[en] Cadmium sulfide/anodic alumina nanoporous bi-layer film was designed for the first time by two-step anodization followed by a sol–gel spin coating method. The chemical composition, morphological, electrical and structural properties of the AA and Cd/AA nanoporous membranes have been examined. The morphological investigation of AA layer demonstrates the development of an exceptionally ordered hexagonal exhibit of nanoporous anodic alumina of pore diameter ~55 nm and inter-pore distance ~125 nm. Though, CdS/AA demonstrated the deposition of nanoporous CdS layer from agglomerated CdS nanoparticles on the surface of the membrane of AA. The energy-dispersive X-ray spectrum of CdS/AA outlined signs of O, Al, Cd, and S, which shows its high purity. The X-ray diffraction affirmed the development of cubic-phase CdS in the favored (220) orientation with normal ~86.2 nm crystallite size. The present voltage and resistance–concentration attributes of the CdS/AA layer as a glucose biosensor are fitted well with second-order polynomial behavior (correlation coefficient=0.981). The glucose concentration changed from 0 to 400 mg/dl. In light of the upsides of the fabrication approach, this new age of minimal effort biosensors can be utilized as a guarantee building block for nanophotonic and nanoelectronic gadgets.

[en] Hybrid imaging combining single photon emission computed tomography (SPECT) with ¹³¹I and X-ray computed tomography (CT) performed at radioablation (RA) for thyroid carcinoma more accurately detects regional lymph node metastases (LNM) than does planar imaging. In this bicentric prospective study we used hybrid imaging in conjunction with histopathological examination to measure LNM frequency in a consecutive group of patients referred for RA due to stage T1 papillary thyroid carcinoma (PTC). At the Departments of Nuclear Medicine of the Ludwig Maximilian University of Munich and the Friedrich Alexander University of Erlangen-Nuremberg SPECT/spiral CT is routinely performed in all PTC subjects at the time of RA. Screening of our SPECT/CT databases for PTC patients with T1 histology produced 98 patients from Munich and 53 patients from Erlangen, including 96 of 151 patients with microcarcinoma. In 69 patients of the entire group, cervical lymph node dissection had been performed, whereas nodal staging in the remaining 82 subjects was based on SPECT/CT. LNM incidence in the whole group was 26% [95% confidence interval (CI): 20-33%] versus 22% (95% CI: 15-31%) in the microcarcinoma subgroup. SPECT/CT was more accurate in 24.5% of our patients than planar imaging with regard to nodal staging. LNM occurs in one quarter of all patients with T1 PTC, and also in the subset with microcarcinoma. Performing ¹³¹I SPECT/CT, either with therapeutic or diagnostic radioactivities, directly after thyroidectomy should provide more accurate staging of T1 PTC, thus facilitating optimal therapeutic management. (orig.)

[en] "1"8F-fluorethyltyrosine-(FET)-PET and MRI-based relative cerebral blood volume (rCBV) have both been used to characterize gliomas. Recently, inter-individual correlations between peak static FET-uptake and rCBV have been reported. Herein, we assess the local intra-lesional relation between FET-PET parameters and rCBV. Thirty untreated glioma patients (27 high-grade) underwent simultaneous PET/MRI on a 3 T hybrid scanner obtaining structural and dynamic susceptibility contrast sequences. Static FET-uptake and dynamic FET-slope were correlated with rCBV within tumour hotspots across patients and intra-lesionally using a mixed-effects model to account for inter-individual variation. Furthermore, maximal congruency of tumour volumes defined by FET-uptake and rCBV was determined. While the inter-individual relationship between peak static FET-uptake and rCBV could be confirmed, our intra-lesional, voxel-wise analysis revealed significant positive correlations (median r = 0.374, p < 0.0001). Similarly, significant inter- and intra-individual correlations were observed between FET-slope and rCBV. However, rCBV explained only 12% of the static and 5% of the dynamic FET-PET variance and maximal overlap of respective tumour volumes was 37% on average. Our results show that the relation between peak values of MR-based rCBV and static FET-uptake can also be observed intra-individually on a voxel basis and also applies to a dynamic FET parameter, possibly determining hotspots of higher biological malignancy. However, just a small part of the FET-PET signal variance is explained by rCBV and tumour volumes determined by the two modalities showed only moderate overlap. These findings indicate that FET-PET and MR-based rCBV provide both congruent and complimentary information on glioma biology. (orig.)

[en] To evaluate the performance of combined PET and multiparametric MRI (mpMRI) radiomics for the group-wise prediction of postsurgical Gleason scores (psGSs) in primary prostate cancer (PCa) patients. Patients with PCa, who underwent [${}^{68}$Ga]Ga-PSMA-11 PET/MRI followed by radical prostatectomy, were included in this retrospective analysis (n = 101). Patients were grouped by psGS in three categories: ISUP grades 1-3, ISUP grade 4, and ISUP grade 5. mpMRI images included T1-weighted, T2-weighted, and apparent diffusion coefficient (ADC) map. Whole-prostate segmentations were performed on each modality, and image biomarker standardization initiative (IBSI)-compliant radiomic features were extracted. Nine support vector machine (SVM) models were trained: four single-modality radiomic models (PET, T1w, T2w, ADC); three PET + MRI double-modality models (PET + T1w, PET + T2w, PET + ADC), and two baseline models (one with patient data, one image-based) for comparison. A sixfold stratified cross-validation was performed, and balanced accuracies (bAcc) of the predictions of the best-performing models were reported and compared through Student's t-tests. The predictions of the best-performing model were compared against biopsy GS (bGS). All radiomic models outperformed the baseline models. The best-performing (mean ± stdv [%]) single-modality model was the ADC model (76 ± 6%), although not significantly better (p > 0.05) than other single-modality models (T1w: 72 ± 3%, T2w: 73 ± 2%; PET: 75 ± 5%). The overall best-performing model combined PET + ADC radiomics (82 ± 5%). It significantly outperformed most other double-modality (PET + T1w: 74 ± 5%, p = 0.026; PET + T2w: 71 ± 4%, p = 0.003) and single-modality models (PET: p = 0.042; T1w: p = 0.002; T2w: p = 0.003), except the ADC-only model (p = 0.138). In this initial cohort, the PET + ADC model outperformed bGS overall (82.5% vs 72.4%) in the prediction of psGS. All single- and double-modality models outperformed the baseline models, showing their potential in the prediction of GS, even with an unbalanced cohort. The best-performing model included PET + ADC radiomics, suggesting a complementary value of PSMA-PET and ADC radiomics.