Identification of a robust DNA methylation signature for Fanconi anemia.

Fanconi anemia (FA) is a clinically variable and genetically heterogeneous cancer-predisposing disorder representing the most common bone marrow failure syndrome. It is caused by inactivating predominantly biallelic mutations involving >20 genes encoding proteins with roles in the FA/BRCA DNA repair pathway. Molecular diagnosis of FA is challenging due to the wide spectrum of the contributing gene mutations and structural rearrangements. The assessment of chromosomal fragility after exposure to DNA cross-linking agents is generally required to definitively confirm diagnosis. We assessed peripheral blood genome-wide DNA methylation (DNAm) profiles in 25 subjects with molecularly confirmed clinical diagnosis of FA (FANCA complementation group) using Illumina's Infinium EPIC array. We identified 82 differentially methylated CpG sites that allow to distinguish subjects with FA from healthy individuals and subjects with other genetic disorders, defining an FA-specific DNAm signature. The episignature was validated using a second cohort of subjects with FA involving different complementation groups, documenting broader genetic sensitivity and demonstrating its specificity using the EpiSign Knowledge Database. The episignature properly classified DNA samples obtained from bone marrow aspirates, demonstrating robustness. Using the selected probes, we trained a machine-learning model able to classify EPIC DNAm profiles in molecularly unsolved cases. Finally, we show that the generated episignature includes CpG sites that do not undergo functional selective pressure, allowing diagnosis of FA in individuals with reverted phenotype due to gene conversion. These findings provide a tool to accelerate diagnostic testing in FA and broaden the clinical utility of DNAm profiling in the diagnostic setting.

Ultrathin Gd-Oxide Nanosheet as Ultrasensitive Companion Diagnostic Tool for MR Imaging and Therapy of Submillimeter Microhepatocellular Carcinoma.

Early stage hepatocellular carcinoma (HCC) presents a formidable challenge in clinical settings due to its asymptomatic progression and the limitations of current imaging techniques in detecting micro-HCC lesions. Addressing this critical issue, we introduce a novel ultrathin gadolinium-oxide (Gd-oxide) nanosheet-based platform with heightened sensitivity for high-field MRI and as a therapeutic agent for HCC. Synthesized via a digestive ripening process, these Gd-oxide nanosheets exhibit an exceptional acid-responsive profile. The integration of the ultrathin Gd-oxide with an acid-responsive polymer creates an ultrasensitive high-field MRI probe, enabling the visualization of submillimeter-sized tumors with superior sensitivity. Our research underscores the ultrasensitive probe's efficacy in the treatment of orthotopic HCC. Notably, the ultrasensitive probe functions dually as a companion diagnostic tool, facilitating simultaneous imaging and therapy with real-time treatment monitoring capabilities. In conclusion, this study showcases an innovative companion diagnostic tool that holds promise for the early detection and effective treatment of micro-HCC.

NanoImprint: A DNA methylation tool for clinical interpretation and diagnosis of common imprinting disorders using nanopore long-read sequencing.

INTRODUCTION: Long-read whole genome sequencing like Oxford Nanopore Technology, is increasingly being introduced in clinical settings. With its ability to simultaneously call sequence variation and DNA modifications including 5-methylcytosine, nanopore is a promising technology to improve diagnostics of imprinting disorders. METHODS: Currently, no tools to analyze DNA methylation patterns at known clinically relevant imprinted regions are available. Here we present NanoImprint, which generates an easily interpretable report, based on long-read nanopore sequencing, to use for identifying clinical relevant abnormalities in methylation levels at 14 imprinted regions and diagnosis of common imprinting disorders. RESULTS AND CONCLUSION: NanoImprint outputs a summarizing table and visualization plots displays methylation frequency (%) and chromosomal positions for all regions, with phased data color-coded for the two alleles. We demonstrate the utility of NanoImprint using three imprinting disorder samples from patients with Beckwith-Wiedemann syndrome (BWS), Angelman syndrome (AS) and Prader-Willi syndrome (PWS). NanoImprint script is available from https://github.com/carolinehey/NanoImprint.

Harnessing exosomes as cancer biomarkers in clinical oncology.

Exosomes are extracellular vesicles well known for facilitating cell-to-cell communication by distributing essential macromolecules like proteins, DNA, mRNA, lipids, and miRNA. These vesicles are abundant in fluids distributed throughout the body, including urine, blood, saliva, and even bile. They are important diagnostic tools for breast, lung, gastrointestinal cancers, etc. However, their application as cancer biomarkers has not yet been implemented in most parts of the world. In this review, we discuss how OMICs profiling of exosomes can be practiced by substituting traditional imaging or biopsy methods for cancer detection. Previous methods like extensive imaging and biopsy used for screening were expensive, mostly invasive, and could not easily provide early detection for various types of cancer. Exosomal biomarkers can be utilized for routine screening by simply collecting body fluids from the individual. We anticipate that the use of exosomes will be brought to light by the success of clinical trials investigating their potential to enhance cancer detection and treatment in the upcoming years.

Expanding the Role of Chiral Drugs and Chiral Nanomaterials as a Potential Therapeutic Tool.

Chirality, the property of molecules having mirror-image forms, plays a crucial role in pharmaceutical and biomedical research. This review highlights its growing importance, emphasizing how chiral drugs and nanomaterials impact drug effectiveness, safety, and diagnostics. Chiral molecules serve as precise diagnostic tools, aiding in accurate disease detection through unique biomolecule interactions. The article extensively covers chiral drug applications in treating cardiovascular diseases, CNS disorders, local anesthesia, anti-inflammatories, antimicrobials, and anticancer drugs. Additionally, it explores the emerging field of chiral nanomaterials, highlighting their suitability for biomedical applications in diagnostics and therapeutics, enhancing medical treatments.

Delirium diagnostic tools in the postoperative setting: A scoping review protocol.

BACKGROUND: Delirium is an acute and fluctuating disturbance in attention, awareness, and cognition, commonly observed in hospital settings, particularly among older adults, critically ill and surgical patients. Delirium poses significant challenges in patient care, leading to increased morbidity, mortality, prolonged hospital stays, and functional decline. AIM: The aim of this review is to map existing evidence on delirium diagnostic tools suitable for use in patients treated surgically due to hip fracture, to inform clinical practice and enhance patient care protocols in the postoperative setting. METHOD: We will conduct a scoping review on delirium diagnostic tools used for adult patients in the postoperative setting according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Eligibility criteria encompass all languages, publications dates, and study designs, with exception of case-reports. We will systematically search multiple databases and include unpublished trials, ensuring a comprehensive review based on a predefined protocol. RESULTS: Results will be presented descriptively, with supplementary tables and graphs. Studies will be grouped by design, surgical specialties, and diagnostic tools to identify potential variations. CONCLUSION: This scoping review will provide an overview of existing delirium diagnostic tools used in the postoperative setting and highlight knowledge-gaps to support future research. Due to the large number of patients affected by postoperative delirium, evidence mapping is much needed to facilitate evidence-based practice.

Artificial Intelligence-Based Tool for Tumor Detection and Quantitative Tissue Analysis in Colorectal Specimens.

Digital pathology adoption allows for applying computational algorithms to routine pathology tasks. Our study aimed to develop a clinical-grade artificial intelligence (AI) tool for precise multiclass tissue segmentation in colorectal specimens (resections and biopsies) and clinically validate the tool for tumor detection in biopsy specimens. The training data set included 241 precisely manually annotated whole-slide images (WSIs) from multiple institutions. The algorithm was trained for semantic segmentation of 11 tissue classes with an additional module for biopsy WSI classification. Six case cohorts from 5 pathology departments (4 countries) were used for formal and clinical validation, digitized by 4 different scanning systems. The developed algorithm showed high precision of segmentation of different tissue classes in colorectal specimens with composite multiclass Dice score of up to 0.895 and pixel-wise tumor detection specificity and sensitivity of up to 0.958 and 0.987, respectively. In the clinical validation study on multiple external cohorts, the AI tool reached sensitivity of 1.0 and specificity of up to 0.969 for tumor detection in biopsy WSI. The AI tool analyzes most biopsy cases in less than 1 minute, allowing effective integration into clinical routine. We developed and extensively validated a highly accurate, clinical-grade tool for assistive diagnostic processing of colorectal specimens. This tool allows for quantitative deciphering of colorectal cancer tissue for development of prognostic and predictive biomarkers and personalization of oncologic care. This study is a foundation for a SemiCOL computational challenge. We open-source multiple manually annotated and weakly labeled test data sets, representing a significant contribution to the colorectal cancer computational pathology field.

Pathologist Computer-Aided Diagnostic Scoring of Tumor Cell Fraction: A Swiss National Study.

Tumor cell fraction (TCF) estimation is a common clinical task with well-established large interobserver variability. It thus provides an ideal test bed to evaluate potential impacts of employing a tumor cell fraction computer-aided diagnostic (TCFCAD) tool to support pathologists' evaluation. During a National Slide Seminar event, pathologists (n = 69) were asked to visually estimate TCF in 10 regions of interest (ROIs) from hematoxylin and eosin colorectal cancer images intentionally curated for diverse tissue compositions, cellularity, and stain intensities. Next, they re-evaluated the same ROIs while being provided a TCFCAD-created overlay highlighting predicted tumor vs nontumor cells, together with the corresponding TCF percentage. Participants also reported confidence levels in their assessments using a 5-tier scale, indicating no confidence to high confidence, respectively. The TCF ground truth (GT) was defined by manual cell-counting by experts. When assisted, interobserver variability significantly decreased, showing estimates converging to the GT. This improvement remained even when TCFCAD predictions deviated slightly from the GT. The standard deviation (SD) of the estimated TCF to the GT across ROIs was 9.9% vs 5.8% with TCFCAD (P < .0001). The intraclass correlation coefficient increased from 0.8 to 0.93 (95% CI, 0.65-0.93 vs 0.86-0.98), and pathologists stated feeling more confident when aided (3.67 ± 0.81 vs 4.17 ± 0.82 with the computer-aided diagnostic [CAD] tool). TCFCAD estimation support demonstrated improved scoring accuracy, interpathologist agreement, and scoring confidence. Interestingly, pathologists also expressed more willingness to use such a CAD tool at the end of the survey, highlighting the importance of training/education to increase adoption of CAD systems.

Sarcopenia and myosteatosis diagnostic tool for gastrointestinal cancer: creatinine to cystatin C ratio as evaluation marker.

OBJECTIVE: This study aimed to develop a simplified diagnostic tool for assessing sarcopenia and myosteatosis in gastrointestinal cancer patients, focusing on the creatinine to cystatin C ratio (CCR) as an evaluation marker. METHODS: 955 patients were split into training (n = 671) and validation (n = 284) cohorts. Using logistic regression, risk factors for sarcopenia and myosteatosis were identified. The predictive capacity of the developed model was examined. The association between CCR and muscle imaging parameters, along with its impact on clinical outcomes, was analyzed. RESULTS: No significant differences were observed in baseline traits between cohorts. CCR emerged as a significant risk factor for both sarcopenia and myosteatosis. Nomograms for diagnosing these conditions demonstrated strong predictive ability, with AUC values indicating high accuracy (sarcopenia AUC: 0.865-0.872; myosteatosis AUC: 0.848-0.849). The clinical utility of the nomograms was confirmed through decision curve analysis. CCR showed significant association with muscle imaging parameters and was a reliable indicator for assessing the risk of sarcopenia, myosteatosis, and cachexia. Moreover, CCR was able to differentiate between patient survival and disease progression rates. CONCLUSION: A diagnostic tool for sarcopenia and myosteatosis in gastrointestinal cancer patients was developed, with CCR being a pivotal biomarker for disease diagnosis and prognosis prediction.

The role of online symptom questionnaires to support the diagnosis of cow's milk allergy in children for healthcare professionals - A Delphi consensus study.

BACKGROUND: Cow's milk allergy (CMA) is one of the most common food allergies world-wide. The emergence of online CMA symptom questionnaires, aimed at parents and/or healthcare professionals (HCP), may raise awareness about the possible diagnosis of CMA, but also increases the risk for overdiagnosis leading to unnecessary dietary restriction impacting on growth and nutrition. This publication sets out to establish the availability of these CMA symptom questionnaires and critically assesses the development and validity. METHODS: Thirteen HCP working in the field of CMA, from different countries, were recruited to participate. A combination of a Pubmed and CINAHL literature and online review using the Google search engine in English language was used. Symptoms in the questionnaires were assessed, using the European Academy for Allergy and Clinical Immunology guidelines for food allergy. Following the assessment of both the questionnaires and literature, the authors followed the modified Delphi approach to generate consensus statements. RESULTS: Six hundred and fifty-one publications were identified, of which 29 were suitable for inclusion, with 26 being associated with the Cow's Milk-Related Symptoms Score. The online search yielded 10 available questionnaires: 7/10 were sponsored by formula milk companies and 7/10 were aimed at parents and three at HCP. Following the assessment of data, 19 statements were generated in two rounds of anonymous voting reaching 100% agreement. CONCLUSIONS: Online CMA questionnaires, available to parents and HCP's, are varied in symptoms, and most were not validated. The overarching consensus generated from authors is that these questionnaires should not be used without the involvement of HCP.

Characterization of unipolar electrogram morphology: a novel tool for quantifying conduction inhomogeneity.

AIMS: Areas of conduction inhomogeneity (CI) during sinus rhythm may facilitate the initiation and perpetuation of atrial fibrillation (AF). Currently, no tool is available to quantify the severity of CI. Our aim is to develop and validate a novel tool using unipolar electrograms (EGMs) only to quantify the severity of CI in the atria. METHODS AND RESULTS: Epicardial mapping of the right atrium (RA) and left atrium, including Bachmann's bundle, was performed in 235 patients undergoing coronary artery bypass grafting surgery. Conduction inhomogeneity was defined as the amount of conduction block. Electrograms were classified as single, short, long double (LDP), and fractionated potentials (FPs), and the fractionation duration of non-single potentials was measured. The proportion of low-voltage areas (LVAs, <1 mV) was calculated. Increased CI was associated with decreased potential voltages and increased LVAs, LDPs, and FPs. The Electrical Fingerprint Score consisting of RA EGM features, including LVAs and LDPs, was most accurate in predicting CI severity. The RA Electrical Fingerprint Score demonstrated the highest correlation with the amount of CI in both atria (r = 0.70, P < 0.001). CONCLUSION: The Electrical Fingerprint Score is a novel tool to quantify the severity of CI using only unipolar EGM characteristics recorded. This tool can be used to stage the degree of conduction abnormalities without constructing spatial activation patterns, potentially enabling early identification of patients at high risk of post-operative AF or selection of the appropriate ablation approach in addition to pulmonary vein isolation at the electrophysiology laboratory.

RNA analysis of tape strips to rule out melanoma in lesions clinically assessed as cutaneous malignant melanoma: A diagnostic study.

BACKGROUND: Distinguishing cutaneous malignant melanoma (CMM) from nevi can be clinically challenging. Suspicious lesions are therefore excised, resulting in many benign lesions being removed surgically to find 1 CMM. It has been proposed to use tape strip derived ribonucleic acid (RNA) to distinguish CMM from nevi. OBJECTIVE: To develop this technique further and validate if RNA profiles can rule out CMM in clinically suspicious lesions with 100% sensitivity. METHODS: Before surgical excision, 200 lesions clinically assessed as CMM were tape stripped. Expression levels of 11 genes on the tapes were investigated by RNA measurement and used in a rule-out test. RESULTS: Histopathology showed that 73 CMMs and 127 non-CMMs were included. Our test correctly identified all CMMs (100% sensitivity) based on the expression levels of 2 oncogenes, PRAME and KIT, relative to a housekeeping gene. Patient age and sample storage time were also significant. Simultaneously, our test correctly excluded CMM in 32% of non-CMM lesions (32% specificity). LIMITATIONS: Our sample contained a very high proportion of CMMs, perhaps due to inclusion during COVID-19 shutdown. Validation in a separate trial must be performed. CONCLUSION: Our results demonstrate that the technique can reduce removal of benign lesions by one-third without overlooking any CMMs.

A combined encoder-transformer-decoder network for volumetric segmentation of adrenal tumors.

BACKGROUND: The morphology of the adrenal tumor and the clinical statistics of the adrenal tumor area are two crucial diagnostic and differential diagnostic features, indicating precise tumor segmentation is essential. Therefore, we build a CT image segmentation method based on an encoder-decoder structure combined with a Transformer for volumetric segmentation of adrenal tumors. METHODS: This study included a total of 182 patients with adrenal metastases, and an adrenal tumor volumetric segmentation method combining encoder-decoder structure and Transformer was constructed. The Dice Score coefficient (DSC), Hausdorff distance, Intersection over union (IOU), Average surface distance (ASD) and Mean average error (MAE) were calculated to evaluate the performance of the segmentation method. RESULTS: Analyses were made among our proposed method and other CNN-based and transformer-based methods. The results showed excellent segmentation performance, with a mean DSC of 0.858, a mean Hausdorff distance of 10.996, a mean IOU of 0.814, a mean MAE of 0.0005, and a mean ASD of 0.509. The boxplot of all test samples' segmentation performance implies that the proposed method has the lowest skewness and the highest average prediction performance. CONCLUSIONS: Our proposed method can directly generate 3D lesion maps and showed excellent segmentation performance. The comparison of segmentation metrics and visualization results showed that our proposed method performed very well in the segmentation.

Sharing Data With Shared Benefits: Artificial Intelligence Perspective.

Artificial intelligence (AI) and data sharing go hand in hand. In order to develop powerful AI models for medical and health applications, data need to be collected and brought together over multiple centers. However, due to various reasons, including data privacy, not all data can be made publicly available or shared with other parties. Federated and swarm learning can help in these scenarios. However, in the private sector, such as between companies, the incentive is limited, as the resulting AI models would be available for all partners irrespective of their individual contribution, including the amount of data provided by each party. Here, we explore a potential solution to this challenge as a viewpoint, aiming to establish a fairer approach that encourages companies to engage in collaborative data analysis and AI modeling. Within the proposed approach, each individual participant could gain a model commensurate with their respective data contribution, ultimately leading to better diagnostic tools for all participants in a fair manner.

The scope of using pragmatic language tests for early detection of dementia: A systematic review of investigations using figurative language.

INTRODUCTION: Dementia cases are expected to rise to 81.1 million in 2040. Efforts are underway to develop diagnostic methods to facilitate early detection of the disease. Herein we review research findings focusing on pragmatic dysfunction in patients with dementia and evaluate the usefulness of assessing dementia and its progress with a battery of tests assessing figurative language skills. METHODS: A total of 74,778 article titles were identified from EMBASE, PubMed, and Google Scholar databases. After systematic screening, 51 journal articles were selected for the final review. RESULT: The review suggests that impaired figurative language might be a marker for early cognitive decline. Different forms of figurative language may be impaired at different stages of the disease and in different types of dementia involving different neuropathologies. CONCLUSION: The use of pragmatic tests in combination with the existing diagnostic protocols might increase the probability of early diagnosis. HIGHLIGHTS Pragmatic impairment could be a marker of early cognitive impairment. Figurative language-an important pragmatic aspect-is disrupted in mild cognitive impairment (MCI) and early Alzheimer's disease (AD). Figurative language impairment might precede literal language impairment. Pragmatic tests could be more sensitive than standard neuropsychological tests. Inclusion of pragmatic tests in diagnostic guidelines might bolster early detection.

Development, Validation, and Two-Year Application of Rapid and Simple LC-MS/MS-Based Method for the Determination of K2MK-7 in Blood Samples.

Biological properties of menaquinone-7, one of the vitamin K2 vitamers (K2MK-7), both those proven and those that remain to be investigated, arouse extensive interest that goes beyond the strictly scientific framework. The most important of them is the prevention of age-related diseases, considering that we live in the times identified as the era of aging societies and many people are exposed to the vitamin K2MK-7 deficiency. Therefore, an effective analytical protocol that can be adopted as a diagnostic and preventive analytics tool is needed. Herein, a simple sample preparation method followed by the liquid chromatography-tandem mass spectrometry-based method (LC-MS/MS), was used for the selective and sensitive determination of K2MK-7 in serum samples. Under the optimized conditions, using 500 µL of serum and the same amount of n-hexane, the reproducibility and the accuracy were obtained in the ranges of 89-97% and 86-110%, respectively, and the limit of detection value was 0.01 ng/mL. This method was used for the routine analysis. Statistical interpretation of the data from 518 samples obtained during 2 years of practice allowed for obtaining information on the content and distribution of K2MK-7 in the Polish population, broken down by the sex and age groups.

Ponticulus Posticus: An Important Diagnostic Finding Often Missed in Lateral Cephalograms.

AIM: The purpose of the current study was to investigate the presence of the ponticulus posticus (PP) frequently encountered in lateral cephalograms. MATERIALS AND METHODS: About 500 patients of age 12-40 years were selected whose digital lateral cephalogram was recorded and traced to confirm the presence of the PP and categorize as: (A) Absent, as evidenced by lateral cephalograms. (B) Complete PP evidenced by the presence of circumferential bone bridge that connected the upper articular process to the atlas's posterior arch. (C) Partial PP: presented as a bone spike that protruded from the top articular process or the posterior arch of the atlas and extended above the vertebral artery sulcus. Symptoms of migraine, shoulder discomfort, orofacial pain, and headache were also evaluated on interaction with the patients. Using the Chi-square test, the relationship between the patient's gender and the presence of the PP was assessed. A p-value of 0.05 or less was regarded as statistically significant. RESULTS: About 10% of the patients reported with the presence of complete variant, 70% with partial variant and rest 20% of patients with neither a partial nor a complete form of PP. There was no statistically significant association between the PP and gender, as indicated by the Chi-square values (3.146; p = 0.526). CONCLUSION: On conclusion, according to the findings of the current study, patients with a complete form of PP experience more symptoms than those with a partial form of PP. In both groups, the PP frequency was higher in females. CLINICAL SIGNIFICANCE: In lateral cephalograms, the cervical spine region is typically ignored and given little weight. A common variation of atlas vertebrae is the PP, which is located in the posterior arch of the atlas. The PP exacerbates symptoms, such as migraine, tension headaches, shoulder pain, double vision, vertigo, stroke, and pain in the neck and orofacial region. Therefore, orthodontic specialists serve as initial diagnosticians and direct the patients to qualified physicians so that they can experience symptom relief.

Towards a Precise NMR Quantification of Acute Phase Inflammation Proteins from Human Serum.

Nuclear Magnetic Resonance (NMR) spectra of human serum and plasma show, besides metabolites and lipoproteins, two characteristic signals termed GlycA and B arising from the acetyl groups of glycoprotein glycans from acute phase proteins, which constitute good markers for inflammatory processes. Here, we report a comprehensive assignment of glycoprotein glycan NMR signals observed in human serum, showing that GlycA and GlycB signals originate from Neu5Ac and GlcNAc moieties from N-glycans, respectively. Diffusion-edited NMR experiments demonstrate that signal components can be associated with specific acute phase proteins. Conventionally determined concentrations of acute phase glycoproteins correlate well with distinct features in NMR spectra (R2 up to 0.9422, p-value <0.001), allowing the simultaneous quantification of several acute phase inflammation proteins. Overall, a proteo-metabolomics NMR signature of significant diagnostic potential is obtained within 10-20 min acquisition time. This is exemplified in serum samples from COVID-19 and cardiogenic shock patients showing significant changes in several acute phase proteins compared to healthy controls.

Diagnostic models for the detection of intrauterine growth restriction and placental insufficiency severity based on magnetic resonance imaging of the placenta.

Purpose: We aimed to provide diagnostic models based on different parameters of placental magnetic resonance imaging (MRI) to detect intrauterine growth restriction (IUGR), as well as the severity of placental insufficiency. Material and methods: We included 44 foetuses with appropriate weight for gestational age (AGA) and 46 foetuses with documented IUGR, defined as the estimated foetal weight (EFW) below the 10th centile. Using Doppler ultrasound, IUGR cases were divided into 2 groups: 1) IUGR with severity signs: EFW < 3rd centile, or cerebroplacental ratio < 5th centile, or abnormal umbilical/uterine artery pulsatility index; and 2) non-severe IUGR without any of this criterion. For all these participants, placental MRI was performed in the third gestational trimester, and its parameters were compared between AGA and IUGR, as well as between the severe and non-severe IUGR groups. Two diagnostic models consisting of significant predictors were developed, and their performance was investigated with accuracy metrics. Results: The severity signs were detected in 25 (54.3%) IUGR cases. The diagnostic model for the differentiation of IUGR from AGA revealed an acceptable performance (area under the curve [AUC] of 0.749) and consisted of 2 variables: 1) the largest size of infarct ≥ 25 mm (odds ratio [OR] = 5.01, p = 0.001), and 2) thickness : volume ratio ≥ 0.043 (OR = 3.76, p = 0.027); while, the logistic regression model for detection of the severity signs was even better, with AUC = 0.862, and comprised of 2 predictors: 1) placental infarct percent ≥ 10% (OR = 26.73, p = 0.004), and 2) placental globular shape (OR = 5.40, p = 0.034). Conclusions: Placental MRI parameters can differentiate IUGR from AGA, and more precisely, assess the severity of placental insufficiency in IUGR foetuses.

Detecting Coronary Artery Disease Using Exhaled Breath Analysis.

INTRODUCTION: Coronary artery disease (CAD) is the leading cause of morbidity and mortality worldwide, and there is an unmet need for a simple, inexpensive, noninvasive tool aimed at CAD detection. The aim of this pilot study was to evaluate the possible use of breath analysis in detecting the presence of CAD. MATERIALS AND METHODS: In a prospective study, breath from patients with no history of CAD who presented with acute chest pain to the emergency room was sampled using a designated portable electronic nose (eNose) system. First, breath samples from 60 patients were analyzed and categorized as obstructive, nonobstructive, and no-CAD according to the actual presence and extent of CAD as was demonstrated on cardiac imaging (either computerized tomography angiography or coronary angiography). Classification models were built according to the results, and their diagnostic performance was then examined in a blinded manner on a new set of 25 patients. The data were compared with the actual results of coronary arteries evaluation. Sensitivity, specificity, and accuracy were calculated for each model. RESULTS: Obstructive CAD was correctly distinguished from nonobstructive and no-CAD with 89% sensitivity, 31% specificity, 83% negative predictive value (NPV), 42% positive predictive value (PPV), and 52% accuracy. In another model, any extent of CAD was successfully distinguished from no-CAD with 69% sensitivity, 67% specificity, 54% NPV, 79% PPV, and 68% accuracy. CONCLUSION: This proof-of-concept study shows that breath analysis has the potential to be used as a novel rapid, noninvasive diagnostic tool to help identify presence of CAD in patients with acute chest pain.