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The initial favorable efficacy and safety profile for Alpha DaRT have been demonstrated (NCT04377360); however, the longer-term safety and durability of the treatment are unknown. This pooled analysis of four prospective trials evaluated the long-term safety and efficacy of Alpha DaRT for the treatment of head and neck or skin tumors. A total of 81 lesions in 71 patients were treated across six international institutions, with a median follow-up of 14.1 months (range: 2-51 months). Alpha DaRT sources were delivered via a percutaneous interstitial technique and placed to irradiate the tumor volume with the margin. The sources were removed two to three weeks following implantation. A complete response was observed in 89% of treated lesions (n = 72) and a partial response in 10% (n = 8). The two-year actuarial local recurrence-free survival was 77% [95% CI 63-87]. Variables, including recurrent versus non-recurrent lesions, baseline tumor size, or histology, did not impact long-term outcomes. Twenty-seven percent of patients developed related acute grade 2 or higher toxicities, which resolved with conservative measures. No grade 2 or higher late toxicities were observed. These data support the favorable safety profile of Alpha DaRT, which is currently being explored in a pivotal US trial.
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OBJECTIVES: In this study, we developed a radiomic signature for the classification of benign lipid-poor adenomas, which may potentially help clinicians limit the number of unnecessary investigations in clinical practice. Indeterminate adrenal lesions of benign and malignant nature may exhibit different values of key radiomics features. METHODS: Patients who had available histopathology reports and a non-contrast-enhanced CT scan were included in the study. Radiomics feature extraction was done after the adrenal lesions were contoured. The primary feature selection and prediction performance scores were calculated using the least absolute shrinkage and selection operator (LASSO). To eliminate redundancy, the best-performing features were further examined using the Pearson correlation coefficient, and new predictive models were created. RESULTS: This investigation covered 50 lesions in 48 patients. After LASSO-based radiomics feature selection, the test dataset's 30 iterations of logistic regression models produced an average performance of 0.72. The model with the best performance, made up of 13 radiomics features, had an AUC of 0.99 in the training phase and 1.00 in the test phase. The number of features was lowered to 5 after performing Pearson's correlation to prevent overfitting. The final radiomic signature trained a number of machine learning classifiers, with an average AUC of 0.93. CONCLUSIONS: Including more radiomics features in the identification of adenomas may improve the accuracy of NECT and reduce the need for additional imaging procedures and clinical workup, according to this and other recent radiomics studies that have clear points of contact with current clinical practice. CLINICAL RELEVANCE STATEMENT: The study developed a radiomic signature using unenhanced CT scans for classifying lipid-poor adenomas, potentially reducing unnecessary investigations that scored a final accuracy of 93%. KEY POINTS: ⢠Radiomics has potential for differentiating lipid-poor adenomas and avoiding unnecessary further investigations. ⢠Quadratic mean, strength, maximum 3D diameter, volume density, and area density are promising predictors for adenomas. ⢠Radiomics models reach high performance with average AUC of 0.95 in the training phase and 0.72 in the test phase.
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Adenoma Adrenocortical , Radiômica , Humanos , Benchmarking , Tomografia Computadorizada por Raios X , Lipídeos , Estudos RetrospectivosRESUMO
Prostate cancer (PCa) risk categorization based on clinical/PSA testing results in a substantial number of men being overdiagnosed with indolent, early-stage PCa. Clinically non-significant PCa is characterized as the presence of ISUP grade one, where PCa is found in no more than two prostate biopsy cores.MRI-ADC and [68Ga]Ga-PSMA-11 PET have been proposed as tools to predict ISUP grade one patients and consequently reduce overdiagnosis. In this study, Radiomics analysis is applied to MRI-ADC and [68Ga]Ga-PSMA-11 PET maps to quantify tumor characteristics and predict histology-proven ISUP grades. ICC was applied with a threshold of 0.6 to assess the features' stability with variations in contouring. Logistic regression predictive models based on imaging features were trained on 31 lesions to differentiate ISUP grade one patients from ISUP two+ patients. The best model based on [68Ga]Ga-PSMA-11 PET returned a prediction efficiency of 95% in the training phase and 100% in the test phase whereas the best model based on MRI-ADC had an efficiency of 100% in both phases. Employing both imaging modalities, prediction efficiency was 100% in the training phase and 93% in the test phase. Although our patient cohort was small, it was possible to assess that both imaging modalities add information to the prediction models and show promising results for further investigations.
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The purpose of this study is to discuss how to use an external radio-opaque template in the Diffusing Alpha-emitters Radiation Therapy (DaRT) technique's pre-planning and treatment stages. This device would help to determine the proper number of sources for tumour coverage, accounting for subcutaneous invasion and augmenting DaRT safety. The procedure will be carried out in a first phase on a phantom and then applied to a clinical case. A typical DaRT procedure workflow comprises steps like tumour measurements and delineation, source number assessment, and therapy administration. As a first step, an adhesive fiberglass mesh (spaced by 2 mm) tape was applied on the skin of the patient and employed as frame of reference. A physician contoured the lesion and marked the entrance points for the needles with a radio opaque ink marker. According to the radio opaque marks and metabolic uptake the clinical target volume was defined, and with a commercial brachytherapy treatment planning system (TPS) it was possible to simulate and adjust the spatial seeds distribution. After the implant procedure a CT was again performed to check the agreement between simulations and seeds positions. With the procedure described above it was possible to simulate a DaRT procedure on a phantom in order to train physicians and subsequently apply the novel approach on patients, outlining the major issues involved in the technique. The present work innovates and supports DaRT technique for the treatment of cutaneous cancers, improving its efficacy and safety.
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The majority of local recurrences, after conservative surgery of breast cancer, occurs in the same anatomical area where the tumour was originally located. For the treatment of ductal carcinoma in situ (DCIS), a new medical device, named BAT-90, (BetaGlue Technologies SpA) has been proposed. BAT-90 is based on the administration of 90Y ß-emitting microspheres, embedded in a bio-compatible matrix. In this work, the Geant4 simulation toolkit is used to simulate BAT-90 as a homogenous cylindrical 90Y layer placed in the middle of a bulk material. The activity needed to deliver a 20 Gy isodose at a given distance z from the BAT-90 layer is calculated for different device thicknesses, tumour bed sizes and for water and adipose bulk materials. A radiobiological analysis has been performed using both the Poisson and logistic Tumour Control Probability (TCP) models. A range of radiobiological parameters (α and ß), target sizes, and densities of tumour cells were considered. Increasing α values, TCP increases too, while, for a fixed α value, TCP decreases as a function of clonogenic cell density. The models predict very solid results in case of limited tumour burden while the activity/dose ratio could be further optimized in case of larger tumour beds.
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Neoplasias da Mama/radioterapia , Carcinoma Ductal de Mama/radioterapia , Carcinoma Intraductal não Infiltrante/radioterapia , Radioterapia/métodos , Simulação por Computador , Feminino , Humanos , Modelos Logísticos , Radioterapia/instrumentação , Dosagem Radioterapêutica , Carga TumoralRESUMO
Testicular cancer is a rare tumor with a worldwide incidence that has increased over the last few decades. The majority of these tumors are testicular non-germ (TNGCTs) and germ cell tumors (TGCTs); the latter divided into two broad classes - seminomatous (SGCTs) and non-seminomatous germ cell tumors (NSGCTs). Although ultrasonography (US) maintains a primary role in the diagnostic workup of scrotal pathology, magnetic resonance imaging (MRI) has emerged as the imaging modality recommended for challenging cases, providing additional information to clarify inconclusive/equivocal US. In this work we describe and publicly share a collection of 44 images of annotated T2-weighted MRI lesions from 42 patients. Given that testicular cancer is a rare tumor, we are confident that this collection can be used to validate statistical models and to further investigate TNGCT and TGCT peculiarities using medical imaging features.
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Imageamento por Ressonância Magnética , Neoplasias Embrionárias de Células Germinativas/diagnóstico por imagem , Neoplasias Testiculares/diagnóstico por imagem , Adulto , Humanos , Masculino , Pessoa de Meia-Idade , Seminoma/diagnóstico por imagem , Testículo/diagnóstico por imagem , Testículo/patologia , Adulto JovemRESUMO
PURPOSE: The objective of this study was to evaluate a set of radiomics-based advanced textural features extracted from 18F-FLT-PET/CT images to predict tumor response to neoadjuvant chemotherapy (NCT) in patients with locally advanced breast cancer (BC). MATERIALS AND METHODS: Patients with operable (T2-T3, N0-N2, M0) or locally advanced (T4, N0-N2, M0) BC were enrolled. All patients underwent chemotherapy (six cycles every 3 weeks). Surgery was performed within 4 weeks of the end of NCT. The MD Anderson Residual Cancer Burden calculator was used to evaluate the pathological response. 18F-FLT-PET/CT was performed 2 weeks before the start of NCT and approximately 3 weeks after the first cycle. The evaluation of PET response was based on EORTC criteria. Standard uptake value (SUV) statistics (SUVmax, SUVpeak, SUVmean), together with 148 textural features, were extracted from each lesion. Indices that are robust against contour variability (ICC test) were used as independent variables to logistically model tumor response. LASSO analysis was used for variable selection. RESULTS: Twenty patients were included in the study. Lesions from 15 patients were evaluable and analyzed: 9 with pathological complete response (pCR) and 6 with pathological partial response (pPR). Concordance between PET response and histological examination was found in 13/15 patients. LASSO logistic modelling identified a combination of SUVmax and the textural feature index IVH_VolumeIntFract_90 as the most useful to classify PET response, and a combination of PET response, ID range, and ID_Coefficient of Variation as the most useful to classify pathological response. CONCLUSIONS: Our study suggests the potential usefulness of FLT-PET for early monitoring of response to NCT. A model based on PET radiomic characteristics could have good discriminatory capacity of early response before the end of treatment.
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How to differentiate with MRI-based techniques testicular germ (TGCTs) and testicular non-germ cell tumors (TNGCTs) is still under debate and Radiomics may be the turning key. Our purpose is to investigate the performance of MRI-based Radiomics signatures for the preoperative prediction of testicular neoplasm histology. The aim is twofold: (i), differentiating TGCTs and TNGCTs status and (ii) differentiating seminomas (SGCTs) from non-seminomatous (NSGCTs). Forty-two patients with pathology-proven testicular neoplasms and referred for pre-treatment MRI, were retrospectively enrolled. Thirty-two out of 44 lesions were TGCTs. Twelve out of 44 were TNGCTs or other histologies. Two radiologists segmented the volume of interest on T2-weighted images. Approximately 500 imaging features were extracted. Least Absolute Shrinkage and Selection Operator (LASSO) was applied as method for variable selection. A linear model and a linear support vector machine (SVM) were trained with selected features to assess discrimination scores for the two endpoints. LASSO identified 3 features that were employed to build fivefold validated linear discriminant and linear SVM classifiers for the TGCT-TNGCT endpoint giving an overall accuracy of 89%. Four features were employed to build another SVM for the SGCT-SNGCT endpoint with an overall accuracy of 86%. The data obtained proved that T2-weighted-based Radiomics is a promising tool in the diagnostic workup of testicular neoplasms by discriminating germ cell from non-gem cell tumors, and seminomas from non-seminomas.
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Neoplasias Embrionárias de Células Germinativas/diagnóstico por imagem , Seminoma/diagnóstico por imagem , Neoplasias Testiculares/diagnóstico por imagem , Adulto , Biomarcadores , Diagnóstico Diferencial , Humanos , Imageamento por Ressonância Magnética , Masculino , Neoplasias Embrionárias de Células Germinativas/patologia , Estudos Retrospectivos , Seminoma/patologia , Máquina de Vetores de Suporte , Neoplasias Testiculares/patologiaRESUMO
PURPOSE: The aim of this work was to analyze the exposure rates measured in the proximity of patients who underwent prostate low-dose-rate brachytherapy with I-125 implant. Effective doses to relatives and to population were computed to estimate the time to reach radioprotection dose constraints. METHODS AND MATERIALS: Measurements were obtained from 180 patients, whereas the body mass index was calculated and reported for 77 patients. The day after the implant, KË measurements were conducted at various skin distances and positions and converted to effective doses. A theoretical model was developed to estimate effective doses from total implanted activity. The latter was approximated with a 10-mL vial inside the patient. RESULTS: The KË measurements showed a low correlation with the total implanted activity, albeit an increasing trend of KË was observed on increasing the activity. A stronger correlation was found between body mass index and KË measurements. The effective dose to population is in general lower than dose constraints as well as the effective doses to relatives, with the exception of children and pregnant women, who command special precautions. We report differences between the experimental model- and theoretical model-based dose evaluation together with their comparison with previous studies found in literature. CONCLUSIONS: Based on the KË measurements and the results of the present analysis, it is possible to provide the patient with radiation safety instructions specifically tailored to his relatives' habits and working environment.
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Braquiterapia , Neoplasias da Próstata , Proteção Radiológica , Braquiterapia/métodos , Criança , Humanos , Radioisótopos do Iodo/uso terapêutico , Masculino , Gravidez , Neoplasias da Próstata/radioterapia , Dosagem RadioterapêuticaRESUMO
PURPOSE: Alpha particle treatments could enhance the probability of an immune response, which can lead to abscopal effects (AE). We report a case of a patient affected by multiple cutaneous squamous cell carcinoma (cSCC). After the treatment with diffusing alpha emitters radiation therapy (DaRT) of one lesion, an AE was observed on at least two distant ones. MATERIAL AND METHODS: We investigated a case of a 65-year-old female patient with multiple synchronous lesions of the skin of lower limbs confirmed by a biopsy. Patient was enrolled in a clinical trial N.CTP-SCC-00 (NCT03015883), with the objective to assess effectiveness of DaRT technique. DaRT is based on the insertion of locally 224Ra-loaded seeds in a clinical target volume (CTV). Treatment plan with positron emission tomography/computed tomography (PET/CT) was used to entirely cover the CTV. Follow-up and biopsy evaluations were employed to outline the patient outcome. RESULTS: We performed seeds implantation according to the Paris system. At 28th day, an evident lesion shrinkage with a persistent minimal area of hyperkeratosis was noted. 76 days after implantation, a complete remission of the treated lesion was observed and an evident reduction of the area with two more distant lesion, which could be associated to an immune-mediated response. One year after the treatment, a complete remission of treated lesion was observed as well as spontaneous regression of untreated distant ones. CONCLUSIONS: In this study, we reported evidences of an AE in cSCC stimulated by radiation and possibly mediated by immune system. In the next DaRT treatments, our intent is to monitor T-lymphocytes variations in peripheral blood in order to demonstrate indirect activation of the immune system mediated by radiation also in patients with solitary lesions, in which, by definition, an AE cannot be observed.
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BACKGROUND: Radiomic analyses of CT images provide prognostic information that can potentially be used for personalized treatment. However, heterogeneity of acquisition- and reconstruction protocols influences robustness of radiomic analyses. The aim of this study was to investigate the influence of different CT-scanners, slice thicknesses, exposures and gray-level discretization on radiomic feature values and their stability. MATERIAL AND METHODS: A texture phantom with ten different inserts was scanned on nine different CT-scanners with varying tube currents. Scans were reconstructed with 1.5 mm or 3 mm slice thickness. Image pre-processing comprised gray-level discretization in ten different bin widths ranging from 5 to 50 HU and different resampling methods (i.e., linear, cubic and nearest neighbor interpolation to 1 × 1 × 3 mm3 voxels) were investigated. Subsequently, 114 textural radiomic features were extracted from a 2.1 cm3 sphere in the center of each insert. The influence of slice thickness, exposure and bin width on feature values was investigated. Feature stability was assessed by calculating the concordance correlation coefficient (CCC) in a test-retest setting and for different combinations of scanners, tube currents and slice thicknesses. RESULTS: Bin width influenced feature values, but this only had a marginal effect on the total number of stable features (CCC > 0.85) when comparing different scanners, slice thicknesses or exposures. Most radiomic features were affected by slice thickness, but this effect could be reduced by resampling the CT-images before feature extraction. Statistics feature 'energy' was the most dependent on slice thickness. No clear correlation between feature values and exposures was observed. CONCLUSIONS: CT-scanner, slice thickness and bin width affected radiomic feature values, whereas no effect of exposure was observed. Optimization of gray-level discretization to potentially improve prognostic value can be performed without compromising feature stability. Resampling images prior to feature extraction decreases the variability of radiomic features.