Background: In Graves’ disease (GD), immunocompetent cells infiltrate thyroid tissue with release of TSH-receptor antibodies (TRAb), and radioiodine treatment is known to elicit an immune response with an increase in TRAb. Objectives: The aim was to study if all patients treated with radioiodine respond with a release of TRAb, anti-thyroperoxidase (anti-TPO), and anti-thyroglobulin (anti-TG). Methods: This is a prospective observational study. GD patients (n = 131) were admitted for treatment with radioiodine. Thyroid antibodies were measured before and 3 months after iodine-131 treatment. Results: After 3 months, a fold change > 1.1 was found in 66% of the GD patients, while the remaining 34% did not have a change or decrease in in TRAb. Anti-TPO and anti-TG also increased; the former showed an increase in 73% and the latter of 52%, while 27 and 48% decreased/were unchanged. A significant positive correlation was found between TRAb and anti-TPO, but not between TRAb and anti-TG. In the group with an increase in TRAb, the median fold change was 5.1, but there were no additional effects of tobacco smoking. The proportion of females below the median age (51.5 years) was significantly higher in the group that increased in TRAb compared to the one that decreased/was unchanged (66 vs. 34%). Conclusions: Treatment with radioiodine elicits an increase in thyroid antibodies, but not in all GD patients. The proportion of responders varied and was affected by age, resulting in a stronger immune response at younger age. However, there were no additional effects of smoking.

Introduction Treatment of Graves´ disease (GD) with radioiodine increases the risk of developing Graves´ ophthalmopathy (GO), and the link between thyroid and orbital tissue may be the presence of TSH-receptors. Radioiodine increases the titers of TRAb and the aim was to investigate the relationship between GO and TRAb titers after treatment with radioiodine and to define the impact of risk genes. Methods GD patients without ophthalmopathy or previous treatment with radioiodine were prospectively included at treatment with radioiodine for hyperthyroidism. A follow-up was performed 1 year later for the registration of GO development. The study was performed at a University Hospital Clinic; a referral center of all patients treated with radioiodine in the south of Sweden. The main outcome measures were the development of TRAb, anti-TPO, and anti-TG after 3 months and GO after 12 months and relationship to the genetic background (HLA, CTLA-4, and CYR61). Results Three months of radioiodine TRAb titers increased in two thirds of patients (p < 0.0005) but not in the other third. Anti-TPO titers were associated with TRAb (R = 0.362, p < 0.0001) but not anti-TG. At follow-up 1 year later (n = 204) 32 patients developed GO with a proportion of 70% in the group increasing in TRAb titers and 30% in the group with unchanged or lower TRAb titers (p-value < 0.0005). Patients with GO had higher titers of TRAb than patients without GO. CTLA-4 (rs231775 SNP) was significantly (p < 0.005) associated with TRAb titers above the median three months after radioiodine. Conclusions The increase in TRAb titers after treatment with radioiodine is associated with GO and a genetic variation in CTLA-4 is associated with higher titers of TRAb.

Background Papillary thyroid cancer (PTC) has an excellent prognosis, and recurrence is rare in patients with no evidence of disease (NED) after initial treatment. Despite this, several guidelines recommend long and costly follow-up, with limited evidence of improved patient outcomes. This study aims to examine the value of follow-up in patients with NED after treatment for PTC, by determining the rate of recurrence, recurrence-associated morbidity, and death, and whether any recurrence was diagnosed through the follow-up programme. Methods Patients operated for PTC at Lund University Hospital between January 2004 and December 2016 were eligible. Patients with T1a N0/NX were excluded as well as patients with any other thyroid malignancy. Data were collected retrospectively by searching the patients’ medical records. NED was defined as thyroglobulin less than 1 ng/ml, thyroglobulin antibodies less than 20 kIU/l, and negative imaging. Biochemical recurrence was defined as thyroglobulin greater than 1 ng/ml, and/or thyroglobulin antibodies greater than 20 kIU/l. Structural recurrence was defined as a strong suspicion of recurrence on imaging and/or histological proof of recurrence. Results Out of a cohort of 187 patients, there were 90 patients with NED who were followed for a median of 6.3 years. Three patients had biochemical recurrence; none of them had symptoms, nor were they treated for their recurrence. Three had structural recurrence; all were above 75 years old and only one was diagnosed through the follow-up programme. No patient died of PTC; five patients died during the follow-up. Conclusion Follow-up as it is designed today cannot identify recurrences accurately and seems to be of questionable benefit in younger patients with NED after treatment for PTC.

BackgroundDosimetry in radionuclide therapy often requires the calculation of average absorbed doses within and between spatial regions, for example, for voxel‐based dosimetry methods, for paired organs, or across multiple tumors. Formation of such averages can be made in different ways, starting from different definitions.PurposeThe aim of this study is to formally specify different averaging strategies for absorbed doses, and to compare their results when applied to absorbed dose distributions that are non‐uniform within and between regions.MethodsFor averaging within regions, two definitions of the average absorbed dose are considered: the simple average over the region (the region average) and the average when weighting by the mass density (density‐weighted region average). The latter is shown to follow from the definition of mean absorbed dose according to the ICRU, and to be consistent with the MIRD formalism. For averaging between different spatial regions, three definitions follow: the volume‐weighted, the mass‐weighted, and the unweighted average. With respect to characterizing non‐uniformity, the different average definitions lead to the use of dose‐volume histograms (DVHs) (region average), dose‐mass histograms (DMHs) (density‐weighted region average), and unweighted histograms (unweighted average). Average absorbed doses are calculated for three worked examples, starting from the different definitions. The first, schematic, example concerns the calculation of the average absorbed dose between two regions with different volumes or mass densities. The second, stylized, example concerns voxel‐based dosimetry, for which the average absorbed‐dose rate within a region is calculated. The geometries studied include three 177Lu‐filled voxelized spheres, where the sphere masses are held constant while the material compositions, densities, and volumes are varied. For comparison, the mean absorbed‐dose rates obtained using unit‐density sphere S‐values are also included. The third example concerns SPECT/CT‐based tumor dosimetry for five patients undergoing therapy with 177Lu‐PSMA and six patients undergoing therapy with 177Lu‐DOTA‐TATE, for which the average absorbed‐dose rates across multiple tumors are calculated. For the second and third examples, analyses also include representations by histograms.ResultsExample 1 shows that the average absorbed doses, calculated using different definitions, can differ considerably if the masses and absorbed doses for two regions are markedly different. From example 2 it is seen that the density‐weighted region average is stable under different activity and density distributions and is also in line with results using S‐values. In contrast, the region average varies as function of the activity distribution. In example 3, the absorbed dose rates for individual tumors differ by (1.1 ± 4.3)% and (−0.1 ± 0.4)% with maximum deviations of +34.4% and −1.4% for 177Lu‐PSMA and 177Lu‐DOTA‐TATE, respectively, when calculated as region averages or density‐weighted region averages, with largest deviations obtained when the density is non‐uniform. The average absorbed doses calculated across all tumors are similar when comparing mass‐weighted and volume‐weighted averages but these differ substantially from unweighted averages.ConclusionDifferent strategies for averaging of absorbed doses within and between regions can lead to substantially different absorbed‐dose estimates. At reporting of radionuclide therapy dosimetry, it is important to specify the averaging strategy applied.

Introduction. Treatment of Graves´ disease (GD) with radioiodine increases the risk of developing Graves´ ophthalmopathy (GO) but the link between thyroid and orbital tissue remains undefined.The aim was to investigate the relationship between GO and TRAb after treatment with radioiodine and to define the impact of risk genes.Methods. GD patients without ophthalmopathy or previous treatment with radioiodine were prospectively included at treatment with radioiodine for hyperthyroidism. A follow-up was performed one year later for registration of GO development. The study was performed at a University Hospital Clinic; referral center of all patients treated with radioiodine in the south of Sweden. The main outcome measures were development of TRAb, anti-TPO, anti-TG after three months and GO after 12 months and relationship to the genetic background (HLA, CTLA-4, CYR61).Results. Three months of radioiodine TRAb increased in two thirds of patients (p<0.0005) but not in the other third. Anti-TPO was associated with TRAb (R=0.362, p <0.0001) but not anti-TG. At follow-up one year later (n=204) 32 patients developed GO with a proportion of 70% in the group increasing in TRAb and 30 % in the group with unchanged or lower TRAb (p-value <0.0005). Patients with GO had higher levels of TRAb than patients without GO. CTLA-4 (rs231775 SNP) was significantly (p<0.005) associated with TRAb levels above the median three months after radioiodine.Conclusions. The increase in TRAb after treatment with radioiodine is associated with GO and a genetic variation in CTLA-4 is associated with higher levels of TRAb.