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Dendritic spines are considered a morphological proxy for excitatory synapses, rendering them a target of many different lines of research. Over recent years, it has become possible to image simultaneously large numbers of dendritic spines in 3D volumes of neural tissue. In contrast, currently no automated method for spine detection exists that comes close to the detection performance reached by human experts. However, exploiting such datasets requires new tools for the fully automated detection and analysis of large numbers of spines. Here, we developed an efficient analysis pipeline to detect large numbers of dendritic spines in volumetric fluorescence imaging data. The core of our pipeline is a deep convolutional neural network, which was pretrained on a general-purpose image library, and then optimized on the spine detection task. This transfer learning approach is data efficient while achieving a high detection precision. To train and validate the model we generated a labelled dataset using five human expert annotators to account for the variability in human spine detection. The pipeline enables fully automated dendritic spine detection and reaches a near human-level detection performance. Our method for spine detection is fast, accurate and robust, and thus well suited for large-scale datasets with thousands of spines. The code is easily applicable to new datasets, achieving high detection performance, even without any retraining or adjustment of model parameters.
The antibody-drug conjugate polatuzumab vedotin (pola) has recently been approved in combination with bendamustine and rituximab (pola-BR) for patients with refractory or relapsed (r/r) large B-cell lymphoma (LBCL). To investigate the efficacy of pola-BR in a real-world setting, we retrospectively analyzed 105 patients with LBCL who were treated in 26 German centers under the national compassionate use program. Fifty-four patients received pola as a salvage treatment and 51 patients were treated with pola with the intention to bridge to chimeric antigen receptor (CAR) T-cell therapy (n = 41) or allogeneic hematopoietic cell transplantation (n = 10). Notably, patients in the salvage and bridging cohort had received a median of 3 prior treatment lines. In the salvage cohort, the best overall response rate was 48.1%. The 6-month progression-free survival and overall survival (OS) was 27.7% and 49.6%, respectively. In the bridging cohort, 51.2% of patients could be successfully bridged with pola to the intended CAR T-cell therapy. The combination of pola bridging and successful CAR T-cell therapy resulted in a 6-month OS of 77.9% calculated from pola initiation. Pola vedotin-rituximab without a chemotherapy backbone demonstrated encouraging overall response rates up to 40%, highlighting both an appropriate alternative for patients unsuitable for chemotherapy and a new treatment option for bridging before leukapheresis in patients intended for CAR T-cell therapy. Furthermore, 7 of 12 patients with previous failure of CAR T-cell therapy responded to a pola-containing regimen. These findings suggest that pola may serve as effective salvage and bridging treatment of r/r LBCL patients.
Autologous hematopoietic stem cell transplantation (auto-HSCT) provides a potentially curative treatment option for relapsed and refractory lymphomas. Obesity displays an emerging epidemic risk factor for global mortality and is associated with an increased mortality in cancer patients. To date, the impact of obesity on the outcome of lymphoma patients undergoing auto-HSCT is understudied. We conducted a retrospective single-center study assessing 119 lymphoma patients who underwent auto-HSCT. Overall survival (OS) served as the primary endpoint whereas progression free survival (PFS), cumulative incidence of non-relapse related mortality (NRM) and cumulative incidence of relapse were analyzed as secondary endpoints. Obese patients (Body mass index, BMI≥30) had significantly lower OS (45.3% vs. 77.9%; p = 0.005) and PFS (29.8% vs. 67.2%; p<0.001) compared to non-obese patients at 48 months post-transplantation. The cumulative incidence of NRM displayed no significant differences while the cumulative incidence of relapse was significantly increased in patients with BMI≥30 (66.2% vs. 21.5%; p<0.001). Patients with a BMI<25 and overweight patients (BMI 25–30; 76.1% vs. 80.9%; p = 0.585), showed no significant difference in OS, whereas patients with BMI≥30 exhibited significant lower OS when compared to either of both groups (76.1% vs. 45.3%; p = .0.021 and 80.9% vs. 45.3%; p = 0.010). Furthermore, in a multivariate analysis, obesity was identified as an independent risk factor for death (Hazard ratio 2.231; 95% CI 1.024 to 4.860; p = 0.043). Further studies are needed to evaluate the reasons for the higher relapse rate causing higher mortality in obese patients.