Search

Abstract Background Indigenous peoples globally continue to be underrepresented in biomarker, genomic, and biobanking research. The aim of this study was to identify core components of culturally safe and ethical biomarker and genomic research with Indigenous peoples in Australia, Aotearoa/New Zealand, Canada and the USA. Methods A scoping review with a systematic search strategy was conducted utilising electronic databases MEDLINE, EMBASE, PsychINFO, CINAHL and Global Health. Key search terms included ‘biomarkers’ and ‘genomics’ research involving Indigenous peoples in relation to ethical and legal principles of respect, sovereignty, governance and existing policies. Original research studies published from the year 2000 to the 1st of August 2023 were reviewed in a systematic manner. Components of culturally safe and ethical research processes were identified and synthesised descriptively. The quality of included studies was assessed using an Aboriginal and Torres Strait Islander Quality Appraisal Tool through an Indigenous lens. Results Seven interrelated research components were identified from seventeen studies as core processes to enhance the cultural safety of biomarker and genomic research. These included building relationships and community engagement, learning, research coordination, logistics, consent, samples and biospecimens, biobank structures and protections and policy. The importance of ensuring self-determination, ownership and decision-making power is emphasised in processes to establish and conduct biomarker and genomic research with Indigenous peoples. Conclusions Components that contribute to the cultural safety of biomarker and genomic research processes identified in this scoping review were assembled into a theoretical framework to guide research practice. Further evaluation is required by Indigenous peoples and communities to appropriate and adapt this framework for local use to promote the cultural safety of research processes and minimise barriers to Indigenous peoples’ participation in biomarker and genomic research.

BACKGROUND: Management of localized or recurrent prostate cancer since the 1990s has been based on risk stratification using clinicopathological variables, including Gleason score, T stage (based on digital rectal exam), and prostate-specific antigen (PSA). In this study a novel prognostic test, the Decipher Prostate Genomic Classifier (GC), was used to stratify risk of prostate cancer progression in a US national database of men with prostate cancer. METHODS: Records of prostate cancer cases from participating SEER (Surveillance, Epidemiology, and End Results) program registries, diagnosed during the period from 2010 through 2018, were linked to records of testing with the GC prognostic test. Multivariable analysis was used to quantify the association between GC scores or risk groups and use of definitive local therapy after diagnosis in the GC biopsy-tested cohort and postoperative radiotherapy in the GC-tested cohort as well as adverse pathological findings after prostatectomy. RESULTS: A total of 572 545 patients were included in the analysis, of whom 8927 patients underwent GC testing. GC biopsy-tested patients were more likely to undergo active active surveillance or watchful waiting than untested patients (odds ratio [OR] =2.21, 95% confidence interval [CI] = 2.04 to 2.38, P

The aim of this study was to analyze the patterns of prostate bed (PB) recurrence in prostate cancer patients experiencing prostate-specific antigen (PSA) persistence (BCP) or biochemical recurrence (BCR) after radical prostatectomy using 68Ga-PSMA-11 PET/CT (68Ga-PSMA PET) in relation to the Radiation Therapy Oncology Group (RTOG) clinical target volumes (CTVs). Methods: This single-center, retrospective analysis included patients with BCP or BCR after radical prostatectomy and PB recurrence on 68Ga-PSMA PET. The PB recurrences were delineated by nuclear medicine physicians, the CTVs by radiation oncologists contouring guidelines on the 68Ga-PSMA PET, respectively, masked from each other. The coverage of the 68Ga-PSMA PET recurrence was categorized as PSMA recurrence completely covered, partially covered, or not covered by the RTOG-based CTV. Further, we evaluated the differences in PSMA recurrence patterns among patients with different 68Ga-PSMA PET staging (miTNM). Mann-Whitney U tests, the chi-square test, and Spearman (ρ) correlation analysis were used to investigate associations between CTV coverage and 68Ga-PSMA PET-based tumor volume, serum PSA levels, miTNM, and rectal/bladder involvement. Results: A total of 226 patients were included in the analysis; 127 patients had PSMA recurrence limited to the PB (miTrN0M0), 30 had pelvic nodal disease (miTrN1M0), 32 had extrapelvic disease (miTrN0M1), and 37 had both pelvic nodal disease and extrapelvic disease (miTrN1M1). In the miTrN0M0 cohort, the recurrence involved the rectal and bladder walls in 12 of 127 (9%) and 4 of 127 (3%), respectively. The PSMA-positive PB recurrences were completely covered by the CTV in 68 of 127 patients (53%), partially covered in 43 of 127 (34%), and not covered in 16 of 127 (13%). Full coverage was associated with a smaller tumor volume (P = 0.043), a lack of rectal/bladder wall involvement (P = 0.03), and lower miTNM staging (P = 0.035) but not with lower serum PSA levels (P = 0.979). Conclusion: Our study suggests that 68Ga-PSMA PET can be a valuable tool for guiding salvage radiation therapy (SRT) planning directed to the PB in the setting of postoperative BCR or BCP. These data should be incorporated into the redefinition of PB contouring guidelines.

Purpose: The aim of this study is to develop a framework for quantitative analysis of longitudinal T2-weighted MRIs (T2w) following radiotherapy (RT) for prostate cancer. Materials and methods: The developed methodology includes: (i) deformable image registration of longitudinal series to pre-RT T2w for automated detection of prostate, peripheral zone (PZ), and gross tumor volume (GTV); and (ii) T2w signal-intensity harmonization based on three reference tissues. The REgistration and HARMonization (REHARM) framework was applied on T2w acquired in a clinical trial consisting of two pre-RT and three post-RT MRI exams. Image registration was assessed by the DICE coefficient between automatic and manual contours, and intensity normalization via inter-patient histogram intersection. Longitudinal consistency was evaluated by the repeatability coefficient and Pearson correlation (r) between the two T2w exams before RT. Results: T2w from 107 MRI exams (23 patients) were utilized. Following REHARM, the histogram intersections for prostate, PZ and GTV increased from median = 0.43/0.16/0.13 to 0.66/0.44/0.46. The repeatability in T2w intensity estimation was better for the automatic than the manual contours for all three regions of interest (r = 0.9, p

BackgroundPatients with prostate cancer undergoing radiation therapy (RT) need comfortably full bladders to reduce toxicities during treatment. Poor compliance is common with standard of care written or verbal instructions, leading to wasted patient value (PV) and clinic resources via poor throughput efficiency (TE). ObjectiveHerein, we assessed the feasibility and acceptability of a smartphone-based behavioral intervention (SBI) to improve bladder-filling compliance and methods for quantifying PV and TE. MethodsIn total, 36 patients with prostate cancer were enrolled in a single-institution, closed-access, nonrandomized feasibility trial. The SBI consists of a fully automated smart water bottle and smartphone app. Both pieces alert the patient to empty his bladder and drink a personalized volume goal, based on simulation bladder volume, 1.25 hours before his scheduled RT. Patients were trained to adjust their volume goal and notification times to achieve comfortably full bladders. The primary end point was met if qualitative (QLC) and quantitative compliance (QNC) were >80%. For QLC, patients were asked if they prepared their bladders before daily RT. QNC was met if bladder volumes on daily cone-beam tomography were >75% of the simulation’s volume. The Service User Technology Acceptability Questionnaire (SUTAQ) was given in person pre- and post-SBI. Additional acceptability and engagement end points were met if >3 out of 5 across 4 domains on the SUTAQ and >80% (15/18) of patients used the device >50% of the time, respectively. Finally, the impact of SBI on PV and TE was measured by time spent in a clinic and on the linear accelerator (linac), respectively, and contrasted with matched controls. ResultsQLC was 100% in 375 out of 398 (94.2%) total treatments, while QNC was 88.9% in 341 out of 398 (85.7%) total treatments. Of a total score of 5, patients scored 4.33 on privacy concerns, 4 on belief in benefits, 4.56 on satisfaction, and 4.24 on usability via SUTAQ. Further, 83% (15/18) of patients used the SBI on >50% of treatments. Patients in the intervention arm spent less time in a clinic (53.24, SEM 1.71 minutes) compared to the control (75.01, SEM 2.26 minutes) group (P

Abstract Extracting longitudinal image quantitative data, known as delta-radiomics, has the potential to capture changes in a patient’s anatomy throughout the course of radiation treatment for prostate cancer. Some of the major challenges of delta-radiomics studies are contouring the structures for individual fractions and accruing patients’ data in an efficient manner. The manual contouring process is often time consuming and would limit the efficiency of accruing larger sample sizes for future studies. The problem is amplified because the contours are often made by highly trained radiation oncologists with limited time to dedicate to research studies of this nature. This work compares the use of automated prostate contours generated using a deformable image-based algorithm to make predictive models of genitourinary and changes in total international prostate symptom score in comparison to manually contours for a cohort of fifty patients. Area under the curve of manual and automated models were compared using the Delong test. This study demonstrated that the delta-radiomics models were similar for both automated and manual delta-radiomics models.

Carnitine palmitoyltransferase II (CPT II) deficiency is an autosomal recessive inherited disorder related to lipid metabolism affecting skeletal muscle. The first cases of CPT II deficiency causing myopathy were reported in 1973. In 1983, Werneck et al published the first two Brazilian patients with myopathy due to CPT II deficiency, where the biochemical analysis confirmed deficient CPT activity in the muscle of both cases. Over the past 40 years since the pioneering publication, clinical phenotypes and genetic loci in the CPT2 gene have been described, and pathogenic mechanisms have been better elucidated. Genetic analysis of one of the original cases disclosed compound heterozygous pathogenic variants (p.Ser113Leu/p.Pro50His) in the CPT2 gene. Our report highlights the historical aspects of the first Brazilian publication of the myopathic form of CPT II deficiency and updates the genetic background of this pioneering publication.

Background Myasthenia gravis (MG) is an autoimmune disease usually caused by antibodies against the acetylcholine receptor (AChR-Abs), muscle-specific tyrosine kinase (MuSK-Abs), or low-density lipoprotein receptor-related protein 4 (LRP4-Abs). However, there are MG patients who do not have these antibodies and are thus said to have triple-seronegative (triple-SN) MG.

Limb-girdle muscular dystrophy (LGMD) is a group of myopathies that lead to progressive muscle weakness, predominantly involving the shoulder and pelvic girdles; it has a heterogeneous genetic etiology, with variation in the prevalence of subtypes according to the ethnic backgrounds and geographic origins of the populations. The aim of the present study was to analyze a series of patients with autosomal recessive LGMD (LGMD-R) to contribute to a better characterization of the disease and to find the relative proportion of the different subtypes in a Southern Brazil cohort. The sample population consisted of 36 patients with LGMD-R. A 9-gene targeted next-generation sequencing panel revealed variants in 23 patients with LGMD (64%), and it identified calpainopathy (LGMD-R1) in 26%, dysferlinopathy (LGMD-R2) in 26%, sarcoglycanopathies (LGMD-R3–R5) in 13%, telethoninopathy (LGMD-R7) in 18%, dystroglicanopathy (LGMD-R9) in 13%, and anoctaminopathy (LGMD-R12) in 4% of the patients. In these 23 patients with LGMD, there were 27 different disease-related variants in the ANO5, CAPN3, DYSF, FKRP, SGCA, SGCB, SGCG, and TCAP genes. There were different causal variants in different exons of these genes, except for the TCAP gene, for which all patients carried the p.Gln53* variant, and the FKRP gene, which showed recurrence of the p.Leu276Ile variant. We analyzed the phenotypic, genotypic and muscle immunohistochemical features of this Southern Brazilian cohort.

(1) Background: The objective of this analysis was to evaluate the device usage rates and patterns of use regarding Tumor-Treating Fields (TTFields) for patients with malignant pleural mesothelioma (MPM) throughout the US. (2) Methods: We evaluated de-identified data from 33 patients with MPM enrolled in FDA-required HDE protocols at 14 institutions across the US from September 2019 to March 2022. (3) Results: The median number of total TTFields usage days was 72 (range: 6–649 days), and the total treatment duration was 160 months for all patients. A low usage rate (defined as less than 6 h per day, 25%) was observed in 34 (21.2%) months. The median TTFields usage in the first 3 months was 12 h per day (range: 1.9–21.6 h), representing 50% (range: 8–90%) of the potential daily duration. The median TTFields usage after 3 months decreased to 9.1 h per day (range: 3.1–17 h), representing 38% (range: 13–71%) of the daily duration, and was lower than usage in the first 3 months (p = 0.01). (4) Conclusions: This study represents the first multicenter analysis of real-world TTFields usage based on usage patterns for MPM patients in clinical practice. The real-world usage level was lower than the suggested daily usage. Further initiatives and guidelines should be developed to evaluate the impact of this finding on tumor control.

BackgroundProstate cancer exhibits biological and clinical heterogeneity even within established clinico-pathologic risk groups. The Decipher genomic classifier (GC) is a validated method to further risk-stratify disease in patients with prostate cancer, but its performance solely within National Comprehensive Cancer Network (NCCN) high-risk disease has not been undertaken to date.MethodsA multi-institutional retrospective study of 405 men with high-risk prostate cancer who underwent primary treatment with radical prostatectomy (RP) or radiation therapy (RT) with androgen-deprivation therapy (ADT) at 11 centers from 1995 to 2005 was performed. Cox proportional hazards models were used to determine the hazard ratios (HR) for the development of metastatic disease based on clinico-pathologic variables, risk groups, and GC score. The area under the receiver operating characteristic curve (AUC) was determined for regression models without and with the GC score.ResultsOver a median follow-up of 82 months, 104 patients (26%) developed metastatic disease. On univariable analysis, increasing GC score was significantly associated with metastatic disease ([HR]: 1.34 per 0.1 unit increase, 95% confidence interval [CI]: 1.19-1.50, p  0.05). On multivariable analysis, GC score (HR: 1.33 per 0.1 unit increase, 95% CI: 1.19-1.48, p

BackgroundImmune checkpoint inhibitor (ICI) therapy is first-line treatment for many advanced non-small cell lung cancer (aNSCLC) patients. Predicting response could help guide selection of intensified or alternative anti-cancer regimens. We hypothesized that radiomics and laboratory variables predictive of ICI response in a murine model would also predict response in aNSCLC patients.MethodsFifteen mice with lung carcinoma tumors implanted in bilateral flanks received ICI. Pre-ICI laboratory and computed tomography (CT) data were evaluated for association with systemic ICI response. Baseline clinical and CT data for 117 aNSCLC patients treated with nivolumab were correlated with overall survival (OS). Models for predicting treatment response were created and subjected to internal cross-validation, with the human model further tested on 42 aNSCLC patients who received pembrolizumab.ResultsModels incorporating baseline NLR and identical radiomics (surface-to-mass ratio, average Gray, and 2D kurtosis) predicted ICI response in mice and OS in humans with AUCs of 0.91 and 0.75, respectively. The human model successfully sorted pembrolizumab patients by longer vs. shorter predicted OS (median 35 months vs. 6 months, p=0.026 by log-rank).DiscussionThis study advances precision oncology by non-invasively classifying aNSCLC patients according to ICI response using pre-treatment data only. Interestingly, identical radiomics features and NLR correlated with outcomes in the preclinical study and with ICI response in 2 independent patient cohorts, suggesting translatability of the findings. Future directions include using a radiogenomic approach to optimize modeling of ICI response.

Background: The European Society for Radiotherapy & Oncology (ESTRO) Advisory Committee for Radiation Oncology Practice (ACROP) panel on prostate bed delineation reflected on macroscopic local recurrences in patients referred for postoperative radiotherapy (PORT), a challenging situation without standardized approach, and decided to propose a consensus recommendation on target volume selection and definition. Methods: An ESTRO ACROP contouring consensus panel consisting of 12 radiation oncologists and one radiologist, all with subspecialty expertise in prostate cancer, was established. Participants were asked to delineate the prostate bed clinical target volumes (CTVs) in two separate clinically relevant scenarios: a local recurrence at the seminal vesicle bed and one apically at the level of the anastomosis. Both recurrences were prostate-specific membrane antigen (PSMA)-avid and had an anatomical correlate on magnetic resonance imaging (MRI). Participants also answered case-specific questionnaires addressing detailed recommendations on target delineation. Discussions via electronic mails and videoconferences for final editing and consensus were performed. Results: Contouring of the two cases confirmed considerable variation among the panelists. Finally, however, a consensus recommendation could be agreed upon. Firstly, it was proposed to always delineate the entire prostate bed as clinical target volume and not the local recurrence alone. The panel judged the risk of further microscopic disease outside of the visible recurrence too high to safely exclude the rest of the prostate bed from the CTV. A focused, “stereotactic” approach should be reserved for re-irradiation after previous PORT. Secondly, the option of a focal boost on the recurrence was discussed. Conclusion: Radiation oncologists are increasingly confronted with macroscopic local recurrences visible on imaging in patients referred for postoperative radiotherapy. It was recommended to always delineate and irradiate the entire prostate bed, and not the local recurrence alone, whatever the exact location of that recurrence. Secondly, specific dose-escalation on the macroscopic recurrence should only be considered if an anatomic correlate is visible. Such a focal boost is probably feasible, provided that OAR constraints are prioritized. Possible dose is also dependent on the location of the recurrence. Its potential benefit should urgently be investigated in prospective clinical trials.

Abstract For prostate cancer (PCa) patients treated with definitive radiotherapy (RT), acute and late RT-related genitourinary (GU) toxicities adversely impact disease-specific quality of life. Early warning of potential RT toxicities can prompt interventions that may prevent or mitigate future adverse events. During intensity modulated RT (IMRT) of PCa, daily cone-beam computed tomography (CBCT) images are used to improve treatment accuracy through image guidance. This work investigated the performance of CBCT-based delta-radiomic features (DRF) models to predict acute and sub-acute International Prostate Symptom Scores (IPSS) and Common Terminology Criteria for Adverse Events (CTCAE) version 5 GU toxicity grades for 50 PCa patients treated with definitive RT. Delta-radiomics models were built using logistic regression, random forest for feature selection, and a 1000 iteration bootstrapping leave one analysis for cross validation. To our knowledge, no prior studies of PCa have used DRF models based on daily CBCT images. AUC of 0.83 for IPSS and greater than 0.7 for CTCAE grades were achieved as early as week 1 of treatment. DRF extracted from CBCT images showed promise for the development of models predictive of RT outcomes. Future studies will include using artificial intelligence and machine learning to expand CBCT sample sizes available for radiomics analysis.

Abstract Background To assess the impact of systematic setup and range uncertainties for robustly optimized (RO) intensity modulated proton therapy (IMPT) and volumetric modulated arc therapy (VMAT) plans in patients with localized prostate cancer. Methods Twenty-six localized prostate patients previously treated with VMAT (CTV to PTV expansion of 3-5 mm) were re-planned with RO-IMPT with 3 mm and 5 mm geometrical uncertainties coupled with 3% range uncertainties. Robust evaluations (RE) accounting for the geometrical uncertainties of 3 and 5 mm were evaluated for the IMPT and VMAT plans. Clinical target volume (CTV), anorectum, and bladder dose metrics were analyzed between the nominal plans and their uncertainty perturbations. Results With geometric uncertainties of 5 mm and accounting for potential inter-fractional perturbations, RO-IMPT provided statistically significant (p

Purpose/Objective: Radiotherapy to the prostate bed is a potentially curative salvage option after radical prostatectomy. Although prostate bed contouring guidelines are available in the literature, important variabilities exist. The objective of this work is to provide a contemporary consensus guideline for prostate bed delineation for postoperative radiotherapy. Methods: An ESTRO-ACROP contouring consensus panel consisting of 11 radiation oncologists and one radiologist, all with known subspecialty expertise in prostate cancer, was established. Participants were asked to delineate the prostate bed clinical target volumes (CTVs) in 3 separate clinically relevant scenarios: adjuvant radiation, salvage radiation with PSA progression, and salvage radiation with persistently elevated PSA. These cases focused on the presence of positive surgical margin, extracapsular extension, and seminal vesicles involvement. None of the cases had radiographic evidence of local recurrence on imaging. A single computed tomography (CT) dataset was shared via FALCON platform and contours were performed using EduCaseTM software. Contours were analyzed qualitatively using heatmaps which provided a visual assessment of controversial regions and quantitatively analyzed using Sorensen-Dice similarity coefficients. Participants also answered case-specific questionnaires addressing detailed recommendations on target delineation. Discussions via electronic mails and videoconferences for final editing and consensus were performed. Results: The mean CTV for the adjuvant case was 76 cc (SD = 26.6), salvage radiation with PSA progression was 51.80 cc (SD = 22.7), and salvage radiation with persistently elevated PSA 57.63 cc (SD = 25.2). Compared to the median, the mean Sorensen-Dice similarity coefficient for the adjuvant case was 0.60 (SD 0.10), salvage radiation with PSA progression was 0.58 (SD = 0.12), and salvage radiation with persistently elevated PSA 0.60 (SD = 0.11). A heatmap for each clinical scenario was generated. The group agreed to proceed with a uniform recommendation for all cases, independent of the radiotherapy timing. Several controversial areas of the prostate bed CTV were identified based on both heatmaps and questionnaires. This formed the basis for discussions via videoconferences where the panel achieved consensus on the prostate bed CTV to be used as a novel guideline for postoperative prostate cancer radiotherapy. Conclusion: Variability was observed in a group formed by experienced genitourinary radiation oncologists and a radiologist. A single contemporary ESTRO-ACROP consensus guideline was developed to address areas of dissonance and improve consistency in prostate bed delineation, independent of the indication.There is important variability in existing contouring guidelines for postoperative prostate bed (PB) radiotherapy (RT) after radical prostatectomy. This work aimed at providing a contemporary consensus guideline for PB delineation. An ESTRO ACROP consensus panel including radiation oncologists and a radiologist, all with known subspecialty expertise in prostate cancer, delineated the PB CTV in 3 scenarios: adjuvant RT, salvage RT with PSA progression, and salvage RT with persistently elevated PSA. None of the cases had evidence of local recurrence. Contours were analysed qualitatively using heatmaps for visual assessment of controversial regions and quantitatively using Sorensen-Dice coefficient. Case-specific questionnaires were also discussed via e-mails and videoconferences for consensus. Several controversial areas of the PB CTV were identified based on both heatmaps and questionnaires. This formed the basis for discussions via videoconferences. Finally, a contemporary ESTRO-ACROP consensus guideline was developed to address areas of dissonance and improve consistency in PB delineation, independent of the indication.

The INFN–CNAF Tier-1 located in Bologna (Italy) is a center of the WLCG e-Infrastructure providing computing power to the four major LHC collaborations and also supports the computing needs of about fifty more groups - also from non HEP research domains. The CNAF Tier1 center has been historically very active putting effort in the integration of computing resources, proposing and prototyping solutions both for extension through Cloud resources, public and private, and with remotely owned sites, as well as developing an integrated HTC+HPC system with the PRACE CINECA supercomputer center located 8Km far from the CNAF Tier-1 located in Bologna. In order to meet the requirements for the new Tecnopolo center, where the CNAF Tier-1 will be hosted, the resource integration activities keep progressing. In particular, this contribution will detail the challenges that have recently been addressed, providing opportunistic access to non standard CPU architectures, such as PowerPC and hardware accelerators (GPUs). We explain the approach adopted to both transparently provision x86_64, ppc64le and NVIDIA V100 GPUs from the Marconi 100 HPC cluster managed by CINECA and to access data from the Tier1 storage system at CNAF. The solution adopted is general enough to enable seamless integration of other computing architectures at the same time from different providers, such as ARM CPUs from the TEXTAROSSA project, and we report about the integration of these within the computing model of the CMS experiment. Finally we will discuss the results of the early experience.

The ML_INFN initiative (“Machine Learning at INFN”) is an effort to foster Machine Learning (ML) activities at the Italian National Institute for Nuclear Physics (INFN). In recent years, artificial intelligence inspired activities have flourished bottom-up in many efforts in Physics, both at the experimental and theoretical level. Many researchers have procured desktop-level devices, with consumer-oriented GPUs, and have trained themselves in a variety of ways, from webinars, books, and tutorials. ML_INFN aims to help and systematize such effort, in multiple ways: by offering state-of-the-art hardware for ML, leveraging on the INFN Cloud provisioning solutions and thus sharing more efficiently GPUs and leveling the access to such resources to all INFN researchers, and by organizing and curating Knowledge Bases with productiongrade examples from successful activities already in production. Moreover, training events have been organized for beginners, based on existing INFN ML research and focused on flattening the learning curve. In this contribution, we will update the status of the project reporting in particular on the development of tools to take advantage of High-Performance Computing resources provisioned by CNAF and ReCaS computing centers for interactive support to activities and on the organization of the first in-person advanced-level training event, with a GPU-equipped cloud-based environment provided to each participant.

The INFN Tier1 data center is currently located in the premises of the Physics Department of the University of Bologna, where CNAF is also located. During 2023 it will be moved to the “Tecnopolo”, the new facility for research, innovation, and technological development in the same city area; the same location is also hosting Leonardo, the pre-exascale supercomputing machine managed by CINECA, co-financed as part of the EuroHPC Joint Undertaking, 4th ranked in the top500 November 2022 list. The construction of the new CNAF data center consists of two phases, corresponding to the computing requirements of LHC: Phase 1 involves an IT power of 3 MW, and Phase 2, starting from 2025, involves an IT power up to 10 MW. The new data center is designed to cope with the computing requirements of the data taking of the HL-LHC experiments, in the time spanning from 2026 to 2040 and will provide, at the same time, computing services for several other INFN experiments and projects, not only belonging to the HEP domain. The co-location with Leonardo opens wider possibilities to integrate HTC and HPC resources and the new CNAF data center will be tightly coupled with it, allowing access from a single entry point to resources located at CNAF and provided by the supercomputer. Data access from both infrastructures will be transparent to users. In this presentation we describe the new data center design, providing a status update on the migration, and we focus on the Leonardo integration showing the results of the preliminary tests to access it from the CNAF access points.

Optical bioimaging is an ever‐growing field that benefits both from the fast progress of optical instrumentation and modalities, and from the development of light‐emitting probes. The efficacy of molecular fluorescent dyes is crucial, yet hindered by limited brightness and hydrophilicity. Addressing these challenges, self‐stabilized fluorogenic organic nanoparticles only made of pure dyes (dFONs) are introduced in this work. Comprising thiol‐sensitive fluorogenic chromophores, these dFONs exhibit enhanced brightness exclusively in the presence of biological thiols, notably glutathione, overcoming the need for water‐solubilizing moieties. Importantly, these nanoparticles demonstrate large fluorescence and one‐ and two‐photon brightness, enabling sensitive bioimaging of intracellular thiols at micromolar concentrations. Notably, only the pristine fluorogenic nanoparticles can penetrate the cells and does not require to wash the cells before imaging, emphasizing their unique role as dye carriers, fluorogenic probes and ease of use. This work highlights the transformative potential of dFONs in advancing optical bioimaging, paving the way for the use of dFONs not just as tracers, but also now as biosensors and ultimately in the future as biomarkers. [ABSTRACT FROM AUTHOR]

Purpose: To assess the performance of a proton-specific knowledge based planning (KBPP) model in creation of robustly optimized intensity-modulated proton therapy (IMPT) plans for treatment of patients with prostate cancer. Materials and Methods: Forty-five patients with localized prostate cancer, who had previously been treated with volumetric modulated arc therapy, were selected and replanned with robustly optimized IMPT. A KBPP model was generated from the results of 30 of the patients, and the remaining 15 patient results were used for validation. The KBPP model quality and accuracy were evaluated with the model-provided organ-at-risk regression plots and metrics. The KBPP quality was also assessed through comparison of expert and KBPP-generated IMPT plans for target coverage and organ-at-risk sparing. Results: The resulting R2 (mean ± SD, 0.87 ± 0.07) between dosimetric and geometric features, as well as the χ2 test (1.17 ± 0.07) between the original and estimated data, showed the model had good quality. All the KBPP plans were clinically acceptable. Compared with the expert plans, the KBPP plans had marginally higher dose-volume indices for the rectum V65Gy (0.8% ± 2.94%), but delivered a lower dose to the bladder (−1.06% ± 2.9% for bladder V65Gy). In addition, KBPP plans achieved lower hotspot (−0.67Gy ± 2.17Gy) and lower integral dose (−0.09Gy ± 0.3Gy) than the expert plans did. Moreover, the KBPP generated better plans that demonstrated slightly greater clinical target volume V95 (0.1% ± 0.68%) and lower homogeneity index (−1.13 ± 2.34). Conclusions: The results demonstrated that robustly optimized IMPT plans created by the KBPP model are of high quality and are comparable to expert plans. Furthermore, the KBPP model can generate more-robust and more-homogenous plans compared with those of expert plans. More studies need to be done for the validation of the proton KBPP model at more-complicated treatment sites.

PurposeRespiratory motion of locally advanced non-small cell lung cancer (LA-NSCLC) adds to the challenge of targeting the disease with radiotherapy (RT). One technique used frequently to alleviate this challenge is an internal gross tumor volume (IGTV) generated from manual contours on a single respiratory phase of the 4DCT via the aid of deformable image registration (DIR)-based auto-propagation. Through assessing the accuracy of DIR-based auto-propagation for generating IGTVs, this study aimed to identify erring characteristics associated with the process to enhance RT targeting in LA-NSCLC.Methods4DCTs of 19 patients with LA-NSCLC were acquired using retrospective gating with 10 respiratory phases (RPs). Ground-truth IGTVs (GT-IGTVs) were obtained through manual segmentation and union of gross tumor volumes (GTVs) in all 10 phases. IGTV auto-propagation was carried out using two distinct DIR algorithms for the manually contoured GTV from each of the 10 phases, resulting in 10 separate IGTVs for each patient per each algorithm. Differences between the auto-propagated IGTVs (AP-IGTVs) and their corresponding GT-IGTVs were assessed using Dice coefficient (DICE), maximum symmetric surface distance (MSSD), average symmetric surface distance (ASSD), and percent volume difference (PVD) and further examined in relation to anatomical tumor location, RP, and deformation index (DI) that measures the degree of deformation during auto-propagation. Furthermore, dosimetric implications due to the analyzed differences between the AP-IGTVs and GT-IGTVs were assessed.ResultsFindings were largely consistent between the two algorithms: DICE, MSSD, ASSD, and PVD showed no significant differences between the 10 RPs used for propagation (Kruskal–Wallis test, ps > 0.90); MSSD and ASSD differed significantly by tumor location in the central–peripheral and superior–inferior dimensions (ps < 0.0001) while only in the central–peripheral dimension for PVD (p < 0.001); DICE, MSSD, and ASSD significantly correlated with the DI (Spearman’s rank correlation test, ps < 0.0001). Dosimetric assessment demonstrated that 79% of the radiotherapy plans created by targeting planning target volumes (PTVs) derived from the AP-IGTVs failed prescription constraints for their corresponding ground-truth PTVs.ConclusionIn LA-NSCLC, errors in DIR-based IGTV propagation present to varying degrees and manifest dependences on DI and anatomical tumor location, indicating the need for personalized consideration in designing RT internal target volume.

Background: Clozapine is the most effective medication for treatment–refractory schizophrenia but is associated with significant adverse drug effects, including hypotension and dizziness, which have a negative impact on quality of life and treatment compliance. Available evidence for the management of clozapine-induced hypotension is scant. Objectives: Due to limited guidance on the safety and efficacy of pharmacological treatments for clozapine-induced hypotension, we set out to systematically review and assess the evidence for the management of clozapine-induced hypotension and provide guidance to clinicians, patients, and carers. Design: We undertook a systematic review of the safety and efficacy of interventions for clozapine-induced hypotension given the limited available evidence. Data Sources and Methods: PubMed, Embase, PsycINFO, CINAHL, and the Cochrane trial Registry were searched from inception to November 2021 for literature on the treatment strategies for clozapine-induced hypotension and dizziness using a PROSPERO pre-registered search strategy. For orthostatic hypotension, we developed a management framework to assist in the choice of intervention. Results: We identified nine case studies and four case series describing interventions in 15 patients. Hypotension interventions included temporary clozapine dose reduction, non-pharmacological treatments, and pharmacological treatments. Midodrine, fludrocortisone, moclobemide and Bovril ® combination, and etilefrine were associated with improvement in symptoms or reduction in orthostatic hypotension. Angiotensin II, arginine vasopressin, and noradrenaline successfully restored and maintained mean arterial pressure in critical care situations. A paradoxical reaction of severe hypotension was reported with adrenaline use. Conclusion: Orthostatic hypotension is a common side effect during clozapine titration. Following an assessment of the titration schedule, salt and fluid intake, and review of hypertensive and nonselective α1-adrenergic agents, first-line treatment should be a temporary reduction in clozapine dose or non-pharmacological interventions. If orthostatic hypotension persists, fludrocortisone should be trialled with monitoring of potassium levels and sodium and fluid intake. Midodrine may be considered second-line or where fludrocortisone is contraindicated or poorly tolerated. For patients on clozapine with hypotension in critical care settings, the use of adrenaline to maintain mean arterial pressure should be avoided. Registration: PROSPERO (Registration No. CRD42020191530)

Background We evaluated the impact of thoracic radiation in patients with non‐small cell lung cancer (NSCLC), considering the depletion of total lymphocytes, use or not of chemotherapy, and radiation doses in healthy lung tissue. Methods Patients with stage III NSCLC, ECOG 0 to 2, receiving radiotherapy with or without chemotherapy were prospectively evaluated. All patients should be treated with three‐dimensional radiotherapy and received biologically effective doses (BED10α/β 10) of 48 to 80 Gy. Peripheral blood lymphocyte total counts were measured at the start of radiotherapy and at 2, 6 and 12 months after radiotherapy. Along with lymphocytes, PTV and doses of 5 Gy and 20 Gy in healthy lung tissue were also evaluated as potential factors influencing overall survival (OS) and progression‐free survival (PFS). Results A total of 46 patients were prospectively evaluated from April 2016 to August 2019, with a median follow‐up of 13 months (interquartile range, 1–39 months). The median of OS of all cohort was 22,8 months (IC 95% 17,6–28,1) and the median PFS was 19,5 months (IC 95%: 14,7–24,2). Most patients received concurrent or neoadjuvant chemotherapy (43; 93.4%). No patient received adjuvant immunotherapy. The lower the lymphocyte loss at 6 months after radiotherapy (every 100 lymphocytes/mcL), the greater the chance of PFS (HR, 0.44; 95%CI, 0.25–0.77; P = 0.004) and OS (HR, 0.83; 95%CI, 0.70–0.98; P = 0.025; P = 0.025). BED was a protective factor for both PFS (HR, 0.52; 95%CI 0.33–0.83; P = 0.0006) and OS (HR, 0.73; 95%CI 0.54–0.97; P = 0.029). Conclusions Our results suggest that lymphocyte depletion after radiotherapy reduces tumor control and survival in patients with stage III lung cancer. Radiation doses equal or higher than 60 Gy (BED1072 Gy) improve PFS and OS, but they negatively affect lymphocyte counts for months, which reduces survival and the potential of immunotherapy. Key points Significant findings of the study Thoracic irradiation for locally advanced lung cancer depletes T lymphocytes for months. Patients whose lymphocyte loss is lower have better overall survival and progression‐free survival. What this study adds It is necessary to protect the lymphocyte population, as well as other organs at risk. New forms of irradiation for large fields are needed. Furthermore, could immunotherapy before chemo‐radiotherapy, with a greater number of lymphocytes, bring an even better result?

Purpose: The National Comprehensive Cancer Network (NCCN) clinical guidelines influence medical practice, payor coverage, and standards of care. The levels of evidence underlying radiation therapy recommendations in NCCN have not been systematically explored. Herein, we aim to systematically investigate the NCCN recommendations pertaining to the categories of consensus and evidence (CE) for radiation therapy. Methods and Materials: We evaluated the distribution of CE underlying current treatment recommendations for the 20 most prevalent cancers in the United States with at least 10 radiation therapy recommendations in the NCCN clinical guidelines. For context, the distribution of evidence in the radiation therapy guidelines was compared with that of systemic therapy using a χ2 test. The proportion of category I CE between radiation and systemic therapy was compared using a 2-proportion, 2-tailed z-test in total and for each disease site. A P value of < .05 was considered significant. Results: Among all radiation therapy recommendations, the proportions of category I, IIA, IIB, and III CE were 9.7%, 80.6%, 8.4%, and 1.3%, respectively. When analyzed by disease site, cervix and breast cancer had the highest portion of category I CE (33% and 31%, respectively). There was no radiation therapy category I CE for hepatobiliary, bone, pancreatic, melanoma, and uterine cancers. There was a significant difference in the distribution of CE between the systemic therapy recommendations and the radiation therapy recommendations (χ2 statistic 64.16, P < .001). Overall, there was a significantly higher proportion of category I CE in the systemic therapy recommendations compared with the radiation therapy recommendations (12.3% vs 9.7%, P = .043). Conclusions: Only 9.7% of radiation therapy recommendations in NCCN guidelines are category I CE. The highest levels of evidence for radiation therapy are in breast and cervical cancers. Despite major advances in the field, these data underline that the majority of NCCN radiation therapy recommendations are based on uniform expert opinion and not on higher level evidence.