Comprehensive dosimetric characterization of novel silicon carbide detectors with UHDR electron beams for FLASH radiotherapy.

Background: The extremely fast delivery of doses with ultra high dose rate (UHDR) beams necessitates the investigation of novel approaches for real-time dosimetry and beam monitoring. This aspect is fundamental in the perspective of the clinical application of FLASH radiotherapy (FLASH-RT), as conventional dosimeters tend to saturate at such extreme dose rates.

Purpose: This study aims to experimentally characterize newly developed silicon carbide (SiC) detectors of various active volumes at UHDRs and systematically assesses their response to establish their suitability for dosimetry in FLASH-RT.

Single-Ion Counting with an Ultra-Thin-Membrane Silicon Carbide Sensor.

In recent times, ion implantation has received increasing interest for novel applications related to deterministic material doping on the nanoscale, primarily for the fabrication of solid-state quantum devices. For such applications, precise information concerning the number of implanted ions and their final position within the implanted sample is crucial. In this work, we present an innovative method for the detection of single ions of MeV energy by using a sub-micrometer ultra-thin silicon carbide sensor operated as an in-beam counter of transmitted ions.

Performance of LGAD strip detectors for particle counting of therapeutic proton beams.

. The performance of silicon detectors with moderate internal gain, named low-gain avalanche diodes (LGADs), was studied to investigate their capability to discriminate and count single beam particles at high fluxes, in view of future applications for beam characterization and on-line beam monitoring in proton therapy..

Calibration method and performance of a time-of-flight detector to measure absolute beam energy in proton therapy.

Background: The beam energy is one of the most significant parameters in particle therapy since it is directly correlated to the particles' penetration depth inside the patient. Nowadays, the range accuracy is guaranteed by offline routine quality control checks mainly performed with water phantoms, 2D detectors with PMMA wedges, or multi-layer ionization chambers. The latter feature low sensitivity, slow collection time, and response dependent on external parameters, which represent limiting factors for the quality controls of beams delivered with fast energy switching modalities, as foreseen in future treatments.

Radiation Hardness Study of Silicon Carbide Sensors under High-Temperature Proton Beam Irradiations.

Silicon carbide (SiC), thanks to its material properties similar to diamond and its industrial maturity close to silicon, represents an ideal candidate for several harsh-environment sensing applications, where sensors must withstand high particle irradiation and/or high operational temperatures. In this study, to explore the radiation tolerance of SiC sensors to multiple damaging processes, both at room and high temperature, we used the Ion Microprobe Chamber installed at the Ruđer Bošković Institute (Zagreb, Croatia), which made it possible to expose small areas within the same device to different ion beams, thus evaluating and comparing effects within a single device. The sensors tested, developed jointly by STLab and SenSiC, are PIN diodes with ultrathin free-standing membranes, realized by means of a recently developed doping-selective electrochemical etching.

Accuracy assessment of the CNAO dose delivery system in the initial period of clinical activity and impact of later improvements on delivered dose distributions.

Purpose: A retrospective analysis of the dose delivery system (DDS) performances of the initial clinical operation at CNAO (Centro Nazionale di Adroterapia Oncologica) is reported, and compared with the dose delivery accuracy following the implementation of a position feedback control.

Methods: Log files and raw data of the DDS were analyzed for every field of patients treated with protons and carbon ions between January 2012 and April 2013 (~3800 fields). To investigate the DDS accuracy, the spot positions and the number of particles per spot measured by the DDS and prescribed by the treatment planning system were compared for each field.

A Monte Carlo approach to the microdosimetric kinetic model to account for dose rate time structure effects in ion beam therapy with application in treatment planning simulations.

Purpose: Advanced ion beam therapeutic techniques, such as hypofractionation, respiratory gating, or laser-based pulsed beams, have dose rate time structures which are substantially different from those found in conventional approaches. The biological impact of the time structure is mediated through the β parameter in the linear quadratic (LQ) model. The aim of this study was to assess the impact of changes in the value of the β parameter on the treatment outcomes, also accounting for noninstantaneous intrafraction dose delivery or fractionation and comparing the effects of using different primary ions.

A fully automatic computer aided diagnosis system for peripheral zone prostate cancer detection using multi-parametric magnetic resonance imaging.

Multiparametric (mp)-Magnetic Resonance Imaging (MRI) is emerging as a powerful test to diagnose and stage prostate cancer (PCa). However, its interpretation is a time consuming and complex feat requiring dedicated radiologists. Computer-aided diagnosis (CAD) tools could allow better integration of data deriving from the different MRI sequences in order to obtain accurate, reproducible, non-operator dependent information useful to identify and stage PCa.

Detection of prostate cancer index lesions with multiparametric magnetic resonance imaging (mp-MRI) using whole-mount histological sections as the reference standard.

Objective: To evaluate the sensitivity of multiparametric magnetic resonance imaging (mp-MRI) for detecting prostate cancer foci, including the largest (index) lesions.

Patients And Methods: In all, 115 patients with biopsy confirmed prostate cancer underwent mp-MRI before radical prostatectomy. A single expert radiologist recorded all prostate cancer foci including the index lesion 'blinded' to the pathologist's biopsy report.

A fully automatic multiscale 3-dimensional Hessian-based algorithm for vessel detection in breast DCE-MRI.

Objectives: The objectives of this study were to develop a fully automatic method for detecting blood vessels in dynamic contrast-enhanced magnetic resonance imaging of the breast on the basis of a multiscale 3-dimensional Hessian-based algorithm and to evaluate the improvement in reducing the number of vessel voxels incorrectly classified as parenchymal lesions by a computer-aided diagnosis (CAD) system.

Materials And Methods: The algorithm has been conceived to work on images obtained with different sequences, different acquisition parameters, such as the use of fat-saturation, and different contrast agents. The analysis was performed on 28 dynamic contrast-enhanced magnetic resonance imaging examinations, with 39 malignant (28 principal and 11 satellite) and 8 benign lesions, acquired at 2 centers using 2 different 1.

A fully automatic method to register the prostate gland on T2-weighted and EPI-DWI images.

Prostate adenocarcinoma (PCa) is the most frequent noncutaneous cancer among men in developed countries. Magnetic Resonance (MR) has been used to detect PCa and several clinical trials report on the accuracy of the test. Multiparametric MR imaging (mpMRI) is defined as the integration of information from different morphological and functional datasets.

Performance of a fully automatic lesion detection system for breast DCE-MRI.

Purpose: To describe and test a new fully automatic lesion detection system for breast DCE-MRI.

Materials And Methods: Studies were collected from two institutions adopting different DCE-MRI sequences, one with and the other one without fat-saturation. The detection pipeline consists of (i) breast segmentation, to identify breast size and location; (ii) registration, to correct for patient movements; (iii) lesion detection, to extract contrast-enhanced regions using a new normalization technique based on the contrast-uptake of mammary vessels; (iv) false positive (FP) reduction, to exclude contrast-enhanced regions other than lesions.

A fully automatic algorithm for segmentation of the breasts in DCE-MR images.

Automatic segmentation of the breast and axillary region is an important preprocessing step for automatic lesion detection in breast MR and dynamic contrast-enhanced-MR studies. In this paper, we present a fully automatic procedure based on the detection of the upper border of the pectoral muscle. Compared with previous methods based on thresholding, this method is more robust to noise and field inhomogeneities.