Medical Physics, AI and Neurotechnology · University of Rome Tor Vergata

fismed@uniroma2.it

FISMED / PEOPLE

Antonio Canichella

Technical Officer · University of Rome Tor Vergata

BACKGROUND

Biography

Antonio Canichella is a technical officer at the University of Rome Tor Vergata. His work includes electronic measurements and the design of hardware and software for acquiring signals from medical instruments and physiological sensors. He develops tools for waveform analysis and web applications, and contributes technical expertise to the group's focused-ultrasound laboratory.

RESEARCH & EXPERTISE

Areas of expertise

  • Electronic measurements
  • Signal acquisition
  • Waveform analysis
  • Scientific software

RESEARCH OUTPUT

Selected publications

  1. Ex vivo localization of wireless implantable microdevice using high-resolution 3D imaging techniques.Frontiers in bioengineering and biotechnology · 2026
    The CROSSBRAIN EU project aims to address the heterogeneous nature of brain pathologies by developing wireless implantable microbots (µBots, planned dimensions 100 × 100 × 100 μm3) for highly localized neuromodulation. These devices are designed to precisely modulate brain activity with minimal invasiveness, enabling targeted resolution of specific spatiotemporal events, capabilities not currently achieved by existing neuromodulation technologies. A crucial step involves visualizing and ensuring the optimal placement of the µBots in the brain tissue, to study their functionality after implantation. In this preliminary ex vivo study, we used non-functional µBot silicon (Si) dummies matching the lateral dimensions of the intended µBots, with reduced thickness (100 × 100 × 50 μm3) to simplify fabrication and handling. Due to the intrinsic MRI incompatibility of the µBot platform, encompassing both the dummies used in this study and the future functional devices under development, and the limitations of standard histological approaches in reliably identifying and preserving the implant site during processing, we developed an integrated imaging workflow combining 2D and 3D techniques. While standard histological methods and tissue clearing presented substantial limitations in preserving the position of the dummies within the brain tissue, combining histological techniques with 3D X-ray tomography provided a robust strategy. In particular, synchrotron radiation-based X-ray Phase Contrast Tomography (XPCT), with its intrinsic high contrast and resolution, enabled detailed visualization of dummies within the surrounding vascular and cellular architecture. In contrast, conventional micro-Computed Tomography (micro-CT), although more widely accessible, enabled non-destructive guidance for targeted sectioning. Importantly, and in line with the scope of a Brief Research Report, this study presents a preliminary but technically robust investigation conducted within the CROSSBRAIN project, aimed at identifying and establishing an optimized imaging strategy for the visualization of implanted µBots in brain tissue. This methodological framework is intended as an initial step toward future in vivo studies, in which the validated imaging pipeline will be applied to track both dummy and functional devices and to enable subsequent evaluation of foreign body response under physiologically relevant conditions. This ex vivo workflow therefore provides the essential technical foundation for such future investigations and supports the clear positioning of this work as a feasibility and optimization study. This approach could be particularly valuable for new generations of implantable technologies incompatible with MRI and could support future development of personalized neuromodulation therapies by enabling precise device localization and structural tissue assessment.
  2. Non-Invasive Detection of Mechanical Alternans Utilizing Photoplethysmography.IEEE journal of biomedical and health informatics · 2019
    BACKGROUND AND SIGNIFICANCE: Mechanical alternans (MA) is a biomarker associated with mortality and life-threatening arrhythmias in heart failure patients. Despite showing prognostic value, its use is limited by the requirement of measuring the continuous blood pressure (BP), which is costly and impractical. OBJECTIVE: To develop and test, for the first time, non-invasive MA surrogates based on photoplethysmography (PPG). METHODS: Continuous BP and PPG were recorded during clinical procedures and tests in 35 patients. MA was induced either by ventricular pacing (Group A, N = 19) or exercise (Group B, N = 16). MA was categorized as sustained or intermittent if MA episodes were observed in at least 20 or between 12 and 20 consecutive beats, respectively. Eight features characterizing the pulse morphology were derived from the PPG, and MA surrogates were evaluated. RESULTS: Sustained alternans was observed in 9 patients (47%) from Group A, whereas intermittent alternans was observed in 13 patients (68%) from Group A and in 10 patients (63%) from Group B. The PPG-based MA surrogate showing the highest accuracy, V'M, was based on the maximum of the first derivative of the PPG pulse. It detected both sustained and intermittent MA with 100% sensitivity and 100% specificity in Group A and intermittent MA with 100% sensitivity and 83% specificity in Group B. Furthermore, the magnitudes of MA and its PPG-based surrogate were linearly correlated (R2 = 0.83, p < 0.001). CONCLUSION: MA can be accurately identified non-invasively through PPG analysis. This may have important clinical implications for risk stratification and remote monitoring.
  3. Prediction of postoperative outcomes using intraoperative hemodynamic monitoring data.Scientific reports · 2017
    Major surgeries can result in high rates of adverse postoperative events. Reliable prediction of which patient might be at risk for such events may help guide peri- and postoperative care. We show how archiving and mining of intraoperative hemodynamic data in orthotopic liver transplantation (OLT) can aid in the prediction of postoperative 180-day mortality and acute renal failure (ARF), improving upon predictions that rely on preoperative information only. From 101 patient records, we extracted 15 preoperative features from clinical records and 41 features from intraoperative hemodynamic signals. We used logistic regression with leave-one-out cross-validation to predict outcomes, and incorporated methods to limit potential model instabilities from feature multicollinearity. Using only preoperative features, mortality prediction achieved an area under the receiver operating characteristic curve (AUC) of 0.53 (95% CI: 0.44-0.78). By using intraoperative features, performance improved significantly to 0.82 (95% CI: 0.56-0.91, P = 0.001). Similarly, including intraoperative features (AUC = 0.82; 95% CI: 0.66-0.94) in ARF prediction improved performance over preoperative features (AUC = 0.72; 95% CI: 0.50-0.85), though not significantly (P = 0.32). We conclude that inclusion of intraoperative hemodynamic features significantly improves prediction of postoperative events in OLT. Features strongly associated with occurrence of both outcomes included greater intraoperative central venous pressure and greater transfusion volumes.
  4. Heart rate variability in untreated newly diagnosed temporal lobe epilepsy: Evidence for ictal sympathetic dysregulation.Epilepsia · 2016
    OBJECTIVE: To compare heart rate variability (HRV) parameters in newly diagnosed and untreated temporal lobe epilepsy (TLE) between the interictal, preictal, ictal, and postictal states. METHODS: HRV parameters were extracted from single-lead electrocardiography data collected during video-electroencephalography (EEG) recordings from 14 patients with newly diagnosed TLE in a resting, awake, and supine state. HRV parameters in the time and frequency domains included low frequency (LF), high frequency (HF), standard deviation of all consecutive R wave intervals (SDNN), and square root of the mean of the sum of the squares of differences between adjacent R wave intervals (RMSSD). Cardiovagal index (CVI), cardiosympathetic index (CSI), and approximate entropy (ApEn) were also studied. RESULTS: Frequency domain analysis showed significantly higher preictal, ictal, and postictal LF/HF ratio compared to the interictal state. Similarly, the LF component increased progressively and was significantly higher during the ictal state compared to interictal and preictal states. RR interval values were lower in the ictal state compared to basal and preictal states and in the postictal state compared to the preictal state. Interictal RMSSD was significantly higher compared to all other states, and ictal SDNN was significantly higher compared to all other states. Ictal CSI was significantly higher compared to preictal and interictal states, whereas preictal CVI was lower than in basal and ictal states. In addition, ictal ApEn was significantly lower than interictal and preictal ApEn. Interictal CVI was lower in left TLE compared to right TLE. In addition, in left TLE, ictal CVI was higher than interictal CVI, whereas in right TLE, CVI was lower in the preictal state compared to all other states. SIGNIFICANCE: Our data suggest an ictal sympathetic overdrive with partial recovery in the postictal state. Higher sympathetic tone and vagal tone imbalance may induce early autonomic dysfunction and increase cardiovascular risk in patients affected by TLE.
  5. Intraoperative hemodynamics predict postoperative mortality in orthotopic liver transplantation.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2015
    Liver transplantation remains the only curative treatment option for a variety of end-stage liver diseases. Prediction of major adverse events following surgery has traditionally focused on static predictors that are known prior to surgery. The effects of intraoperative management can now be explored due to the archiving of high-resolution monitoring data. We extracted intraoperative hemodynamic trend data of 55 patients undergoing orthotopic liver transplantation (OLT) and computed 12 features from the systolic arterial blood pressure (ABP), cardiac index, central venous pressure (CVP), and stroke volume variation (SVV) signals. Using a logistic regression classifier with a leave-one-out cross-validation procedure, we selected subsets of these features to predict mortality up to 180 days after surgery. Best performance was achieved with a combination of 3 features - median absolute deviation (MAD) of ABP, median CVP, and time spent with SVV <; 10% - reaching an area under the receiver-operating characteristic (or c-statistic) of 0.808. Odds ratios (OR) computed from the coefficients of the multivariate logistic regression model constructed from these features showed that greater time spent with SVV <; 10% (OR = 0.981 min(-1), p = 0.001) and greater MAD of systolic ABP (OR = 0.696 mmHg(-1), p = 0.026) were significantly associated with survival. Adding preoperative measures such as age and serum concentrations of albumin, bilirubin, and creatinine failed to improve performance of the prediction model. These results show that the course of intraoperative hemodynamics can predict 180-day mortality after OLT.
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