Decision Tree With Only Two Musculoskeletal Sites to Diagnose Polymyalgia Rheumatica Using [18F]FDG PET-CT.

Introduction: The aim of this study was to find the best ordered combination of two FDG positive musculoskeletal sites with a machine learning algorithm to diagnose polymyalgia rheumatica (PMR) vs. other rheumatisms in a cohort of patients with inflammatory rheumatisms. Methods: This retrospective study included 140 patients who underwent [18F]FDG PET-CT and whose final diagnosis was inflammatory rheumatism. The cohort was randomized, stratified on the final diagnosis into a training and a validation cohort. FDG uptake of 17 musculoskeletal sites was evaluated visually and set positive if uptake was at least equal to that of the liver. A decision tree classifier was trained and validated to find the best combination of two positives sites to diagnose PMR. Diagnosis performances were measured first, for each musculoskeletal site, secondly for combination of two positive sites and thirdly using the decision tree created with machine learning. Results: 55 patients with PMR and 85 patients with other inflammatory rheumatisms were included. Musculoskeletal sites, used either individually or in combination of two, were highly imbalanced to diagnose PMR with a high specificity and a low sensitivity. The machine learning algorithm identified an optimal ordered combination of two sites to diagnose PMR. This required a positive interspinous bursa or, if negative, a positive trochanteric bursa. Following the decision tree, sensitivity and specificity to diagnose PMR were respectively 73.2 and 87.5% in the training cohort and 78.6 and 80.1% in the validation cohort. Conclusion: Ordered combination of two visually positive sites leads to PMR diagnosis with an accurate sensitivity and specificity vs. other rheumatisms in a large cohort of patients with inflammatory rheumatisms.

Internal dosimetry of [99m Tc]NTP15-5 radiotracer for cartilage imaging in preclinical and clinical models using the GATE Monte Carlo platform.

PURPOSE: This study aims to perform dosimetry for [99m Tc]NTP15-5 radiotracer used in imaging of articular cartilage in rabbits and humans. The radiotracer (covered by a world patent WO 01/00621 A1) has been proposed in the previous years for the study of cartilage in osteoarthritis diseases. A sensitive imaging approach is essential to quantify osteoarthritis progression and monitor response to new therapies. [99m Tc]NTP15-5 binds to cartilage proteoglycans whose decreased content is associated to a loss of biomedical function of cartilage. We have implemented the whole dosimetry study concerning this new radiotracer for rabbits and humans using the GATE Monte Carlo platform. MATERIALS AND METHODS: Absorbed doses to critical organs are determined using the MIRD formalism. Biodistribution data are obtained by organ sampling, measuring the activity in organs for three rabbits sacrificed at various times postadministration, and by SPECT/CT imaging at different times after injection. Most important sources are cartilages (in knees and intervertebral discs), due to localization together with the liver and kidneys due to excretion of the agent. S-values are calculated from rabbit's CT scan and human CT scan using the GATE v8.0 Monte Carlo platform. Cumulated activity in humans is extrapolated from animals using the %kg-dose/g method. Particular attention is given to dose calculation in bones, bone marrow and organs at risk. RESULTS: The dosimetry performed in rabbits shows highest absorbed doses for liver and kidneys with respectively 22.5 and 43.8 µGy per MBq of injected activity. In humans, we found absorbed doses for a maximum injected activity of 15 MBq/kg, that is, 1050 MBq for an adult of 70 kgs of 9.03 mGy for kidneys and 4.16 mGy for knee cartilages. Effective dose is 2.69 µSv/MBq. CONCLUSIONS: The dosimetry profile of [99m Tc]NTP15-5 in the context of preclinical trials is of major importance in order to make sure that organs at risk are not overexposed. GATE provides all the capability needed to calculate dose profiles for internal dosimetry. The extrapolation of the dose for a human model is a first step towards clinical trials.

Utility of 18F-Fluorodeoxyglucose Positron Emission Tomography in Inflammatory Rheumatism, Particularly Polymyalgia Rheumatica: A Retrospective Study of 222 PET/CT.

Purpose: The objective of this study was to evaluate periarticular FDG uptake scores from 18F-FDG-PET/CT to identify polymyalgia rheumatica (PMR) within a population presenting rheumatic diseases. Methods: A French retrospective study from 2011 to 2015 was conducted. Patients who underwent 18F-FDG-PET/CT for diagnosis or follow-up of a rheumatism or an unexplained biological inflammatory syndrome were included. Clinical data and final diagnosis were reviewed. Seventeen periarticular sites were sorted by a visual reading enabling us to calculate two scores: mean FDG visual uptake score, number of sites with significant uptake same as that or higher than liver uptake intensity and by a semi-quantitative analysis using mean maximum standardized uptake value (SUVmax). Optimal cutoffs of visual score and SUVmax to diagnose PMR were determined using receiver operating characteristics curves. Results: Among 222 18F-FDG PET/CT selected for 215 patients, 161 18F-FDG PET/CT were performed in patients who presented inflammatory rheumatism as a final diagnosis (of whom 57 PMR). The presence of at least three sites with significant uptake identified PMR with a sensitivity of 86% and a specificity of 85.5% (AUC 0.872, 95% CI [0.81-0.93]). The mean FDG visual score cutoff to diagnose a PMR was 0.765 with a sensitivity of 82.5% and a specificity of 75.8% (AUC 0.854; 95% CI [0.80-0.91]). The mean SUVmax cutoff to diagnose PMR was 2.168 with a sensitivity of 77.2% and a specificity of 77.6% (AUC 0.842; 95% CI [0.79-0.89]). Conclusions: This study suggests that 18F-FDG PET/CT had good performances to identify PMR within a population presenting rheumatic diseases.

Age, thyroglobulin levels and ATA risk stratification predict 10-year survival rate of differentiated thyroid cancer patients.

INTRODUCTION: Differentiated thyroid cancer (DTC) is the most common of endocrine cancers. Many studies have focused on recurrence-free survival of DTC patients, however, few studies have addressed overall survival rates. Given its very good prognosis, estimating overall or long-term survival in patients with DTC seems rational. So far, neither the impact of pre- and post-ablation thyroglobulin, nor that of initial American Thyroid Association (ATA) risk stratification on long-term disease-specific survival, have been sufficiently studied. OBJECTIVE: The aim of this study was to determine the factors that influence long-term disease-specific survival and thyroglobulin levels in patients with DTC who have been previously treated with thyroidectomy and radioactive iodine (RAI) remnant ablation. PATIENTS AND METHODS: This observational retrospective study included 1093 patients who were treated for DTC between 1995 and 2010 and are still monitored in our tertiary center. Only patients who needed RAI ablation after thyroidectomy were included in this study. Patients who were treated with RAI following rhTSH stimulation, patients who presented positive anti-thyroglobulin antibodies, and patients who had micro-cancers were excluded. Pre-ablation stimulated thyroglobulin (Pre-ablation sTg) was measured after thyroid hormone withdrawal (THW), just before RAI. RESULTS: According to ATA standards, 29 patients (2.7%) were classified as high-risk patients. Initial ATA high-recurrence risk rating (HR 21.9; 95% CI: 8.5-56.3), age>55 years (HR 23.8; 95%-CI: 7.5-75.3) and pre-ablation sTg≥30 µg/l (HR 8.4; 95% CI: 4.6-15.3) significantly impacted ten-year survival. Moreover, age over 45 years, ATA moderate-risk and follicular DTC were also significant. Ten-year survival was lower in ATA high-risk patients (51% vs 95% and 93% for the low and intermediate risk; p<10-7), patients older than 55 years (82% vs 98%; p<10-7), and in patients with pre-ablation sTg≥30 (78% vs 95%; p<10-7). Three rates of long-term survival were distinguished: excellent (survival rate of 99% in patients<55 years with pre-ablation sTg <30µg/l) representing 59% of the cohort, moderate (survival rate of 94.5% in patients <55 years with pre-ablation sTg ≥30µg/l or ≥55 years with pre-ablation sTg <30 µg/l) representing 38% of the cohort, and low (survival rate of 49% in patients ≥55 years with pre-ablation sTg ≥30µg/l) representing 3% of the cohort. CONCLUSION: Initial ATA high-risk classification, age over 55 years old and pre-ablation sTg ≥30 µg/l are the main negative factors that influence the ten-year survival in DTC. We suggest three categories of overall survival rates. Patients older than 55 years with pre-ablation sTg ≥30 µg/l have the worst survival rate.

Radiation dosimetry of [131 I]ICF01012 in rabbits: Application to targeted radionuclide therapy for human melanoma treatment.

PURPOSE: Dosimetry for melanoma-targeted radionuclide therapy (TRT) with [131 I]ICF01012, a melanin ligand, has been previously evaluated in mice bearing melanomas. In this study, activity distribution and dosimetry are performed on healthy rabbits (Fauve de Bourgogne) using SPECT-CT imaging and ex vivo measurements. MATERIAL AND METHODS: Ex vivo biodistribution (i.v. injection: 370 kBq/kg, n = 2 per point) is performed on blood, eyes, brain, lung, liver, kidneys, heart, stomach, and spleen. Dosimetry calculations follow the MIRD formalism: S values are calculated from CT images using the GATE Monte Carlo platform and activity distributions are obtained from SPECT-CT imaging (i.v. injection: 37 MBq/kg n = 3 per point). A specific study is presented to assess dose to human retina. RESULTS: Time-integrated activities based on SPECT-CT are in accordance with ex vivo measurements except for spleen. Doses to liver and eyes are the most significant, with respectively, 6.38 ± 0.50 Gy/GBq (evaluated through SPECT-CT imaging) and 45.8 ± 7.9 Gy/GBq (evaluated through ex vivo measurements). Characterization of ocular [131 I]ICF01012 biodistribution in rabbits and quantification of melanin allowed to assess a dose of 3.07 ± 0.70 Gy/GBq to human retina. CONCLUSION: This study sustains [131 I]ICF01012 as a good candidate for melanoma TRT and open perspectives for personalized dosimetry calculation during phase I clinical transfer.

Visual versus quantitative assessment of intratumor 18F-FDG PET uptake heterogeneity: prognostic value in non-small cell lung cancer.

UNLABELLED: The goal of this study was to compare visual assessment of intratumor (18)F-FDG PET uptake distribution with a textural-features (TF) automated quantification and to establish their respective prognostic value in non-small cell lung cancer (NSCLC). METHODS: The study retrospectively included 102 consecutive patients. Only primary tumors were considered. Intratumor heterogeneity was visually scored (3-level scale [Hvisu]) by 2 nuclear medicine physicians. Tumor volumes were automatically delineated, and heterogeneity was quantified with TF. Mean and maximum standardized uptake value were also included. Visual interobserver agreement and correlations with quantitative assessment were evaluated using the κ test and Spearman rank (ρ) coefficient, respectively. Association with overall survival and recurrence-free survival was investigated using the Kaplan-Meier method and Cox regression models. RESULTS: Moderate correlations (0.4 < ρ < 0.6) between TF parameters and Hvisu were observed. Interobserver agreement for Hvisu was moderate (κ = 0.64, discrepancies in 27% of the cases). High standardized uptake value, large metabolic volumes, and high heterogeneity according to TF were associated with poorer overall survival and recurrence-free survival and remained an independent prognostic factor of overall survival with respect to clinical variables. CONCLUSION: Quantification of (18)F-FDG uptake heterogeneity in NSCLC through TF was correlated with visual assessment by experts. However, TF also constitutes an objective heterogeneity quantification, with reduced interobserver variability, and independent prognostic value potentially useful for patient stratification and management.