Basal cell carcinoma: 10-year experience with electrochemotherapy

BACKGROUND: Electrochemotherapy (ECT), by combining manageable cytotoxic agents with short electric pulses, represents an effective palliative skin-directed therapy. The accumulated evidence indicates that ECT stands out as a safe and well-tolerated alternative treatment for patients with multiple or large basal cell carcinoma (BCC), who are not suitable for conventional treatments. However, long-term data and shared indications are lacking. METHODS: In this observational study, we retrospectively analyzed 84 prospectively collected patients with multiple, recurrent or locally advanced BCC who were not candidate for standard therapies and received bleomycin-based ECT according to the European Standard Operative Procedures of ECT, from 2006 to 2016. RESULTS: Disease extent was local, locally advanced and metastatic in 40 (48%), 41 (49%) and 3 (3%), respectively. Forty-four (52%) individuals had multiple BCCs. Grade 3 skin toxicity after ECT was observed in 6% of cases. Clearance rate was 50% (95% CI 39-61%). Primary presentation (p = 0.004), tumor size <3 cm (p < 0.001), well-defined borders (p = 0.021), absence of tumor ulceration (p = 0.001), non-aggressive BCC histology (p = 0.046) and age 6469 years were associated with higher complete response rate. In patients with local BCC, the clearance rate was 72.5 and 85% after one or two ECT cycles, respectively. In the laBCC group, 32 patients (78%) achieved an objective response. Five-year recurrence rate for local and laBCC was 20 and 38%, respectively (p 64 0.001). CONCLUSIONS: One or two ECT cycles with bleomycin may be a valuable palliative treatment in well-selected patients with multiple BCCs and favorable tumor features. Validation of predictive factors will be imperative to match patients with optimal ECT treatment modalities. Management of laBCC with ECT warrants further investigation. Trial registration ISRCTN14633165 Registered 24 March 2017 (retrospectively registered)

Treatment efficacy with electrochemotherapy: A multi-institutional prospective observational study on 376 patients with superficial tumors

BACKGROUND: Cutaneous metastases represent a therapeutic challenge. An increasing body of experience suggests that electrochemotherapy (ECT) provides effective tumor control, although its evidence basis should be strengthened. METHODS: This prospective, multicenter, observational study enrolled patients with superficial metastases, who underwent ECT at 10 centers between 2008 and 2013. Outcomes included adherence to European Standard Operating Procedures of ECT (ESOPE), tumor response, local progression-free survival (LPFS), toxicity and patient-reported outcomes (PROs, EORTC QLQ-C30 plus an 8-item questionnaire). RESULTS: We enrolled 376 eligible patients. Tumor histotype distribution was as follows: melanoma, 56%; squamous cell carcinoma, 11%; Kaposi sarcoma, 11%; breast carcinoma, 8%; basal cell carcinoma, 6%; soft tissue sarcomas, 3%; others, 5%. We registered 1304 target tumors (median size 1 cm). Treatment adhered to ESOPE in 88% of patients as to the route of drug administration, and in 70% as to electrode application. The procedure was mainly performed under sedation (64.6%) and by using intravenous chemotherapy (93.4%). Tumor response rate at 60 days was 88% (complete, 50%). Small tumor size predicted complete response achievement (OR 2.24, p = 0.003), higher LPFS (HR 0.68, p = 0.004) and improved PROs (Global Health Status, p < 0.001; wound bleeding, p < 0.001; healing, p = 0.002; and aesthetics, p < 0.001). Skin toxicity (grade 653, 7.8%) was lower in patients with tumors <2 cm (p 640.001). One-year LPFS was 73.7% (95%CI 68.4-78.3). CONCLUSIONS: ECT represents a valuable skin-directed therapy across a range of malignancies. The most frequently applied treatment modality is intravenous chemotherapy under sedation. Small tumor size predicts durable tumor control, fewer side-effects and better PROs

CAD-based computer vision: the automatic generation of recognition stragtegies

Journal ArticleThree-dimensional model-based computer vision uses geometric models of objects and sensed data to recognize objects in a scene. Likewise, Computer Aided Design (CAD) systems are used to interactively generate three-dimensional models during these fields. Recently, the unification of CAD and vision systems has become the focus of research in the context of manufacturing automation. This paper explores the connection between CAD and computer vision. A method for the automatic generation of recognition strategies based on the geometric properties of shape has been devised and implemented. This uses a novel technique developed for quantifying the following properties of features which compose models used in computer vision: robustness, completeness, consistency, cost, and uniqueness. By utilizing this information, the automatic synthesis of a specialized recognition scheme, called a Strategy Tree, is accomplished. Strategy Trees describe, in a systematic and robust manner. the search process used for recognition and localization of particular objects in the given scene. They consist of selected features which satisfy system constraints and Corroborating Evidence Subtrees which are used in the formation of hypotheses. Verification techniques, used to substantiate or refute these hypotheses, are explored. Experiments utilizing 3-D data are presented

Investigating the UHECR characteristics from cosmogenic neutrino limits with the measurements of the Pierre Auger Observatory

Cosmogenic neutrinos are expected to originate in the extragalactic propagation of ultra-high-energy cosmic rays (UHECRs), as a result of their interactions with background photons. Due to these reactions, the visible Universe in UHECRs is more limited than in neutrinos, which instead could reach us without interacting after traveling cosmological distances. In this contribution, we exploit a multimessenger approach by computing the expected energy spectrum and mass composition of UHECRs at Earth corresponding to combinations of spectral parameters and mass composition at their sources, as well as parameters related to the UHECR source distribution, and by determining, at the same time, the associated cosmogenic neutrino fluxes. By comparing the expected UHECR observables to the energy spectrum and mass composition measured at the Pierre Auger Observatory above 1017.8 eV and the expected neutrino fluxes to the most updated neutrino limits, we show the dependence of the neutrino fluxes on the characteristics of the the properties of the potential sources of UHECRs, such as their cosmological evolution and maximum redshift. In addition, the fraction of protons compatible with the data is also investigated in terms of expected neutrino fluxes

Deep-Learning-Based Cosmic-Ray Mass Reconstruction Using the Water-Cherenkov and Scintillation Detectors of AugerPrime

At the highest energies, cosmic rays can be detected only indirectly by the extensive air showers they create upon interaction with the Earth\u27s atmosphere. While high-statistics measurements of the energy and arrival directions of cosmic rays can be performed with large surface detector arrays like the Pierre Auger Observatory, the determination of the cosmic-ray mass on an event-by-event basis is challenging. Meaningful physical observables in this regard include the depth of maximum of air-shower profiles, which is related to the mean free path of the cosmic ray in the atmosphere and the shower development, as well as the number of muons that rises with the number of nucleons in a cosmic-ray particle. In this contribution, we present an approach to determine both of these observables from combined measurements of water-Cherenkov detectors and scintillation detectors, which are part of the AugerPrime upgrade of the Observatory. To characterize the time-dependent signals of the two detectors both separately as well as in correlation to each other, we apply deep learning techniques. Transformer networks employing the attention mechanism are especially well-suited for this task. We present the utilized network concepts and apply them to simulations to determine the precision of the event-by-event mass reconstruction that can be achieved by the combined measurements of the depth of shower maximum and the number of muons

Combined fit to the spectrum and composition data measured by the Pierre Auger Observatory including magnetic horizon effects

The measurements by the Pierre Auger Observatory of the energy spectrum and mass composition of cosmic rays can be interpreted assuming the presence of two extragalactic source populations, one dominating the flux at energies above a few EeV and the other below. To fit the data ignoring magnetic field effects, the high-energy population needs to accelerate a mixture of nuclei with very hard spectra, at odds with the approximate E$^{-2}$ shape expected from diffusive shock acceleration. The presence of turbulent extragalactic magnetic fields in the region between the closest sources and the Earth can significantly modify the observed CR spectrum with respect to that emitted by the sources, reducing the flux of low-rigidity particles that reach the Earth. We here take into account this magnetic horizon effect in the combined fit of the spectrum and shower depth distributions, exploring the possibility that a spectrum for the high-energy population sources with a shape closer to E$^{-2}$ be able to explain the observations