Letizia Morelli

Background: Sacral chordoma (SC) is a rare and locally aggressive tumor, characterized by a high risk of local recurrence (LR). Advanced imaging biomarkers capturing tumor heterogeneity and treatment response may help refine patient stratification and improve outcomes. Purpose: This study aims to explore the potential of microstructural parameters and habitat analysis derived from diffusion‐weighted MRI (DW‐MRI) to characterize intratumoral heterogeneity, assess treatment‐induced changes, following carbon ion radiotherapy (CIRT), and investigate their association with recurrence patterns in SC patients. Methods: A retrospective analysis was performed on 40 SC patients treated with CIRT. Microstructural parameters—cell radius ( R ), eccentricity (ecc), diffusion coefficient ( D ), cell volume fraction (vf), and apparent cellularity (ρ‐app)—were estimated from DW‐MRI using a computational model based on Monte Carlo simulations. Longitudinal changes were assessed from DW‐MRI scans acquired at baseline, first follow‐up (3 months after CIRT), and, for LR patients, at the time of recurrence. Habitat imaging analysis was performed by applying K ‐means clustering ( k = 2) independently to each map of the six microstructural parameters. A joint clustering approach was then used to combine these binary maps, resulting in 64 unique microstructural configurations (2 ⁶ habitats). The spatial distribution of these habitats was quantified within the gross tumor volume (GTV) and recurrence regions. Associations with clinical outcomes were explored by analyzing habitat fractions in patients with early (early‐LR) vs. late recurrence (late‐LR), and by comparing recurrences predominantly located within the high‐dose clinical target volume irradiated during CIRT (in‐field‐LR) vs. those partially outside the target (marginal‐LR). Statistical tests, multiregional spatial interaction (MSI) matrix analysis, Cox regression, Spearman correlation and Kaplan–Meier survival analyses were performed. Results: Treatment‐induced changes in microstructural parameters were statistically significant in both local control (LC) and LR patients, characterized by an increase in cell radius, eccentricity, ADC, and diffusion, and a concomitant reduction in cell volume fraction and apparent cellularity. This pattern suggested a reduction in cell density and increased tissue disorganization, likely reflecting CIRT‐induced cell damage and extracellular matrix remodeling. Habitat analysis revealed distinct microstructural configurations associated with clinical outcome. A favorable microstructural pattern—high diffusivity and low cellularity—was predominantly found in LC patients (HABITAT47_212221), whereas more aggressive configurations (low diffusivity and high cellularity) were enriched in LR patients (HABITAT26_122112 and HABITAT28_122122). Univariate Cox regression identified these high‐risk habitats as significantly associated with recurrence (hazard ratio > 1, p ‐value < 0.05). Moreover, habitat fractions showed a progressive trend across recurrence risk subgroups (LC, late‐LR, early‐LR; LC, in‐field‐LR, marginal‐LR), while spatial analyses revealed increased co‐localization of high‐risk habitats in LR patients based on MSI matrix analysis. Finally, Kaplan–Meier analysis based on hazard ratios predicted at first follow‐up using Cox models trained on baseline habitat fractions revealed significant differences in progression‐free survival. Conclusion: This study demonstrates the potential of DW‐MRI‐derived microstructural parameters and habitat imaging to capture intratumoral heterogeneity, assess treatment‐induced microstructural changes, and identify high‐risk patterns associated with LR in SC patients treated with CIRT. These findings support the integration of microstructural and habitat‐based imaging as a non‐invasive tool for risk stratification and personalized treatment planning in CIRT for SC.

Electrical impedance tomography (EIT) is a medical imaging technique based on the injection of a current or voltage pattern through electrodes on the skin of the patient, and on the reconstruction of the internal conductivity distribution from the voltages collected by the electrodes. Compared to other imaging techniques, EIT shows significant advantages: it does not use ionizing radiation, is non-invasive and is characterized by high temporal resolution. Moreover, its low cost and high portability make it suitable for real-time, bedside monitoring. However, EIT is also characterized by some technical limitations that cause poor spatial resolution. The possibility to design wearable devices based on EIT has recently given a boost to this technology. In this paper we reviewed EIT physical principles, hardware design and major clinical applications, from the classical to a wearable setup. A wireless and wearable EIT system seems a promising frontier of this technology, as it can both facilitate making clinical measurements and open novel scenarios to EIT systems, such as home monitoring.

Carbon Ion Radiotherapy (CIRT) is one of the most promising therapeutic options to reduce Local Recurrence (LR) in Sacral Chordomas (SC). The aim of this work is to compare the performances of survival models fed with dosiomics features and conventional DVH metrics extracted from relative biological effectiveness (RBE)-weighted dose (D_RBE) and dose-averaged Linear Energy Transfer (LET_d) maps, towards the identification of possible prognostic factors for LR in SC patients treated with CIRT. This retrospective study included 50 patients affected by SC with a focus on patients that presented a relapse in a high-dose region. Survival models were built to predict both LR and High-Dose Local Recurrencies (HD-LR). The models were evaluated through Harrell Concordance Index (C-index) and patients were stratified into high/low-risk groups. Local Recurrence-free Kaplan–Meier curves were estimated and evaluated through log-rank tests. The model with highest performance (median(interquartile-range) C-index of 0.86 (0.22)) was built on features extracted from LET_d maps, with D_RBE models showing promising but weaker results (C-index of 0.83 (0.21), 0.80 (0.21)). Although the study should be extended to a wider patient population, LET_d maps show potential as a prognostic factor for SC HD-LR in CIRT, and dosiomics appears to be the most promising approach against more conventional methods (e.g., DVH-based).

Skull-base chordoma (SBC) is a rare tumour whose molecular and radiological characteristics are still being investigated. In neuro-oncology microstructural imaging techniques, like diffusion-weighted MRI (DW-MRI), have been widely investigated, with the apparent diffusion coefficient (ADC) being one of the most used DW-MRI parameters due to its ease of acquisition and computation. ADC is a potential biomarker without a clear link to microstructure. The aim of this work was to derive microstructural information from conventional ADC, showing its potential for the characterisation of skull-base chordomas. Sixteen patients affected by SBC, who underwent conventional DW-MRI were retrospectively selected. From mono-exponential fits of DW-MRI, ADC maps were estimated using different sets of b-values. DW-MRI signals were simulated from synthetic substrates , which mimic the cellular packing of a tumour tissue with well-defined microstructural features. Starting from a published method, an error-driven procedure was evaluated to improve the estimates of microstructural parameters obtained through the simulated signals. A quantitative description of the tumour microstructure was then obtained from the DW-MRI images. This allowed successfully differentiating patients according to histologically-verified cell proliferation information.Clinical Relevance — The impact on cancer management derives from the expected improvement of radiation treatment quality tailored to a patient-specific non-invasive description of tumour microstructure.