Russell W. Chan

Chronic liver and kidney diseases frequently coexist, but their assessment typically requires separate clinical workflows involving serum-based estimated glomerular filtration rate (eGFR) testing and liver elastography-based controlled attenuation parameter (CAP). Electrical impedance tomography (EIT) has recently shown promise for providing portable, non-invasive proxies for both reference measurements. However, existing multi-organ EIT assessment still requires different acquisition protocols for each organ. To simplify this procedure, we assessed the feasibility of a single-plane EIT framework for reconstructing organ-specific images and estimating liver and kidney health from one abdominal belt placement. Across diverse abdominal belt locations, opposite-plane deviation was significantly greater for eGFR _EIT estimates (2.92%; IQR, 0.46-12.53%) than for CAP _EIT estimates (0.94%; IQR, 0.66-1.70%) (p < 0.01). For both organs, compared to images acquired at the conventional organ-specific planes, image correlation significantly decreased (both, p < 0.05) and normalized root mean squared error significantly increased (both, p < 0.05) at the furthest imaging plane, with these differences being numerically larger for the kidney. Together, these results supported the kidney plane as the preferred location for multi-organ assessment. Test-retest evaluation after belt removal and reapplication demonstrated that the correlation between two repeated CAP _EIT estimates was just as strong at the kidney plane (R ² = 0.98, p < 0.001) as it was at the conventional liver plane (R ² = 0.97, p < 0.001). Finally, in an independent clinical cohort, kidney-plane CAP _EIT estimates were significantly higher in participants with a high metabolic liver-risk profile (i.e. diabetes and high blood pressure) (p < 0.005). CAP _EIT estimates also distinguished high and low metabolic risk groups with an AUC of 0.756. Together, these findings support the feasibility of a portable multi-organ EIT imaging framework capable of extracting complementary liver and kidney information from a single belt placement.

Chronic cardiopulmonary, metabolic, and renal diseases represent an immense global health burden, yet access to organ-specific diagnostics remains limited outside of hospitals. Most clinical assessments rely on imaging or laboratory testing that is costly, infrastructure-dependent, and impractical for large-scale or longitudinal monitoring in community settings. Here, we introduce VitoCheck, a compact, user-friendly electrical impedance tomography (EIT) platform that provides non-invasive evaluation of lung, heart, liver, and kidney function within minutes. We first demonstrate system stability, spatial specificity, and spectral sensitivity through controlled phantom studies. We then validate VitoCheck in clinical cohorts by demonstrating accurate EIT-based predictions of standard diagnostic metrics, including spirometry-derived forced expiratory volumes, echocardiography-derived ejection fraction, ultrasound-derived liver fat scores, and blood serum-derived kidney filtration. User feedback further highlights the rapid scan workflow that supports deployment by non-specialists in decentralized environments. By combining portable and easy-to-use hardware with quantitative organ health analytics, VitoCheck enables scalable screening and proactive disease management for use in remote and out-of-clinic care.

Accessibility of diagnostic screening and treatment monitoring devices for respiratory diseases is critical in promoting healthcare and reducing sudden complications and mortality. Spirometry is the standard for diagnosing and monitoring several lung diseases. However, it lacks regional assessment capabilities necessary for detecting subtle regional changes in certain diseases. It also requires challenging breathing maneuvers difficult for elderlies, children, and diseased patients. Here, we actualized an affordable, portable, and self-administrable electrical impedance tomography (EIT) system for home-based lung function assessment and telemedicine. Through simultaneous EIT-spirometry trials on healthy subjects, we demonstrated that our device can predict spirometry indicators over a wide range and can provide regional mapping of these indicators. We further developed a close-to-effortless breathing paradigm and tested it by longitudinally monitoring a COVID-19 discharged subject and two healthy controls with results suggesting the paradigm can detect initial deterioration followed by recovery. Overall, the EIT system can be widely applicable for lung function screening and monitoring both at homes and clinics.