Prostate-specific membrane antigen (PSMA)-targeted therapy with 177Lu-PSMA-617 is a therapeutic option for patients with metastatic castration-resistant prostate cancer (mCRPC). To optimize the therapy procedure, it is necessary to determine relevant parameters to define radiation protection and safety necessities. Therefore, this study aimed at estimating the ambient radiation exposure received by the patient. Moreover, the excreted activity was quantified. In total, 50 patients with mCRPC and treated with 177Lu-PSMA-617 (mean administered activity 6.3 ± 0.5 GBq) were retrospectively included in a bi-centric study. Whole-body dose rates were measured at a distance of 2 m at various time points after application of 177Lu-PSMA-617, and effective half-lives for different time points were calculated and compared. Radiation exposure to the public was approximated using the dose integral. For the estimation of the excreted activity, whole body measurements of 25 patients were performed at 7 time points. Unbound 177Lu-PSMA-617 was rapidly cleared from the body. After 4 h, approximately 50% and, after 12 h, approximately 70% of the administered activity were excreted, primarily via urine. The mean dose rates were the following: 3.6 ± 0.7 μSv/h at 2 h p. i., 1.6 ± 0.6 μSv/h at 24 h, 1.1 ± 0.5 μSv/h at 48 h, and 0.7 ± 0.4 μSv/h at 72 h. The mean effective half-life of the cohort was 40.5 ± 9.6 h (min 21.7 h; max 85.7 h). The maximum dose to individual members of the public per treatment cycle was ~ 250 ± 55 μSv when the patient was discharged from the clinic after 48 h and ~ 190 ± 36 μSv when the patient was discharged after 72 h. In terms of the radiation exposure to the public, 177Lu-PSMA is a safe option of radionuclide therapy. As usually four (sometimes more) cycles of the therapy are performed, it must be conducted in a way that ensures that applicable legal requirements can be followed. In other words, the radiation exposure to the public and the concentration of activity in wastewater must be sub-marginal. Therefore, in certain countries, hospitalization of these patients is mandatory.

Selecting a set of relevant markers to predict conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) has become a challenging task given the wealth of regional pathologic information that can be extracted from multimodal imaging data. Here, we used regularized regression approaches with an elastic net penalty for best subset selection of multiregional information from AV45-PET, FDG-PET and volumetric MRI data to predict conversion from MCI to AD. The study sample consisted of 127 MCI subjects from ADNI-2 who had a clinical follow-up between 6 and 31 months. Additional analyses assessed the effect of partial volume correction on predictive performance of AV45- and FDG-PET data. Predictor variables were highly collinear within and across imaging modalities. Penalized Cox regression yielded more parsimonious prediction models compared to unpenalized Cox regression. Within single modalities, time to conversion was best predicted by increased AV45-PET signal in posterior medial and lateral cortical regions, decreased FDG-PET signal in medial temporal and temporobasal regions, and reduced gray matter volume in medial, basal, and lateral temporal regions. Logistic regression models reached up to 72% cross-validated accuracy for prediction of conversion status, which was comparable to cross-validated accuracy of non-linear support vector machine classification. Regularized regression outperformed unpenalized stepwise regression when number of parameters approached or exceeded the number of training cases. Partial volume correction had a negative effect on the predictive performance of AV45-PET, but slightly improved the predictive value of FDG-PET data. Penalized regression yielded more parsimonious models than unpenalized stepwise regression for the integration of multiregional and multimodal imaging information. The advantage of penalized regression was particularly strong with a high number of collinear predictors.

Attenuation correction (AC) based on low-dose computed tomography (CT) could be more accurate in brain single-photon emission computed tomography (SPECT) than the widely used Chang method, and, therefore, has the potential to improve both semi-quantitative analysis and visual image interpretation. The present study evaluated CT-based AC for dopamine transporter SPECT with I-123-ioflupane. Sixty-two consecutive patients in whom I-123-ioflupane SPECT including low-dose CT had been performed were recruited retrospectively at 3 centres. For each patient, 3 different SPECT images were reconstructed: without AC, with Chang AC and with CT-based AC. Distribution volume ratio (DVR) images were obtained by scaling voxel intensities using the whole brain without striata as reference. For assessing the impact of AC on semi-quantitative analysis, specific-to-background ratios (SBR) in caudate and putamen were obtained by fully automated SPM8-based region of interest (ROI) analysis and tested for their diagnostic power using receiver-operator-characteristic (ROC) analysis. For assessing the impact of AC on visual image reading, screenshots of stereotactically normalized DVR images presented in randomized order were interpreted independently by two raters at each centre. CT-based AC resulted in intermediate SBRs about half way between no AC and Chang. Maximum area under the ROC curve was achieved by the putamen SBR, with negligible impact of AC (0.924, 0.935 and 0.938 for no, CT-based and Chang AC). Diagnostic accuracy of visual interpretation also did not depend on AC. The impact of CT-based versus Chang AC on the interpretation of I-123-ioflupane SPECT is negligible. Therefore, CT-based AC cannot be recommended for routine use in clinical patient care, not least because of the additional radiation exposure.

Multiple sclerosis (MS), an autoimmune-driven, inflammatory demyelinating disease of the central nervous system (CNS), causes irreversible accumulation of neurological deficits to a variable extent. Although there are potent disease-modifying agents for its initial relapsing–remitting phase, immunosuppressive therapies show limited efficacy in secondary progressive MS (SPMS). Although modulation of sphingosine-1 phosphate receptors has proven beneficial during SPMS, the underlying mechanisms are poorly understood. In this project, we followed the hypothesis that siponimod, a sphingosine-1 phosphate receptor modulator, exerts protective effects by direct modulation of glia cell function (i.e., either astrocytes, microglia, or oligodendrocytes). To this end, we used the toxin-mediated, nonautoimmune MS animal model of cuprizone (Cup) intoxication. On the histological level, siponimod ameliorated cuprizone-induced oligodendrocyte degeneration, demyelination, and axonal injury. Protective effects were evident as well using GE180 translocator protein 18-kDa (TSPO) imaging with positron emission tomography (PET)/computed tomography (CT) imaging or next generation sequencing (NGS). Siponimod also ameliorated the cuprizone-induced pathologies inRag1-deficient mice, demonstrating that the protection is independent of T and B cell modulation. Proinflammatory responses in primary mixed astrocytes/microglia cell cultures were not modulated by siponimod, suggesting that other cell types than microglia and astrocytes are targeted. Of note, siponimod completely lost its protective effects inS1pr5-deficient mice, suggesting direct protection of degenerating oligodendrocytes. Our study demonstrates that siponimod exerts protective effects in the brain in a S1PR5-dependent manner. This finding is not just relevant in the context of MS but in other neuropathologies as well, characterized by a degeneration of the axon–myelin unit.