disease (F238:M78, mean age 42.1 ± 16 y, 4–94). 179 patients (56.6%) had no prior therapeutic intervention (treatment-naive patients), whereas 6 patients had prior thyroid surgery, and 131 (41.5%) had been treated with anti-thyroid medications. The mean estimated thyroid gland size was 50.2 g ± 18, range 15–100. Mean RAIU was 0.57 ± 0.17 (normal 0.07–0.30). RAI doses ranged from 5 to 70 mCi (mean dose = 18.1 mCi). Successful treatment of hyperthyroidism at our institution was obtained after a single therapeutic 131-I activity administration in 295 of 316 (93.3%) patients. Multivariate logistic regression analysis demonstrated that failure of 131I therapy was associated with previous PTU therapy (p <  0.001). The mean response time after successful RAI therapy was 110.2 days, with cumulative response of 25% at 61 days, 50% by 84 days and 75% by 118 days after radioiodine administration. The mean time to respond for those on prior PTU medications was 297 days compared to 116 days for those on MMI and 109 days for those not previously treated with antithyroid medications. In patients with persistent hyperthyroidism, failure of RAI therapy was documented in 16 patients (76.2%) within (less than) one year after 131I administration and in 5 patients (23.8%) more than one year after initial therapy, considered late failure. Conclusion Successful 131I therapy for Graves’ hyperthyroidism with a single calculated dose can be achieved in the majority (> 90%) of patients, adjusting for the thyroid size and 24 h uptake measurement.https://deepblue.lib.umich.edu/bitstream/2027.42/146543/1/40842_2018_Article_71.pd

MIBG detection of hepatic neuroblastoma: Correlation with CT, US and surgical findings

Metaiodobenzylguanidine (MIBG) imaging is used in the diagnosis, staging and follow-up of virtually every case of neuroblastoma seen at our institution. Normal sites of MIBG uptake include the liver and therefore difficulties have been predicted and encountered in the diagnosis of hepatic neuroblastoma due to inability to separate abnormally increased tracer deposition from normal hepatic activity. We reviewed every MIBG (I 123 and I 131 ) study performed at our pediatric hospital over a 4 year period encompassing 88 patients, 67 of whom had biopsy proven neuroblastoma. Hepatic findings on MIBG studies were compared with concurrent abdominal CT and US studies in all 67 patients. The clinical records of all patients with abnormal MIBG scans or abnormal CT or US studies of the liver were also reviewed. Eight patients were found to have abnormal liver findings on one or more imaging studies (MIBG, CT, or US). There were 3 true positive MIBG studies, one of which was an early study in a patient who later went on to have one of the false positive studies. Two patients had false positive MIBG scans for liver neuroblastoma. MIBG failed to detect liver involvement in 4 patients.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46701/1/247_2005_Article_BF02010914.pd

A Survey of OB / GYN Physicians' Training & Current Practice Patterns in Breast Care

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94493/1/tbj12028.pd

Double-reading mammograms using artificial intelligence technologies: A new model of mass preventive examination organization

BACKGROUND: In recent years, the availability of medical datasets and technologies for software development based on artificial intelligence technology has resulted in a growth in the number of solutions for medical diagnostics, particularly mammography. Registered as a medical device, this program can interpret digital mammography, significantly saving time, material, and human resources in healthcare while ensuring the quality of mammary gland preventive studies. AIM: This study aims to justify the possibility and effectiveness of artificial intelligence-based software for the first interpretation of digital mammograms while maintaining the practice of a radiologists second description of X-ray images. MATERIALS AND METHODS: A dataset of 100 digital mammography studies (50 absence of target pathology and 50 ― presence of target pathology, with signs of malignant neoplasms) was processed by software based on artificial intelligence technology that was registered as a medical device in the Russian Federation. Receiver operating characteristic analysis was performed. Limitations of the study include the values of diagnostic accuracy metrics obtained for software based on artificial intelligence technology versions, relevant at the end of 2022. RESULTS: When set to 80.0% sensitivity, artificial intelligence specificity was 90.0% (95% CI, 81.798.3), and accuracy was 85.0% (95% CI, 78.092.0). When set to 100% specificity, artificial intelligence demonstrated 56.0% sensitivity (95% CI, 42.269.8) and 78.0% accuracy (95% CI, 69.986.1). When the sensitivity was set to 100%, the artificial intelligence specificity was 54.0% (95% CI, 40.267.8), and the accuracy was 77.0% (95% CI, 68.885.2). Two approaches have been proposed, providing an autonomous first interpretation of digital mammography using artificial intelligence. The first approach is to evaluate the X-ray image using artificial intelligence with a higher sensitivity than that of the double-reading mammogram by radiologists, with a comparable level of specificity. The second approach implies that artificial intelligence-based software will determine the mammogram category (absence of target pathology or presence of target pathology), indicating the degree of confidence in the obtained result, depending on the corridor into which the predicted value falls. CONCLUSIONS: Both proposed approaches for using artificial intelligence-based software for the autonomous first interpretation of digital mammograms can provide diagnostic quality comparable to, if not superior to, double-image reading by radiologists. The economic benefit from the practical implementation of this approach nationwide can range from 0.6 to 5.5 billion rubles annually

Measuring co-authorship and networking-adjusted scientific impact

Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I1 for a single scientist as the number of authors who appear in at least I1 papers of the specific scientist. For a group of scientists or institution, In is defined as the number of authors who appear in at least In papers that bear the affiliation of the group or institution. I1 depends on the number of papers authored Np. The power exponent R of the relationship between I1 and Np categorizes scientists as solitary (R>2.5), nuclear (R=2.25-2.5), networked (R=2-2.25), extensively networked (R=1.75-2) or collaborators (R<1.75). R may be used to adjust for co-authorship networking the citation impact of a scientist. In similarly provides a simple measure of the effective networking size to adjust the citation impact of groups or institutions. Empirical data are provided for single scientists and institutions for the proposed metrics. Cautious adoption of adjustments for co-authorship and networking in scientific appraisals may offer incentives for more accountable co-authorship behaviour in published articles.Comment: 25 pages, 5 figure

Joint EANM/SIOPE/RAPNO practice guidelines/SNMMI procedure standards for imaging of paediatric gliomas using PET with radiolabelled amino acids and [¹⁸F]FDG: version 1.0

Positron emission tomography (PET) has been widely used in paediatric oncology. 2-Deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) is the most commonly used radiopharmaceutical for PET imaging. For oncological brain imaging, different amino acid PET radiopharmaceuticals have been introduced in the last years. The purpose of this document is to provide imaging specialists and clinicians guidelines for indication, acquisition, and interpretation of [18F]FDG and radiolabelled amino acid PET in paediatric patients affected by brain gliomas. There is no high level of evidence for all recommendations suggested in this paper. These recommendations represent instead the consensus opinion of experienced leaders in the field. Further studies are needed to reach evidence-based recommendations for the applications of [18F]FDG and radiolabelled amino acid PET in paediatric neuro-oncology. These recommendations are not intended to be a substitute for national and international legal or regulatory provisions and should be considered in the context of good practice in nuclear medicine. The present guidelines/standards were developed collaboratively by the EANM and SNMMI with the European Society for Paediatric Oncology (SIOPE) Brain Tumour Group and the Response Assessment in Paediatric Neuro-Oncology (RAPNO) working group. They summarize also the views of the Neuroimaging and Oncology and Theranostics Committees of the EANM and reflect recommendations for which the EANM and other societies cannot be held responsible

Criteria for evaluation of disease extent by 123I-metaiodobenzylguanidine scans in neuroblastoma: a report for the International Neuroblastoma Risk Group (INRG) Task Force

BackgroundNeuroblastoma is an embryonic tumour of the sympathetic nervous system, metastatic in half of the patients at diagnosis, with a high preponderance of osteomedullary disease, making accurate evaluation of metastatic sites and response to therapy challenging. Metaiodobenzylguanidine (mIBG), taken into cells via the norepinephrine transporter, provides a sensitive and specific method of assessing tumour in both soft tissue and bone sites. The goal of this report was to develop consensus guidelines for the use of mIBG scans in staging, response assessment and surveillance in neuroblastoma.MethodsThe International Neuroblastoma Risk Group (INRG) Task Force, including a multidisciplinary group in paediatric oncology of North and South America, Europe, Oceania and Asia, formed a subcommittee on metastatic disease evaluation, including expert nuclear medicine physicians and oncologists, who developed these guidelines based on their experience and the medical literature, with approval by the larger INRG Task Force.ResultsGuidelines for patient preparation, radiotracer administration, techniques of scanning including timing, energy, specific views, and use of single photon emission computed tomography are included. Optimal timing of scans in relation to therapy and for surveillance is reviewed. Validated semi-quantitative scoring methods in current use are reviewed, with recommendations for use in prognosis and response evaluation.ConclusionsMetaiodobenzylguanidine scans are the most sensitive and specific method of staging and response evaluation in neuroblastoma, particularly when used with a semi-quantitative scoring method. Use of the optimal techniques for mIBG in staging and response, including a semi-quantitative score, is essential for evaluation of the efficacy of new therapy

Early In-Hospital Mortality following Trainee Doctors' First Day at Work

BACKGROUND:There is a commonly held assumption that early August is an unsafe period to be admitted to hospital in England, as newly qualified doctors start work in NHS hospitals on the first Wednesday of August. We investigate whether in-hospital mortality is higher in the week following the first Wednesday in August than in the previous week. METHODOLOGY:A retrospective study in England using administrative hospital admissions data. Two retrospective cohorts of all emergency patients admitted on the last Wednesday in July and the first Wednesday in August for 2000 to 2008, each followed up for one week. PRINCIPAL FINDINGS:The odds of death for patients admitted on the first Wednesday in August was 6% higher (OR 1.06, 95% CI 1.00 to 1.15, p=0.05) after controlling for year, gender, age, socio-economic deprivation and co-morbidity. When subdivided into medical, surgical and neoplasm admissions, medical admissions admitted on the first Wednesday in August had an 8% (OR 1.08, 95% CI 1.01 to 1.16, p=0.03) higher odds of death. In 2007 and 2008, when the system for junior doctors' job applications changed, patients admitted on Wednesday August 1(st) had 8% higher adjusted odds of death than those admitted the previous Wednesday, but this was not statistically significant (OR 1.08, 95% CI 0.95 to 1.23, p=0.24). CONCLUSIONS:We found evidence that patients admitted on the first Wednesday in August have a higher early death rate in English hospitals compared with patients admitted on the previous Wednesday. This was higher for patients admitted with a medical primary diagnosis

Who is teaching and supervising our junior residents' central venous catheterizations?

Article deposited according to agreement with BMC, December 6, 2010.YesFunding provided by the Open Access Authors Fund

A July Spike in Fatal Medication Errors: A Possible Effect of New Medical Residents

residencies and acquire increased responsibility for patient care. Many have suggested that these new medical residents may produce errors and worsen patient outcomes—the so-called “July Effect; ” however, we have found no U.S. evidence documenting this effect. OBJECTIVE: Determine whether fatal medication errors spike in July