Scientia
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El sistema de repositori digital DSpace captura, emmagatzema, indexa, conserva i distribueix material de recerca digital.2024-03-28T02:15:13ZEvaluation of effectiveness and safety of the CorPath GRX robotic system in endovascular embolization procedures of cerebral aneurysms
https://hdl.handle.net/11351/11254
Evaluation of effectiveness and safety of the CorPath GRX robotic system in endovascular embolization procedures of cerebral aneurysms
Mendes Pereira, Vitor; Rice, Hal; de Villiers, Laetitia; Sourour, Nader; Clarencon, Frederic; Spears, Julian; Tomasello, Alejandro
Background Robotic-assisted neurointervention was recently introduced, with implications that it could be used to treat neurovascular diseases.
Objective To evaluate the effectiveness and safety of the robotic-assisted platform CorPath GRX for treating cerebral aneurysms.
Methods This prospective, international, multicenter study enrolled patients with brain aneurysms that required endovascular coiling and/or stent-assisted coiling. The primary effectiveness endpoint was defined as successful completion of the robotic-assisted endovascular procedure without any unplanned conversion to manual treatment with guidewire or microcatheter navigation, embolization coil(s) or intracranial stent(s) deployment, or an inability to navigate vessel anatomy. The primary safety endpoint included intraprocedural and periprocedural events.
Results The study enrolled 117 patients (74.4% female) with mean age of 56.6 years from 10 international sites,. Headache was the most common presenting symptom in 40/117 (34.2%) subjects. Internal carotid artery was the most common location (34/122, 27.9%), and the mean aneurysm height and neck width were 5.7±2.6 mm and 3.5±1.4 mm, respectively. The overall procedure time was 117.3±47.3 min with 59.4±32.6 min robotic procedure time. Primary effectiveness was achieved in 110/117 (94%) subjects with seven subjects requiring conversion to manual for procedure completion. Only four primary safety events were recorded with two intraprocedural aneurysm ruptures and two strokes. A Raymond-Roy Classification Scale score of 1 was achieved in 71/110 (64.5%) subjects, and all subjects were discharged with a modified Rankin Scale score of ≤2.
Conclusions This first-of-its-kind robotic-assisted neurovascular trial demonstrates the effectiveness and safety of the CorPath GRX System for endovascular embolization of cerebral aneurysm procedures.
Trial registration number NCT04236856
Aneurysm; Brain; Stent; Aneurisma; Cerebro; Stent; Aneurisma; Cervell; Stent
2024-03-14T00:00:00ZThe efficacy of chemotherapy is limited by intratumoral senescent cells expressing PD-L2
https://hdl.handle.net/11351/11253
The efficacy of chemotherapy is limited by intratumoral senescent cells expressing PD-L2
Chaib, Selim; Lopez-Dominguez, Jose Alberto; Lalinde Gutiérrez, Marta; Prats, Neus; Marin Guillen, Ines; Boix Sánchez, Olga; Pérez Ramos, Sandra; Escorihuela Baez, Marta; Garcia-Garijo, Andrea; Abad, Maria; Gros, Alena; Arribas, Joaquin
Chemotherapy often generates intratumoral senescent cancer cells that strongly modify the tumor microenvironment, favoring immunosuppression and tumor growth. We discovered, through an unbiased proteomics screen, that the immune checkpoint inhibitor programmed cell death 1 ligand 2 (PD-L2) is highly upregulated upon induction of senescence in different types of cancer cells. PD-L2 is not required for cells to undergo senescence, but it is critical for senescent cells to evade the immune system and persist intratumorally. Indeed, after chemotherapy, PD-L2-deficient senescent cancer cells are rapidly eliminated and tumors do not produce the senescence-associated chemokines CXCL1 and CXCL2. Accordingly, PD-L2-deficient pancreatic tumors fail to recruit myeloid-derived suppressor cells and undergo regression driven by CD8 T cells after chemotherapy. Finally, antibody-mediated blockade of PD-L2 strongly synergizes with chemotherapy causing remission of mammary tumors in mice. The combination of chemotherapy with anti-PD-L2 provides a therapeutic strategy that exploits vulnerabilities arising from therapy-induced senescence.
Chemotherapy; Intratumoral senescent cells; Quimioterapia; Células senescentes intratumorales; Quimioteràpia; Cèl·lules senescents intratumorals
2024-01-24T00:00:00ZTALAPRO-3 clinical trial protocol: phase III study of talazoparib plus enzalutamide in metastatic castration-sensitive prostate cancer
https://hdl.handle.net/11351/11252
TALAPRO-3 clinical trial protocol: phase III study of talazoparib plus enzalutamide in metastatic castration-sensitive prostate cancer
Matsubara, Nobuaki; Agarwal, Neeraj; Saad, Fred; Azad, Arun; Mateo, Joaquin; Shore, Neal
Poly(ADP-ribose) polymerase inhibitors in combination with androgen-receptor signaling inhibitors are a promising therapeutic option for patients with metastatic castration-sensitive prostate cancer (mCSPC) and homologous recombination repair (HRR) gene alterations. Here, we describe the design and rationale of the multinational, phase III, TALAPRO-3 study comparing talazoparib plus enzalutamide versus placebo plus enzalutamide in patients with mCSPC and HRR gene alterations. The primary end point is investigator-assessed radiographic progression-free survival (rPFS) per RECIST 1.1 in soft tissue, or per PCWG3 criteria in bone. The TALAPRO-3 study will demonstrate whether the addition of talazoparib can improve the efficacy of enzalutamide as assessed by rPFS in patients with mCSPC and HRR gene alterations undergoing androgen deprivation therapy.
Clinical Trial Registration:NCT04821622 (ClinicalTrials.gov)
Registry Name: Study of Talazoparib With Enzalutamide in Men With DDR Gene Mutated mCSPC.
Date of Registration: 29 March 2021.
PARP inhibitor; Androgen receptor; Enzalutamide; Inhibidor de PARP; Receptor de andrógenos; Enzalutamida; Inhibidor de PARP; Receptor d'andrògens; Enzalutamida
2023-10-26T00:00:00ZGlioblastoma Pseudoprogression Discrimination Using Multiparametric Magnetic Resonance Imaging, Principal Component Analysis, and Supervised and Unsupervised Machine Learning
https://hdl.handle.net/11351/11251
Glioblastoma Pseudoprogression Discrimination Using Multiparametric Magnetic Resonance Imaging, Principal Component Analysis, and Supervised and Unsupervised Machine Learning
Thenier-Villa, Jose Luis; Martinez-Ricarte, Fran; Figueroa Vezirián, Margarita; Arikan Abello, Fuat
Background
One of the most frequent phenomena in the follow-up of glioblastoma is pseudoprogression, present in up to half of cases. The clinical usefulness of discriminating this phenomenon through magnetic resonance imaging and nuclear medicine has not yet been standardized; in this study, we used machine learning on multiparametric magnetic resonance imaging to explore discriminators of this phenomenon.
Methods
For the study, 30 patients diagnosed with IDH wild-type glioblastoma operated on at both study centers in 2011–2020 were selected; 15 patients corresponded to early tumor progression and 15 patients to pseudoprogression. Using unsupervised learning, the number of clusters and tumor segmentation was recorded using gap-stat and k-means method, adjusting to voxel adjacency. In a second phase, a class prediction was carried out with a multinomial logistic regression supervised learning method; the outcome variables were the percentage of assignment, class overrepresentation, and degree of voxel adjacency.
Results
Unsupervised learning of the tumor in its diagnosis shows up to 14 well-differentiated tumor areas. In the supervised learning phase, there is a higher percentage of assigned classes (P < 0.01), less overrepresentation of classes (P < 0.01), and greater adjacency (55% vs. 33%) in cases of true tumor progression compared with pseudoprogression.
Conclusions
True tumor progression preserves the multidimensional characteristics of the basal tumor at the voxel and region of interest level, resulting in a characteristic differential pattern when supervised learning is used.
Glioblastoma; Prediction models; Pseudoprogression; Glioblastoma; Models de predicció; Pseudoprogressió; Glioblastoma; Modelos de predicción; Pseudoprogresión
2024-03-01T00:00:00Z