Objective. This study aims to assess the composition of scattered particles generated in proton therapy for tumors situated proximal to some titanium (Ti) dental implants. The investigation involves decomposing the mixed field and recording Linear Energy Transfer (LET) spectra to quantify the influence of metallic dental inserts located behind the tumor. Approach. A therapeutic conformal proton beam was used to deliver the treatment plan to an anthropomorphic head phantom with two types of implants inserted in the target volume (made of Ti and plastic, respectively). The scattered radiation resulted during the irradiation was detected by a hybrid semiconductor pixel detector MiniPIX Timepix3 that was placed distal to the Spread-out Bragg peak. Visualization and field decomposition of stray radiation were generated using algorithms trained in particle recognition based on artificial intelligence neural networks (AI NN). Spectral sensitive aspects of the scattered radiation were collected using two angular positions of the detector relative to the beam direction: 0° and 60°. Results. Using AI NN, 3 classes of particles were identified: protons, electrons & photons, and ions & fast neutrons. Placing a Ti implant in the beam’s path resulted in predominantly electrons and photons, contributing 52.2% of the total number of detected particles, whereas for plastic implants, the contribution was 65.4%. Scattered protons comprised 45.5% and 31.9% with and without metal inserts, respectively. The LET spectra were derived for each group of particles identified, with values ranging from 0.01 to 7.5 keV μm⁻¹ for Ti implants/plastic implants. The low-LET component was primarily composed of electrons and photons, while the high-LET component corresponded to protons and ions. Significance. This method, complemented by directional maps, holds the potential for evaluating and validating treatment plans involving stray radiation near organs at risk, offering precise discrimination of the mixed field, and enhancing in this way the LET calculation.

The primary aim of this review is to summarize current evidence from clinical and pre-clinical studies on endogenous molecular biomarkers associated with radiosensitivity and radioresistance in cervical cancer, including patients treated with photon-based radiotherapy, cervical cancer cell lines, and xenograft models, and to evaluate the association of these biomarkers with radiotherapy response, residual disease, recurrence and survival, and experimental measures of radiosensitivity. A systematic literature review was conducted for studies published over the last 10 years that evaluated associations between genomic, epigenetic, or protein biomarkers and radiotherapy response or survival outcomes in cervical cancer. Eligible studies included in the current analysis summarize clinical, translational, and pre-clinical studies in correlation with photon-based radiotherapy. Research focusing exclusively on non-coding RNAs, exogenous radiosensitizers, or non-photon modalities was excluded. In total, 112 studies were identified, and 46 of them met the inclusion criteria. The identified biomarkers clustered into several key biological processes: DNA damage response and cell cycle regulation, cancer stemness, hypoxia and microenvironment, epigenetic and transcriptional regulation, and signaling pathways, including exosome-mediated communication. Most markers were linked to radioresistance and adverse outcomes, whereas a smaller subset was associated with increased radiosensitivity. A limited group of biomarkers was linked to clinical outcomes such as local control, residual disease, or survival, and emerging multi-marker protein signatures suggested that combinatorial approaches may outperform single-marker strategies. Radiosensitivity in cervical cancer is regulated by a network of biological pathways. Validated, integrated biomarker panels that capture DNA repair proficiency, stemness, hypoxia adaptation, and key signaling pathways are needed to improve risk stratification and enable biomarker-guided radiosensitization.