@article{HartrampfHeinrichSeitzetal.2020, author = {Hartrampf, Philipp E. and Heinrich, Marieke and Seitz, Anna Katharina and Brumberg, Joachim and Sokolakis, Ioannis and Kalogirou, Charis and Schirbel, Andreas and K{\"u}bler, Hubert and Buck, Andreas K. and Lapa, Constantin and Krebs, Markus}, title = {Metabolic Tumour Volume from PSMA PET/CT Scans of Prostate Cancer Patients during Chemotherapy — Do Different Software Solutions Deliver Comparable Results?}, series = {Journal of Clinical Medicine}, volume = {9}, journal = {Journal of Clinical Medicine}, number = {5}, issn = {2077-0383}, doi = {10.3390/jcm9051390}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-205893}, year = {2020}, abstract = {(1) Background: Prostate-specific membrane antigen (PSMA)-derived tumour volume (PSMA-TV) and total lesion PSMA (TL-PSMA) from PSMA PET/CT scans are promising biomarkers for assessing treatment response in prostate cancer (PCa). Currently, it is unclear whether different software tools for assessing PSMA-TV and TL-PSMA produce comparable results. (2) Methods: \(^{68}\)Ga-PSMA PET/CT scans from n = 21 patients with castration-resistant PCa (CRPC) receiving chemotherapy were identified from our single-centre database. PSMA-TV and TL-PSMA were calculated with Syngo.via (Siemens) as well as the freely available Beth Israel plugin for FIJI (Fiji Is Just ImageJ) before and after chemotherapy. While statistical comparability was illustrated and quantified via Bland-Altman diagrams, the clinical agreement was estimated by matching PSMA-TV, TL-PSMA and relative changes of both variables during chemotherapy with changes in serum PSA (ΔPSA) and PERCIST (Positron Emission Response Criteria in Solid Tumors). (3) Results: Comparing absolute PSMA-TV and TL-PSMA as well as Bland-Altman plotting revealed a good statistical comparability of both software algorithms. For clinical agreement, classifying therapy response did not differ between PSMA-TV and TL-PSMA for both software solutions and showed highly positive correlations with BR. (4) Conclusions: due to the high levels of statistical and clinical agreement in our CRPC patient cohort undergoing taxane chemotherapy, comparing PSMA-TV and TL-PSMA determined by Syngo.via and FIJI appears feasible.}, language = {en} } @article{KotlyarKrebsSolimandoetal.2023, author = {Kotlyar, Mischa J. and Krebs, Markus and Solimando, Antonio Giovanni and Marquardt, Andr{\´e} and Burger, Maximilian and K{\"u}bler, Hubert and Bargou, Ralf and Kneitz, Susanne and Otto, Wolfgang and Breyer, Johannes and Vergho, Daniel C. and Kneitz, Burkhard and Kalogirou, Charis}, title = {Critical evaluation of a microRNA-based risk classifier predicting cancer-specific survival in renal cell carcinoma with tumor thrombus of the inferior vena cava}, series = {Cancers}, volume = {15}, journal = {Cancers}, number = {7}, issn = {2072-6694}, doi = {10.3390/cancers15071981}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-311040}, year = {2023}, abstract = {(1) Background: Clear cell renal cell carcinoma extending into the inferior vena cava (ccRCC\(^{IVC}\)) represents a clinical high-risk setting. However, there is substantial heterogeneity within this patient subgroup regarding survival outcomes. Previously, members of our group developed a microRNA(miR)-based risk classifier — containing miR-21-5p, miR-126-3p and miR-221-3p expression — which significantly predicted the cancer-specific survival (CSS) of ccRCC\(^{IVC}\) patients. (2) Methods: Examining a single-center cohort of tumor tissue from n = 56 patients with ccRCC\(^{IVC}\), we measured the expression levels of miR-21, miR-126, and miR-221 using qRT-PCR. The prognostic impact of clinicopathological parameters and miR expression were investigated via single-variable and multivariable Cox regression. Referring to the previously established risk classifier, we performed Kaplan-Meier analyses for single miR expression levels and the combined risk classifier. Cut-off values and weights within the risk classifier were taken from the previous study. (3) Results: miR-21 and miR-126 expression were significantly associated with lymphonodal status at the time of surgery, the development of metastasis during follow-up, and cancer-related death. In Kaplan-Meier analyses, miR-21 and miR-126 significantly impacted CSS in our cohort. Moreover, applying the miR-based risk classifier significantly stratified ccRCC\(^{IVC}\) according to CSS. (4) Conclusions: In our retrospective analysis, we successfully validated the miR-based risk classifier within an independent ccRCC\(^{IVC}\) cohort.}, language = {en} }