International Journal of Biomedical Imaging

A challenge in accurately identifying and classifying left ventricular hypertrophy (LVH) is distinguishing it from hypertrophic cardiomyopathy (HCM) and Fabry disease. The reliance on imaging techniques often requires the expertise of multiple specialists, including cardiologists, radiologists, and geneticists. This variability in the interpretation and classification of LVH leads to inconsistent diagnoses. LVH, HCM, and Fabry cardiomyopathy can be differentiated using T1 mapping on cardiac magnetic resonance imaging (MRI). However, differentiation between HCM and Fabry cardiomyopathy using echocardiography or MRI cine images is challenging for cardiologists. Our proposed system named the MRI short-axis view left ventricular hypertrophy classifier (MSLVHC) is a high-accuracy standardized imaging classification model developed using AI and trained on MRI short-axis (SAX) view cine images to distinguish between HCM and Fabry disease. The model achieved impressive performance, with an -score of 0.846, an accuracy of 0.909, and an AUC of 0.914 when tested on the Taipei Veterans General Hospital (TVGH) dataset. Additionally, a single-blinding study and external testing using data from the Taichung Veterans General Hospital (TCVGH) demonstrated the reliability and effectiveness of the model, achieving an -score of 0.727, an accuracy of 0.806, and an AUC of 0.918, demonstrating the model’s reliability and usefulness. This AI model holds promise as a valuable tool for assisting specialists in diagnosing LVH diseases.

Purpose. The Gram-positive Staphylococcus aureus bacterium is one of the leading causes of infection in humans. The lack of specific noninvasive techniques for diagnosis of staphylococcal infection together with the severity of its associated complications support the need for new specific and selective diagnostic tools. This work presents the successful synthesis of an immunotracer that targets the α-toxin released by S. aureus. Methods. [⁸⁹Zr]Zr-DFO-ToxAb was synthesized based on radiolabeling an anti-α-toxin antibody with zirconium-89. The physicochemical characterization of the immunotracer was performed by high-performance liquid chromatography (HPLC), radio-thin layer chromatography (radio-TLC), and electrophoretic analysis. Its diagnostic ability was evaluated in vivo by positron emission tomography/computed tomography (PET/CT) imaging in an animal model of local infection-inflammation (active S. aureus vs. heat-killed S. aureus) and infective osteoarthritis. Results. Chemical characterization of the tracer established the high radiochemical yield and purity of the tracer while maintaining antibody integrity. In vivo PET/CT image confirmed the ability of the tracer to detect active foci of S. aureus. Those results were supported by ex vivo biodistribution studies, autoradiography, and histology, which confirmed the ability of [⁸⁹Zr]Zr-DFO-ToxAb to detect staphylococcal infectious foci, avoiding false-positives derived from inflammatory processes. Conclusions. We have developed an immuno-PET tracer capable of detecting S. aureus infections based on a radiolabeled antibody specific for the staphylococcal alpha toxins. The in vivo assessment of [⁸⁹Zr]Zr-DFO-ToxAb confirmed its ability to selectively detect staphylococcal infectious foci, allowing us to discern between infectious and inflammatory processes.

Background. Ferumoxytol (Ferahame, AMAG Pharmaceuticals, Waltham, MA) is increasingly used off-label as an MR contrast agent due to its relaxivity and safety profiles. However, its potent T2 relaxivity limits achievable T1-weighted positive contrast and leads to artifacts in standard MRI protocols. Optimization of protocols for ferumoxytol deployment is necessary to realize its potential. Methods. We present first-in-human clinical results of the Quantitative Ultrashort Time-to-Echo Contrast Enhanced (QUTE-CE) MRA technique using the superparamagnetic iron oxide nanoparticle agent ferumoxytol for vascular imaging of the head/brain in 15 subjects at 3.0T. The QUTE-CE MRA method was implemented on a 3T scanner using a stack-of-spirals 3D Ultrashort Time-to-Echo sequence. Time-of-flight MRA and standard TE T1-weighted (T1w) images were also collected. For comparison, gadolinium-enhanced blood pool phase images were obtained retrospectively from clinical practice. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and intraluminal signal heterogeneity (ISH) were assessed and compared across approaches with Welch’s two-sided -test. Results. Fifteen volunteers ( years old, 9 women) participated. QUTE-CE MRA provided high-contrast snapshots of the arterial and venous networks with lower intraluminal heterogeneity. QUTE-CE demonstrated significantly higher SNR (), blood-tissue CNR (), and lower ISH () compared to ferumoxytol T1-weighted (; ; , respectively) and time-of-flight (; ; , respectively), with in each comparison. The high CNR increased the depth of vessel visualization. Vessel lumina were captured with lower heterogeneity. Conclusion. Quantitative Ultrashort Time-to-Echo Contrast-Enhanced MR angiography provides approximately 5-fold superior contrast with fewer artifacts compared to other contrast-enhanced vascular imaging techniques using ferumoxytol or gadolinium, and to noncontrast time-of-flight MR angiography, for clinical vascular imaging. This trial is registered with NCT03266848.

The kidney’s microstructure, which comprises a highly convoluted tubular and vascular network, can only be partially revealed using classical 2D histology. Considering that the kidney’s microstructure is closely related to its function and is often affected by pathologies, there is a need for powerful and high-resolution 3D imaging techniques to visualize the microstructure. Here, we present how cryogenic contrast-enhanced microCT (cryo-CECT) allowed 3D visualization of glomeruli, tubuli, and vasculature. By comparing different contrast-enhancing staining agents and freezing protocols, we found that the preferred sample preparation protocol was the combination of staining with 1:2 hafnium(IV)-substituted Wells-Dawson polyoxometalate and freezing by submersion in isopentane at −78°C. This optimized protocol showed to be highly sensitive, allowing to detect small pathology-induced microstructural changes in a mouse model of mild trauma-related acute kidney injury after thorax trauma and hemorrhagic shock. In summary, we demonstrated that cryo-CECT is an effective 3D histopathological tool that allows to enhance our understanding of kidney tissue microstructure and their related function.

Purpose. This study is aimed at evaluating the efficacy of the gradient-spin echo- (GraSE-) based short tau inversion recovery (STIR) sequence (GraSE-STIR) in cardiovascular magnetic resonance (CMR) imaging compared to the conventional turbo spin echo- (TSE-) based STIR sequence, specifically focusing on image quality, specific absorption rate (SAR), and image acquisition time. Methods. In a prospective study, we examined forty-four normal volunteers and seventeen patients referred for CMR imaging using conventional STIR and GraSE-STIR techniques. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), image quality, signal intensity (SI) ratio, SAR, and image acquisition time were compared between both sequences. Results. GraSE-STIR showed significant improvements in image quality ( vs. , ) and cardiac motion artifact reduction (7 vs. 18 out of 53, ) compared to conventional STIR. Furthermore, the acquisition time ( vs. seconds, ) and the local torso SAR (<13% vs. <17%, ) were significantly lower for GraSE-STIR compared to conventional STIR in short-axis plan. However, no significant differences were shown in SI ratio (), SNR (), CNR (), and SAR () between these two sequences. Conclusions. GraSE-STIR offers notable advantages over conventional STIR sequence, with improved image quality, reduced motion artifacts, and shorter acquisition times. These findings highlight the potential of GraSE-STIR as a valuable technique for routine clinical CMR imaging.

Background. MRI is an important tool for accurate detection and targeted biopsy of prostate lesions. However, the imaging appearances of some prostate cancers are similar to those of the surrounding normal tissue on MRI, which are referred to as MRI-invisible prostate cancers (MIPCas). The detection of MIPCas remains challenging and requires extensive systematic biopsy for identification. In this study, we developed a weakly supervised UNet (WSUNet) to detect MIPCas. Methods. The study included 777 patients (training set: 600; testing set: 177), all of them underwent comprehensive prostate biopsies using an MRI-ultrasound fusion system. MIPCas were identified in MRI based on the Gleason grade (≥7) from known systematic biopsy results. Results. The WSUNet model underwent validation through systematic biopsy in the testing set with an AUC of 0.764 (95% CI: 0.728-0.798). Furthermore, WSUNet exhibited a statistically significant precision improvement of 91.3% () over conventional systematic biopsy methods in the testing set. This improvement resulted in a substantial 47.6% () decrease in unnecessary biopsy needles, while maintaining the same number of positively identified cores as in the original systematic biopsy. Conclusions. In conclusion, the proposed WSUNet could effectively detect MIPCas, thereby reducing unnecessary biopsies.