Diagnosis and prognosis of abnormal cardiac scintigraphy uptake suggestive of cardiac amyloidosis using artificial intelligence: a retrospective, international, multicentre, cross-tracer development and validation study.

BACKGROUND: The diagnosis of cardiac amyloidosis can be established non-invasively by scintigraphy using bone-avid tracers, but visual assessment is subjective and can lead to misdiagnosis. We aimed to develop and validate an artificial intelligence (AI) system for standardised and reliable screening of cardiac amyloidosis-suggestive uptake and assess its prognostic value, using a multinational database of 99mTc-scintigraphy data across multiple tracers and scanners. METHODS: In this retrospective, international, multicentre, cross-tracer development and validation study, 16 241 patients with 19 401 scans were included from nine centres: one hospital in Austria (consecutive recruitment Jan 4, 2010, to Aug 19, 2020), five hospital sites in London, UK (consecutive recruitment Oct 1, 2014, to Sept 29, 2022), two centres in China (selected scans from Jan 1, 2021, to Oct 31, 2022), and one centre in Italy (selected scans from Jan 1, 2011, to May 23, 2023). The dataset included all patients referred to whole-body 99mTc-scintigraphy with an anterior view and all 99mTc-labelled tracers currently used to identify cardiac amyloidosis-suggestive uptake. Exclusion criteria were image acquisition at less than 2 h (99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid, 99mTc-hydroxymethylene diphosphonate, and 99mTc-methylene diphosphonate) or less than 1 h (99mTc-pyrophosphate) after tracer injection and if patients' imaging and clinical data could not be linked. Ground truth annotation was derived from centralised core-lab consensus reading of at least three independent experts (CN, TT-W, and JN). An AI system for detection of cardiac amyloidosis-associated high-grade cardiac tracer uptake was developed using data from one centre (Austria) and independently validated in the remaining centres. A multicase, multireader study and a medical algorithmic audit were conducted to assess clinician performance compared with AI and to evaluate and correct failure modes. The system's prognostic value in predicting mortality was tested in the consecutively recruited cohorts using cox proportional hazards models for each cohort individually and for the combined cohorts. FINDINGS: The prevalence of cases positive for cardiac amyloidosis-suggestive uptake was 142 (2%) of 9176 patients in the Austrian, 125 (2%) of 6763 patients in the UK, 63 (62%) of 102 patients in the Chinese, and 103 (52%) of 200 patients in the Italian cohorts. In the Austrian cohort, cross-validation performance showed an area under the curve (AUC) of 1·000 (95% CI 1·000-1·000). Independent validation yielded AUCs of 0·997 (0·993-0·999) for the UK, 0·925 (0·871-0·971) for the Chinese, and 1·000 (0·999-1·000) for the Italian cohorts. In the multicase multireader study, five physicians disagreed in 22 (11%) of 200 cases (Fleiss' kappa 0·89), with a mean AUC of 0·946 (95% CI 0·924-0·967), which was inferior to AI (AUC 0·997 [0·991-1·000], p=0·0040). The medical algorithmic audit demonstrated the system's robustness across demographic factors, tracers, scanners, and centres. The AI's predictions were independently prognostic for overall mortality (adjusted hazard ratio 1·44 [95% CI 1·19-1·74], p<0·0001). INTERPRETATION: AI-based screening of cardiac amyloidosis-suggestive uptake in patients undergoing scintigraphy was reliable, eliminated inter-rater variability, and portended prognostic value, with potential implications for identification, referral, and management pathways. FUNDING: Pfizer.

Toscana virus central nervous system infections in southern Italy.

Toscana virus was detected by reverse transcription-nested PCR in 5.6% of cerebrospinal fluid (CSF) samples from patients with meningitis and encephalitis during the summer in southern Italy. The central nervous system infections were associated with young adults and with a substantially benign clinical course. Presenting features and CSF findings are also discussed in the present report.

No evidence of in vitro and in vivo porcine endogenous retrovirus infection after plasmapheresis through the AMC-bioartificial liver.

BACKGROUND: Currently a number of bioartificial livers (BAL) based on porcine liver cells have been developed as a treatment to bridge acute liver failure patients to orthotopic liver transplantation or liver regeneration. These xenotransplantation related treatments hold the risk of infection of treated patients by porcine endogenous retrovirus (PERV) released from the porcine cells, as in vitro infection experiments and transplantations in immunocompromised mice have shown that PERV is able to infect human cells. The Academic Medical Center (AMC)-BAL, unlike other BALs, is characterized by direct contact between porcine liver cells and human plasma, and might therefore be permissive for PERV transfer. METHODS: Prior to a clinical phase I trial, human plasma perfused through the AMC-BAL was investigated for PERV DNA and RNA. Moreover productive infectivity was analyzed by exposing the plasma to HEK-293 cells that were subsequently tested for PERV DNA, PERV RNA and reverse transcriptase activity. RESULTS: Although PERV DNA was detected in the perfused plasma, no productive infectivity was detected. Consequently fourteen patients were treated with the AMC-BAL and monitored for PERV transmission. Immediately after treatment the plasma of the patients was positive for PERV DNA, most probably due to porcine liver cell lysis. The PERV DNA was cleared within 2 weeks post-treatment and no PERV RNA was detected. No productive infectivity in human embryonic kidney (HEK)-293 cells exposed to plasma of treated patients was detectable. CONCLUSION: To conclude, no release of infective PERV particles from the AMC-BAL was observed. Therefore we consider the AMC-BAL as safe, however careful surveillance of patients will be continued.