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Deflectometric profilometers are used to precisely measure the form of beam shaping optics of synchrotrons and X-ray free-electron lasers. They often utilize autocollimators which measure slope by evaluating the displacement of a reticle image on a detector. Based on our privileged access to the raw image data of an autocollimator, novel strategies to reduce the systematic measurement errors by using a set of overlapping images of the reticle obtained at different positions on the detector are discussed. It is demonstrated that imaging properties such as, for example, geometrical distortions and vignetting, can be extracted from this redundant set of images without recourse to external calibration facilities. This approach is based on the fact that the properties of the reticle itself do not change - all changes in the reticle image are due to the imaging process. Firstly, by combining interpolation and correlation, it is possible to determine the shift of a reticle image relative to a reference image with minimal error propagation. Secondly, the intensity of the reticle image is analysed as a function of its position on the CCD and a vignetting correction is calculated. Thirdly, the size of the reticle image is analysed as a function of its position and an imaging distortion correction is derived. It is demonstrated that, for different measurement ranges and aperture diameters of the autocollimator, reductions in the systematic errors of up to a factor of four to five can be achieved without recourse to external measurements.

PurposeThis study aimed to develop novel non-contrast MR perfusion techniques for assessing micro-vascularity of the foot in human subjects.MethodsAll experiments were performed on a clinical 3 T scanner using arterial spin labeling (ASL). Seven healthy subjects (30-72 years old, 5 males and 2 females) were enrolled and bilateral feet were imaged with tag-on and tag-off alternating inversion recovery spin labeling for determining micro-vascularity. We compared an ASL technique with 1-tag against 4-tag pulses. For perfusion, we determined signal increase ratio (SIR) at varying inversion times (TI) from 0.5 to 2 s. SIR versus TI data were fit to determine perfusion metrics of peak height (PH), time to peak (TTP), full width at half maximum (FWHM), area under the curve (AUC), and apparent blood flow (aBF) in the distal foot and individual toes. Using analysis of variance (ANOVA), effects of tag pulse and region of interest (ROI) on the mean perfusion metrics were assessed. In addition, a 4-tag pulse perfusion experiment was performed on patients with peripheral artery disease (PAD) and Raynaud's disease.ResultsUsing our MR perfusion techniques, SIR versus TI data showed well-defined leading and trailing edges, with a peak near TI of 0.75-1.0 s and subsiding quickly to near zero by TI of 2 s, particularly when 4-tag pulses were used. When imaged with 4-tag pulse, we found significantly greater values in perfusion metrics, as compared to 1-tag pulse. The patients with PAD and Raynaud's disease showed a reduced or scattered perfusion curves compared to the healthy control.ConclusionMR perfusion imaging of the distal foot shows greater SIR and perfusion metrics with the 4-tag pulse compared to the 1-tag pulse technique. This will likely benefit those with low perfusion due to aging, PAD, diabetic foot, and other vascular diseases.

AbstractThe evidence underlying the use of advanced diagnostic imaging is based mainly on diagnostic accuracy studies and not on well-designed trials demonstrating improved patient outcomes. This has led to an expansion of low-value and potentially harmful patient care and raises ethical issues around the widespread implementation of tests with incompletely known benefits and harms. Randomized clinical trials are needed to support the safety and effectiveness of imaging tests and should be required for clearance of most new technologies. Large, diverse cohort studies are needed to quantify disease risk associated with many imaging findings, especially incidental findings, to enable evidence-based management. The responsibility to minimize the use of tests with unknown or low value requires engagement of clinicians, medical societies, and the public.

BackgroundHousehold contact investigations are effective for finding tuberculosis (TB) cases but are hindered by low referral uptake for clinic-based evaluation and testing. We assessed the acceptability and feasibility of in-home testing of household contacts (HHC) using the GeneXpert Edge platform.MethodsWe conducted a 2-arm, randomized study in Eastern Cape, South Africa. HHCs were verbally assessed using the World Health Organization-recommended 4-symptom screen. Households with ≥1 eligible symptomatic contact were randomized. Intervention households received in-home GeneXpert MTB/RIF molecular testing. GeneXpert-positive HHCs were referred for clinic-based treatment. Standard-of-care households were referred for clinic-based sputum collection and testing. We defined acceptability as agreeing to in-home testing and feasibility as generation of valid Xpert MTB/RIF results. The proportion and timeliness of test results received was compared between groups.ResultsEighty-four households were randomized (n = 42 per arm). Of 100 eligible HHCs identified, 98/100 (98%) provided consent. Of 51 HHCs allocated to the intervention arm, all accepted in-home testing; of those, 24/51 (47%) were sputum productive and 23/24 (96%) received their test results. Of 47 HCCs allocated to standard-of-care, 7 (15%) presented for clinic-based TB evaluation, 6/47 (13%) were tested, and 4/6 (67%) returned for their results. The median (interquartile range) number of days from screening to receiving test results was 0 (0) and 16.5 (11-15) in the intervention and standard-of-care arms, respectively.ConclusionsIn-home testing for TB was acceptable, feasible, and increased HHCs with a molecular test result. In-home testing mitigates a major limitation of household contact investigations (dependency on clinic-based referral), revealing new strategies for enhancing early case detection.

Tuberculous peritonitis (TB peritonitis) is one of the most challenging forms of extrapulmonary TB to diagnose. While tumor markers can be elevated in patients with TB peritonitis, FDG-PET/CT can aid in distinguishing TB peritonitis from malignancies, if an apron-like omentum pattern is seen. Laparoscopy is crucial for accurate and early diagnosis.

BACKGROUND: The elastic scattering spectroscopy (ESS) device (DermaSensor Inc., Miami, FL) is a noninvasive, painless, adjunctive tool for skin cancer detection. OBJECTIVES: To investigate the performance of the ESS device in the detection of melanoma. METHODS: A prospective, investigator-blinded, multicenter study was conducted at 8 United States (US) and 2 Australian sites. All eligible skin lesions were clinically concerning for melanoma, examined with the ESS device, subsequently biopsied according to dermatologists standard of care, and evaluated with histopathology. A total of 311 participants with 440 lesions were enrolled, including 44 melanomas (63.6% in situ and 36.4% invasive) and 44 severely dysplastic nevi. RESULTS: The observed sensitivity of the ESS device for melanoma detection was 95.5% (95% CI, 84.5% to 98.8%, 42 of 44 melanomas), and the observed specificity was 32.5% (95% CI, 27.2% to 38.3%). The positive and negative predictive values were 16.0% and 98.1%, respectively. LIMITATIONS: The device was tested in a high-risk population with lesions selected for biopsy based on clinical and dermoscopic assessments of board-certified dermatologists. Most enrolled lesions were pigmented. CONCLUSION: The ESS devices high sensitivity and NPV for the detection of melanoma suggest the device may be a useful adjunctive, point-of-care tool for melanoma detection.

BackgroundSputum-based testing is a barrier to increasing access to molecular diagnostics for tuberculosis (TB). Many people with TB are unable to produce sputum, and sputum processing increases assay complexity and cost. Tongue swabs are emerging as an alternative to sputum, but performance limits are uncertain.MethodsFrom June 2022 to July 2023, we enrolled 397 consecutive adults with cough >2 weeks at 2 health centers in Kampala, Uganda. We collected demographic and clinical information, sputum for TB testing (Xpert MTB/RIF Ultra and 2 liquid cultures), and tongue swabs for same-day quantitative polymerase chain reaction (qPCR) testing. We evaluated tongue swab qPCR diagnostic accuracy versus sputum TB test results, quantified TB targets per swab, assessed the impact of serial swabbing, and compared 2 swab types (Copan FLOQSWAB and Steripack spun polyester).ResultsAmong 397 participants, 43.1% were female, median age was 33 years, 23.5% were diagnosed with human immunodeficiency virus, and 32.0% had confirmed TB. Sputum Xpert Ultra and tongue swab qPCR results were concordant for 98.2% (95% confidence interval [CI]: 96.2-99.1) of participants. Tongue swab qPCR sensitivity was 92.6% (95% CI: 86.5 to 96.0) and specificity was 99.1% (95% CI: 96.9 to 99.8) versus microbiological reference standard. A single tongue swab recovered a 7-log range of TB copies, with a decreasing recovery trend among 4 serial swabs. Swab types performed equivalently.ConclusionsTongue swabs are a promising alternative to sputum for molecular diagnosis of TB, with sensitivity approaching sputum-based molecular tests. Our results provide valuable insights for developing successful tongue swab-based TB diagnostics.

Chronic conditions associated with aging have proven difficult to prevent or treat. Senescence is a cell fate defined by loss of proliferative capacity and the development of a pro-inflammatory senescence-associated secretory phenotype comprised of cytokines/chemokines, proteases, and other factors that promotes age-related diseases. Specifically, an increase in senescent peripheral blood mononuclear cells (PBMCs), including T cells, is associated with conditions like frailty, rheumatoid arthritis, and bone loss. However, it is unknown if the percentage of senescent PBMCs associated with age-associated orthopedic decline could be used for potential diagnostic or prognostic use in orthopedics. Here, we report senescent cell detection using the fluorescent compound C12FDG to quantify PBMCs senescence across a large cohort of healthy and osteoarthritic patients. There is an increase in the percent of circulating C12FDG+ PBMCs that is commensurate with increases in age and senescence-related serum biomarkers. Interestingly, C12FDG+ PBMCs and T cells also were found to be elevated in patients with mild to moderate osteoarthritis, a progressive joint disease that is strongly associated with inflammation. The percent of C12FDG+ PBMCs and age-related serum biomarkers were decreased in a small subgroup of study participants taking the senolytic drug fisetin. These results demonstrate quantifiable measurements in a large group of participants that could create a composite score of healthy aging sensitive enough to detect changes following senolytic therapy and may predict age-related orthopedic decline. Detection of peripheral senescence in PBMCs and subsets using C12FDG may be clinically useful for quantifying cellular senescence and determining how and if it plays a pathological role in osteoarthritic progression.

IntroductionLewy body disease (LBD) is a common primary or co-pathology in neurodegenerative syndromes. An alpha-synuclein seed amplification assay (αSyn-SAA) is clinically available, but clinical performance, especially lower sensitivity in amygdala-predominant cases, is not well understood.MethodsAntemortem CSF from neuropathology-confirmed LBD cases was tested with αSyn-SAA (N = 56). Diagnostic performance and clinicopathological correlations were examined.ResultsSimilar to prior reports, sensitivity was 100% for diffuse and transitional LBD (9/9), and overall specificity was 96.3% (26/27). Sensitivity was lower in amygdala-predominant (6/14, 42.8%) and brainstem-predominant LBD (1/6, 16.7%), but early spread outside these regions (without meeting criteria for higher stage) was more common in αSyn-SAA-positive cases (6/7, 85.7%) than negative (2/13, 15.4%).DiscussionIn this behavioral neurology cohort, αSyn-SAA had excellent diagnostic performance for cortical LBD. In amygdala- and brainstem-predominant cases, sensitivity was lower, but positivity was associated with anatomical spread, suggesting αSyn-SAA detects early LBD progression in these cohorts.HighlightsA cerebrospinal fluid alpha-synuclein assay detects cortical LBD with high sensitivity/specificity. Positivity in prodromal stages of LBD was associated with early cortical spread. The assay provides precision diagnosis of LBD that could support clinical trials. The assay can also identify LBD co-pathology, which may impact treatment responses.

Six decades after its conception, proton computed tomography (pCT) and proton radiography have yet to be used in medical clinics. However, good progress has been made on relevant detector technologies in the past two decades, and a few prototype pCT systems now exist that approach the performance needed for a clinical device.The tracking and energy-measurement technologies in common use are described, as are the few pCT scanners that are in routine operation at this time.Most of these devices still look like detector R\&D efforts as opposed to medical devices, are difficult to use, are at least factor of five slower than desired for clinical use, and are too small to image many parts of the human body.Recommendations are made for what to consider when engineering a pre-clinical pCT scanner that is designed to meet clinical needs in terms of performance, cost, and ease of use.

Therapeutic antibodies for reducing Aβ plaque load in Alzheimer’s disease (AD) is currently making rapid progress. The diagnostic imaging of Aβ plaque load in AD has been underway and is now used in clinical studies. Here, we report our preliminary findings on imaging a therapeutic antibody, Lecanemab, in a postmortem AD brain anterior cingulate. [125I]5-iodo-3-pyridinecarboxamido-Lecanemab ([125I]IPC-Lecanemab) was prepared by coupling N-succinimidyl-5-([125I]iodo)-3-pyridinecarboxylate with Lecanemab in modest yields. The distinct binding of [125I]IPC-Lecanemab to Aβ-rich regions in postmortem human AD brains was higher in grey matter (GM) containing Aβ plaques compared to white matter (WM) (GM/WM was 1.6). Anti-Aβ immunostaining was correlated with [125I]IPC-Lecanemab regional binding in the postmortem AD human brains. [125I]IPC-Lecanemab binding was consistent with the binding of Aβ small molecules, [18F]flotaza and [125I]IBETA, in the same subjects. [18F]Flotaza and [125I]IBETA, however, exhibited significantly higher GM/WM ratios (>20) compared to [125I]IPC-Lecanemab. Our results suggest that radiolabeled [125I]IPC-Lecanemab retains the ability to bind to Aβ in human AD and may therefore be useful as a PET imaging radiotracer when labeled as [124I]IPC-Lecanemab. The ability to directly visualize in vivo a promising therapeutic antibody for AD may be useful in treatment planning and dosing and could be complimentary to small-molecule diagnostic imaging to assess outcomes of therapeutic interventions.

There is an important need for methods to process myocardial perfusion imaging (MPI) single-photon emission computed tomography (SPECT) images acquired at lower-radiation dose and/or acquisition time such that the processed images improve observer performance on the clinical task of detecting perfusion defects compared to low-dose images. To address this need, we build upon concepts from model-observer theory and our understanding of the human visual system to propose a detection task-specific deep-learning-based approach for denoising MPI SPECT images (DEMIST). The approach, while performing denoising, is designed to preserve features that influence observer performance on detection tasks. We objectively evaluated DEMIST on the task of detecting perfusion defects using a retrospective study with anonymized clinical data in patients who underwent MPI studies across two scanners (N = 338). The evaluation was performed at low-dose levels of 6.25%, 12.5%, and 25% and using an anthropomorphic channelized Hotelling observer. Performance was quantified using area under the receiver operating characteristics curve (AUC). Images denoised with DEMIST yielded significantly higher AUC compared to corresponding low-dose images and images denoised with a commonly used task-agnostic deep learning-based denoising method. Similar results were observed with stratified analysis based on patient sex and defect type. Additionally, DEMIST improved visual fidelity of the low-dose images as quantified using root mean squared error and structural similarity index metric. A mathematical analysis revealed that DEMIST preserved features that assist in detection tasks while improving the noise properties, resulting in improved observer performance. The results provide strong evidence for further clinical evaluation of DEMIST to denoise low-count images in MPI SPECT.

Alzheimer's disease (AD) is a neurodegenerative disease that commonly causes dementia. Identifying biomarkers for the early detection of AD is an emerging need, as brain dysfunction begins two decades before the onset of clinical symptoms. To this end, we reanalyzed untargeted metabolomic mass spectrometry data from 905 patients enrolled in the AD Neuroimaging Initiative (ADNI) cohort using MS-DIAL, with 1,304,633 spectra of 39,108 unique biomolecules. Metabolic profiles of 93 hydrophilic metabolites were determined. Additionally, we integrated targeted lipidomic data (4873 samples from 1524 patients) to explore candidate biomarkers for predicting progressive mild cognitive impairment (pMCI) in patients diagnosed with AD within two years using the baseline metabolome. Patients with lower ergothioneine levels had a 12% higher rate of AD progression with the significance of P = 0.012 (Wald test). Furthermore, an increase in ganglioside (GM3) and decrease in plasmalogen lipids, many of which are associated with apolipoprotein E polymorphism, were confirmed in AD patients, and the higher levels of lysophosphatidylcholine (18:1) and GM3 d18:1/20:0 showed 19% and 17% higher rates of AD progression, respectively (Wald test: P = 3.9 × 10-8 and 4.3 × 10-7). Palmitoleamide, oleamide, diacylglycerols, and ether lipids were also identified as significantly altered metabolites at baseline in patients with pMCI. The integrated analysis of metabolites and genomics data showed that combining information on metabolites and genotypes enhances the predictive performance of AD progression, suggesting that metabolomics is essential to complement genomic data. In conclusion, the reanalysis of multiomics data provides new insights to detect early development of AD pathology and to partially understand metabolic changes in age-related onset of AD.

With the emergence of Alzheimer's disease (AD) disease-modifying therapies, identifying patients who could benefit from these treatments becomes critical. In this study, we evaluated whether a precise blood test could perform as well as established cerebrospinal fluid (CSF) tests in detecting amyloid-β (Aβ) plaques and tau tangles. Plasma %p-tau217 (ratio of phosporylated-tau217 to non-phosphorylated tau) was analyzed by mass spectrometry in the Swedish BioFINDER-2 cohort (n = 1,422) and the US Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) cohort (n = 337). Matched CSF samples were analyzed with clinically used and FDA-approved automated immunoassays for Aβ42/40 and p-tau181/Aβ42. The primary and secondary outcomes were detection of brain Aβ or tau pathology, respectively, using positron emission tomography (PET) imaging as the reference standard. Main analyses were focused on individuals with cognitive impairment (mild cognitive impairment and mild dementia), which is the target population for available disease-modifying treatments. Plasma %p-tau217 was clinically equivalent to FDA-approved CSF tests in classifying Aβ PET status, with an area under the curve (AUC) for both between 0.95 and 0.97. Plasma %p-tau217 was generally superior to CSF tests in classification of tau-PET with AUCs of 0.95-0.98. In cognitively impaired subcohorts (BioFINDER-2: n = 720; Knight ADRC: n = 50), plasma %p-tau217 had an accuracy, a positive predictive value and a negative predictive value of 89-90% for Aβ PET and 87-88% for tau PET status, which was clinically equivalent to CSF tests, further improving to 95% using a two-cutoffs approach. Blood plasma %p-tau217 demonstrated performance that was clinically equivalent or superior to clinically used FDA-approved CSF tests in the detection of AD pathology. Use of high-performance blood tests in clinical practice can improve access to accurate AD diagnosis and AD-specific treatments.

Hyperpolarization techniques significantly enhance the sensitivity of magnetic resonance (MR) and thus present fascinating new directions for research and applications with in vivo MR imaging and spectroscopy (MRI/S). Hyperpolarized 13C MRI/S, in particular, enables real-time non-invasive assessment of metabolic processes and holds great promise for a diverse range of clinical applications spanning fields like oncology, neurology, and cardiology, with a potential for improving early diagnosis of disease, patient stratification, and therapy response assessment. Despite its potential, technical challenges remain for achieving clinical translation. This paper provides an overview of the discussions that took place at the international workshop "New Horizons in Hyperpolarized 13C MRI," in March 2023 at the Bavarian Academy of Sciences and Humanities, Munich, Germany. The workshop covered new developments, as well as future directions, in topics including polarization techniques (particularly focusing on parahydrogen-based methods), novel probes, considerations related to data acquisition and analysis, and emerging clinical applications in oncology and other fields.

Chronic myeloid leukemia (CML) is initiated and maintained by BCR::ABL which is clinically targeted using tyrosine kinase inhibitors (TKIs). TKIs can induce long-term remission but are also not curative. Thus, CML is an ideal system to test our hypothesis that transcriptome-based state-transition models accurately predict cancer evolution and treatment response. We collected time-sequential blood samples from tetracycline-off (Tet-Off) BCR::ABL-inducible transgenic mice and wild-type controls. From the transcriptome, we constructed a CML state-space and a three-well leukemogenic potential landscape. The potential's stable critical points defined observable disease states. Early states were characterized by anti-CML genes opposing leukemia; late states were characterized by pro-CML genes. Genes with expression patterns shaped similarly to the potential landscape were identified as drivers of disease transition. Re-introduction of tetracycline to silence the BCR::ABL gene returned diseased mice transcriptomes to a near healthy state, without reaching it, suggesting parts of the transition are irreversible. TKI only reverted the transcriptome to an intermediate disease state, without approaching a state of health; disease relapse occurred soon after treatment. Using only the earliest time-point as initial conditions, our state-transition models accurately predicted both disease progression and treatment response, supporting this as a potentially valuable approach to time clinical intervention, before phenotypic changes become detectable.

In pancreatic ductal adenocarcinoma (PDAC), no recurrent metastasis-specific mutation has been found, suggesting that epigenetic mechanisms, such as DNA methylation, are the major contributors of late-stage disease progression. Here, we performed the first whole-genome bisulfite sequencing (WGBS) on mouse and human PDAC organoid models to identify stage-specific and molecular subtype-specific DNA methylation signatures. With this approach, we identified thousands of differentially methylated regions (DMRs) that can distinguish between the stages and molecular subtypes of PDAC. Stage-specific DMRs are associated with genes related to nervous system development and cell-cell adhesions, and are enriched in promoters and bivalent enhancers. Subtype-specific DMRs showed hypermethylation of GATA6 foregut endoderm transcriptional networks in the squamous subtype and hypermethylation of EMT transcriptional networks in the progenitor subtype. These results indicate that aberrant DNA methylation contributes to both PDAC progression and subtype differentiation, resulting in significant and reoccurring DNA methylation patterns with diagnostic and prognostic potential.

Proton resonance frequency shift (PRFS) MR thermometry is the most common method used in clinical thermal treatments because of its fast acquisition and high sensitivity to temperature. However, motion is the biggest obstacle in PRFS MR thermometry for monitoring thermal treatment in moving organs. This challenge arises because of the introduction of phase errors into the PRFS calculation through multiple methods, such as image misregistration, susceptibility changes in the magnetic field, and intraframe motion during MRI acquisition. Various approaches for motion correction have been developed for real-time, motion-robust, and volumetric MR thermometry. However, current technologies have inherent trade-offs among volume coverage, processing time, and temperature accuracy. These tradeoffs should be considered and chosen according to the thermal treatment application. In hyperthermia treatment, precise temperature measurements are of increased importance rather than the requirement for exceedingly high temporal resolution. In contrast, ablation procedures require robust temporal resolution to accurately capture a rapid temperature rise. This paper presents a comprehensive review of current cutting-edge MRI techniques for motion-robust MR thermometry, and recommends which techniques are better suited for each thermal treatment. We expect that this study will help discern the selection of motion-robust MR thermometry strategies and inspire the development of motion-robust volumetric MR thermometry for practical use in clinics.

PurposeTroponin T levels are routinely checked in trauma patients after experiencing a ground-level fall to identify potential cardiac causes of syncope. An elevated initial troponin prompts serial testing until the level peaks. However, the high sensitivity of the test may lead to repeat testing that is of little clinical value. Here, we examine the role of serial troponins in predicting the need for further cardiac workup in trauma patients after sustaining a fall.MethodsRetrospective review of all adult trauma activations for ground-level fall from January 1, 2021 to December 31, 2021 in patients who were hemodynamically and neurologically normal at presentation. Outcomes evaluated included need for cardiology consult, admission to cardiology service, outpatient cardiology follow-up, cardiology intervention and in-hospital mortality.ResultsThere were 1555 trauma activations for ground-level fall in the study period. The cohort included 560 patients evaluated for a possible syncopal fall, hemodynamically stable, Glasgow Coma Scale score of 15, and with a troponin drawn at presentation. The initial median troponin was 20 ng/L (13-37). Second troponin values were drawn on 58% (median 33 ng/L (22-52)), with 42% of patients having an increase from first to second test. 29% of patients had a third troponin drawn (median 42 ng/L (26-67)). The initial troponin value was significantly associated with undergoing a subsequent echo (p=0.01), cardiology consult (p50 ng/L as a threshold for further clinical evaluation would improve the utility of the test and likely reduce unnecessary hospital stays and costs for otherwise healthy patients.Level of evidenceLevel III.

Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.72 (7 years prior) to 0.81 (1 day prior). We further harnessed matched cohort models to identify conditions with predictive power before AD onset. Knowledge networks highlight shared genes between multiple top predictors and AD (for example, APOE, ACTB, IL6 and INS). Genetic colocalization analysis supports AD association with hyperlipidemia at the APOE locus, as well as a stronger female AD association with osteoporosis at a locus near MS4A6A. We therefore show how clinical data can be utilized for early AD prediction and identification of personalized biological hypotheses.

IntroductionWith emergence of disease-modifying therapies, efficient diagnostic pathways are critically needed to identify treatment candidates, evaluate disease severity, and support prognosis. A combination of plasma biomarkers and brief digital cognitive assessments could provide a scalable alternative to current diagnostic work-up.MethodsWe examined the accuracy of plasma biomarkers and a 10-minute supervised tablet-based cognitive assessment (Tablet-based Cognitive Assessment Tool Brain Health Assessment [TabCAT-BHA]) in predicting amyloid β positive (Aβ+) status on positron emission tomography (PET), concurrent disease severity, and functional decline in 309 older adults with subjective cognitive impairment (n = 49), mild cognitive impairment (n = 159), and dementia (n = 101).ResultsCombination of plasma pTau181, Aβ42/40, neurofilament light (NfL), and TabCAT-BHA was optimal for predicting Aβ-PET positivity (AUC = 0.962). Whereas NfL and TabCAT-BHA optimally predicted concurrent disease severity, combining these with pTau181 and glial fibrillary acidic protein was most accurate in predicting functional decline.DiscussionCombinations of plasma and digital cognitive markers show promise for scalable diagnosis and prognosis of ADRD.HighlightsThe need for cost-efficient diagnostic and prognostic markers of AD is urgent. Plasma and digital cognitive markers provide complementary diagnostic contributions. Combination of these markers holds promise for scalable diagnosis and prognosis. Future validation in community cohorts is needed to inform clinical implementation.

IntroductionEarly risk stratification for clinical dementia could lead to preventive therapies. We identified and validated a magnetic resonance imaging (MRI) signature for Alzheimer's disease (AD) and related dementias (ARDR).MethodsAn MRI ADRD signature was derived from cortical thickness maps in Framingham Heart Study (FHS) participants with AD dementia and matched controls. The signature was related to the risk of ADRD and cognitive function in FHS. Results were replicated in the University of California Davis Alzheimer's Disease Research Center (UCD-ADRC) cohort.ResultsParticipants in the bottom quartile of the signature had more than three times increased risk for ADRD compared to those in the upper three quartiles (P

Feline chronic gingivostomatitis (FCGS) is a debilitating inflammatory oral mucosal disease with a multifactorial etiology. The clinical diagnosis of FCGS is made based on inspection of severe inflammatory lesions and histological confirmation rather than a molecular diagnostic outcome. This gap limits the ability to provide an early diagnosis. In this report, we seek to provide additional diagnostic tools using genomics to aid in providing clinically relevant information. The use of in-depth diagnostic tools, like transcriptomics of diseased tissues, to diagnose FCGS and stratify patients into predictive treatment response groups would dramatically improve both clinical decisions and patient outcomes. In this study, we addressed the gap in diagnostic options using transcriptomic analysis of caudal oral mucosal swab specimens coupled to detailed medical record linkage of FCGS-affected cats undergoing tooth extractions and in some cases administration of mesenchymal stromal cells (MSCs). To better identify markers of disease and potential response to treatment, the transcriptomes of FCGS-afflicted cats were compared to those of healthy cats and those with chronic periodontitis to clearly establish diagnostic biomarker signal transduction connections. Phosphatidylinositol 3-kinase/Ak strain transforming (PI3K/AKT) and stress-activated protein kinases/Jun N-terminal kinase (SAP/JNK) signaling pathways were significantly differentially regulated in FCGS-afflicted cats. Activation of these pathways also differed in the treatment response groups. In conjunction, the enzymes Caspase 4 (CASP4), matrix metalloproteinase-8 (MMP8), and prostaglandin-endoperoxide synthase 2 (PTGS2) were identified as potential biomarkers for the prediction of treatment response outcomes. The observations in the case study support the use of transcriptomics of FCGS patients to contribute to improved molecular diagnostics for the diagnosis and treatment of FCGS.

Opinion statementPSMA-PET has been a practice-changing imaging biomarker for the management of men with PCa. Research suggests improved accuracy over conventional imaging and other PET radiotracers in many contexts. With multiple approved PSMA-targeting radiotracers, PSMA PET will become even more available in clinical practice. Its increased use requires an understanding of the prospective data available and caution when extrapolating from prior trial data that utilized other imaging modalities. Future trials leveraging PSMA PET for treatment optimization and management decision-making will ultimately drive its clinical utility.

BackgroundNon-sputum-based triage tests for tuberculosis are a priority for ending tuberculosis. We aimed to evaluate the diagnostic accuracy of the late-prototype Xpert MTB Host Response (Xpert HR) blood-based assay.MethodsWe conducted a prospective diagnostic accuracy study among outpatients with presumed tuberculosis in outpatient clinics in Viet Nam, India, the Philippines, Uganda, and South Africa. Eligible participants were aged 18 years or older and reported cough lasting at least 2 weeks. We excluded those receiving tuberculosis treatment in the preceding 12 months and those who were unwilling to consent. Xpert HR was performed on capillary or venous blood. Reference standard testing included sputum Xpert MTB/RIF Ultra and mycobacterial culture. We performed receiver operating characteristic (ROC) analysis to identify the optimal cutoff value for the Xpert HR to achieve the target sensitivity of 90% or more while maximising specificity, then calculated diagnostic accuracy using this cutoff value. This study was prospectively registered with ClinicalTrials.gov, NCT04923958.FindingsBetween July 13, 2021, and Aug 15, 2022, 2046 adults with at least 2 weeks of cough were identified, of whom 1499 adults (686 [45·8%] females and 813 [54·2%] males) had valid Xpert HR and reference standard results. 329 (21·9%) had microbiologically confirmed tuberculosis. Xpert HR had an area under the ROC curve of 0·89 (95% CI 0·86-0·91). The optimal cutoff value was less than or equal to -1·25, giving a sensitivity of 90·3% (95% CI 86·5-93·3; 297 of 329) and a specificity of 62·6% (95% CI 59·7-65·3; 732 of 1170). Sensitivity was similar across countries, by sex, and by subgroups, although specificity was lower in people living with HIV (45·1%, 95% CI 37·8-52·6) than in those not living with HIV (65·9%, 62·8-68·8; difference of 20·8%, 95% CI 13·0-28·6; p

284 Background: Multiparametric MRI (mpMRI) and PSMA-PET are complementary imaging modalities used in the pre-surgical evaluation of patients with prostate cancer (PCa). The aim of this study was to evaluate the imaging and pathology parameters associated with PSMA-PET and mpMRI disagreement with each other and with gold standard histopathology. Methods: Patients undergoing radical prostatectomy (RP) with pre-surgical PSMA-PET and mpMRI were screened for inclusion in this retrospective analysis. Patients had the imaging scans done 3, n=153). mpMRI and PSMA PET identified 138 and 170 lesions, respectively. Sensitivity for ISUP>3 lesions was 79% and 87% for mpMRI and PSMA-PET, respectively. 115/153 (76%) ISUP> 3 lesions were correctly identified, and 14/153 (9%) were missed by both imaging modalities, respectively. 5/153 (3%) were correctly identified by mpMRI and missed by PSMA-PET, 17/153 (11%) were correctly identified by PSMA-PET and missed by mpMRI. Lesion’s ISUP grade group and size on pathology were significantly lower in mpMRI- compared to mpMRI+ and in PET- compared to PET+ lesions. SUVmax and SUVmean were significantly higher in PET+/MRI+ than PET+/MRI- lesions. Lesion’s ISUP grade group and size were significantly correlated to PSMA-PET and mpMRI agreement, whereas PSMA-PET metrics were not. Logistic regression model showed that lesions with lower ISUP, smaller size, and lack of aggressive prostate cancer features on pathology (cribriform pattern and intraductal carcinoma) have higher likelihood of being missed by PET and mpMRI and of PET/MRI disagreement. Conclusions: Higher SUVmax, SUVmean, and tumor volume on PSMA-PET were associated with a TP finding on PSMA-PET, higher ISUP grade group and size on pathology were associated with a TP finding on both PSMA-PET and mpMRI, and with agreement between PSMA-PET and mpMRI.

Deviations from normal blood pressure (BP) during general anesthesia have been clearly linked to several adverse outcomes. Measuring BP accurately is therefore critically important for producing excellent outcomes in health care. Normal BP does not necessarily guarantee adequate organ perfusion however and adverse events have occurred even when BP seemed adequate. Invasive blood pressure monitoring has recently evolved beyond merely measuring BP. Arterial line-derived pulse contour analysis is used now to assess both cardiac output and stroke volume variation as indices of adequate intravascular volume. Confirmation of acceptable cardiac output with data derived from invasive intra-arterial catheters has become very important when managing high-risk patients. Newer devices that measure BP continuously and non-invasively in the digital arteries via a finger cuff have also become available. Many clinicians contemplate now if these new devices are ready to replace invasive monitoring with an arterial catheter. Unlike non-invasive devices, intra-arterial catheters allow frequent blood sampling. This makes it possible to assess vital parameters like pH, hemoglobin concentration, ionized calcium, potassium, glucose, and arterial partial pressure of oxygen and carbon dioxide frequently. Non-invasive continuous BP measurement has been found to be unreliable in critically ill patients, the elderly, and patients with calcified arteries. Pulse contour-derived estimates of cardiac output and stroke volume variation have been validated better with data derived from arterial lines than that from the newer finger cuff monitors. Significant advances have been recently made with non-invasive continuous BP monitors. Invasive monitoring with an arterial line however remains the gold standard for measuring BP and assessing pulse contour analysis-derived hemodynamic variables in critically ill patients. In the future, non-invasive continuous BP monitors will likely replace intermittent oscillometers in the operating room and the postoperative period. They will however not eliminate the need for arterial catheterization in critically ill patients.

ObjectiveTo investigate whether functional upper eyelid malposition is associated with unrecognized deficits in automated perimetry among glaucoma patients by examining patients undergoing eyelid surgery who had not been identified as requiring eyelid taping during glaucoma field testing.MethodsIn this retrospective pre-post study, an automated database search followed by manual chart review was used to identify eligible patients from January 2012 to March 2020. Included patients had reliable visual field testing within two years before and after functional upper blepharoplasty or ptosis repair and no comorbid ocular diagnoses. As part of routine practice, glaucoma visual field technicians taped patients with pupil-obstructing eyelid malposition; taped examinations were excluded from analysis. Clinical and demographic characteristics, mean deviation, and pattern standard deviation were evaluated within a two year period before and after eyelid surgery.ResultsThe final analysis included 60 eyes of 38 patients. Change in visual field parameters after eyelid surgery did not reach statistical significance in crude or adjusted analyses. Among patients with ptosis, the margin reflex distance-1 was not associated with change in mean deviation after surgery (Pearson R2 ​= ​0.0061; P ​= ​0.700). Five of 17 eyes excluded from analysis due to unreliable pre-operative visual fields demonstrated substantial improvement after surgery.ConclusionsFunctional upper eyelid malposition does not appear to cause spurious visual field abnormalities among glaucoma patients with reliable visual fields who were determined not to require eyelid taping at the time of their visual fields. Unreliable visual fields could be a sign of eyelid interference in this population.

PurposeTimely diagnosis of diabetic retinopathy is important in preventing vision loss. This study aims to determine if remote retinal imaging enables earlier eye care access among newly-diagnosed diabetic patients.DesignRetrospective cohort study.MethodsUsing the OptumLabs® Data Warehouse - a longitudinal, real-world dataset containing deidentified administrative claims and electronic health record (EHR) data, we included 968 846 adults with newly diagnosed type 2 diabetes and at least 1 year of continuous enrollment. We compared time from initial diabetes diagnosis to first eye exam by remote screening or in-person eye exam.ResultsWe found that at year 1 after diagnosis, 5459 (0.56%) patients underwent remote imaging and 208 023 (21.5%) underwent in-person exam. The mean (95% CI) time to eye exam was 3.48 (3.38-3.58) months for remote imaging and 4.22 (4.20-4.23) months for in-person visits (p

BackgroundSeizure detection is challenging outside the clinical environment due to the lack of comfortable, reliable, and practical long-term neurophysiological monitoring devices. We developed a novel, discreet, unobstructive in-ear sensing system that enables long-term electroencephalography (EEG) recording. This is the first study we are aware of that systematically compares the seizure detection utility of in-ear EEG with that of simultaneously recorded intracranial EEG. In addition, we present a similar comparison between simultaneously recorded in-ear EEG and scalp EEG.MethodsIn this foundational research, we conducted a clinical feasibility study and validated the ability of the ear-EEG system to capture focal-onset seizures against 1255 hrs of simultaneous ear-EEG data along with scalp or intracranial EEG in 20 patients with refractory focal epilepsy (11 with scalp EEG, 8 with intracranial EEG, and 1 with both).ResultsIn a blinded, independent review of the ear-EEG signals, two epileptologists were able to detect 86.4% of the seizures that were subsequently identified using the clinical gold standard EEG modalities, with a false detection rate of 0.1 per day, well below what has been reported for ambulatory monitoring. The few seizures not detected on the ear-EEG signals emanated from deep within the mesial temporal lobe or extra-temporally and remained very focal, without significant propagation. Following multiple sessions of recording for a median continuous wear time of 13 hrs, patients reported a high degree of tolerance for the device, with only minor adverse events reported by the scalp EEG cohort.ConclusionsThese preliminary results demonstrate the potential of using ear-EEG to enable routine collection of complementary, prolonged, and remote neurophysiological evidence, which may permit real-time detection of paroxysmal events such as seizures and epileptiform discharges. This study suggests that the ear-EEG device may assist clinicians in making an epilepsy diagnosis, assessing treatment efficacy, and optimizing medication titration.

BackgroundBone biomarkers are strongly prognostic for overall survival (OS) in men with castration-resistant prostate cancer but not fully established for hormone-sensitive prostate cancer (HSPC).ObjectiveBone biomarkers in HSPC were prospectively evaluated as part of a phase 3 study of androgen deprivation therapy ± the CYP17 inhibitor orteronel.Design, setting, and participantsPatients were randomly divided into training (n = 316) and validation (n = 633) sets. Recursive partitioning and Cox proportional hazard models were employed.Outcome measurements and statistical analysisBone resorption (C-telopeptide and pyridinoline) and bone formation markers (C-terminal collagen propeptide and bone alkaline phosphatase) were assessed from patient sera.Results and limitationsOf 1279 men, 949 had evaluable baseline bone biomarkers. Optimal cutoffs were identified to define elevated levels of each of the four biomarkers (all p

The breasts undergo marked physiologic changes during lactation that can make conventional imaging evaluation with mammography and US challenging. MRI can be a valuable diagnostic aid to differentiate physiologic and benign processes from malignancy in patients who are lactating. In addition, MRI may allow more accurate delineation of disease involvement than does conventional imaging and assists in locoregional staging, screening of the contralateral breast, assessment of response to neoadjuvant chemotherapy, and surgical planning. Although the American College of Radiology recommends against patients undergoing contrast-enhanced MRI during pregnancy because of fetal safety concerns, contrast-enhanced MRI is safe during lactation. As more women delay childbearing, the incidence of pregnancy-associated breast cancer (PABC) and breast cancer in lactating women beyond the 1st year after pregnancy is increasing. Thus, MRI is increasingly being performed in lactating women for diagnostic evaluation and screening of patients at high risk. PABC is associated with a worse prognosis than that of non-PABCs, with delays in diagnosis contributing to an increased likelihood of advanced-stage disease at diagnosis. Familiarity with the MRI features of the lactating breast and the appearance of various pathologic conditions is essential to avoid diagnostic pitfalls and prevent delays in cancer diagnosis and treatment. The authors review clinical indications for breast MRI during lactation, describe characteristic features of the lactating breast at MRI, and compare MRI features of a spectrum of benign and malignant breast abnormalities. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Chikarmane in this issue.

Various plasma biomarkers for amyloid-β (Aβ) have shown high predictability of amyloid PET positivity. However, the characteristics of discordance between amyloid PET and plasma Aβ42/40 positivity are poorly understood. Thorough interpretation of discordant cases is vital as Aβ plasma biomarker is imminent to integrate into clinical guidelines. We aimed to determine the characteristics of discordant groups between amyloid PET and plasma Aβ42/40 positivity, and inter-assays variability depending on plasma assays. We compared tau burden measured by PET, brain volume assessed by MRI, cross-sectional cognitive function, longitudinal cognitive decline and polygenic risk score (PRS) between PET/plasma groups (PET-/plasma-, PET-/plasma+, PET+/plasma-, PET+/plasma+) using Alzheimer's Disease Neuroimaging Initiative database. Additionally, we investigated inter-assays variability between immunoprecipitation followed by mass spectrometry method developed at Washington University (IP-MS-WashU) and Elecsys immunoassay from Roche (IA-Elc). PET+/plasma+ was significantly associated with higher tau burden assessed by PET in entorhinal, Braak III/IV, and Braak V/VI regions, and with decreased volume of hippocampal and precuneus regions compared to PET-/plasma-. PET+/plasma+ showed poor performances in global cognition, memory, executive and daily-life function, and rapid cognitive decline. PET+/plasma+ was related to high PRS. The PET-/plasma+ showed intermediate changes between PET-/plasma- and PET+/plasma+ in terms of tau burden, hippocampal and precuneus volume, cross-sectional and longitudinal cognition, and PRS. PET+/plasma- represented heterogeneous characteristics with most prominent variability depending on plasma assays. Moreover, IP-MS-WashU showed more linear association between amyloid PET standardized uptake value ratio and plasma Aβ42/40 than IA-Elc. IA-Elc showed more plasma Aβ42/40 positivity in the amyloid PET-negative stage than IP-MS-WashU. Characteristics of PET-/plasma+ support plasma biomarkers as early biomarker of amyloidopathy prior to amyloid PET. Various plasma biomarker assays might be applied distinctively to detect different target subjects or disease stages.

BackgroundPostoperative delirium is prevalent in older adults and has been shown to increase the risk of long-term cognitive decline. Plasma biomarkers to identify the risk for postoperative delirium and the risk of Alzheimer's disease and related dementias are needed.MethodsThis biomarker discovery case-control study aimed to identify plasma biomarkers associated with postoperative delirium. Patients aged ≥65 years undergoing major elective noncardiac surgery were recruited. The preoperative plasma proteome was interrogated with SOMAmer-based technology targeting 1433 biomarkers.ResultsIn 40 patients (20 with vs. 20 without postoperative delirium), a preoperative panel of 12 biomarkers discriminated patients with postoperative delirium with an accuracy of 97.5%. The final model of five biomarkers delivered a leave-one-out cross-validation accuracy of 80%. Represented biological pathways included lysosomal and immune response functions.ConclusionIn older patients who have undergone major surgery, plasma SOMAmer proteomics may provide a relatively non-invasive benchmark to identify biomarkers associated with postoperative delirium.

Distinguishing between alcohol-associated hepatitis (AH) and alcohol-associated cirrhosis (AC) remains a diagnostic challenge. In this study, we used machine learning with transcriptomics and proteomics data from liver tissue and peripheral mononuclear blood cells (PBMCs) to classify patients with alcohol-associated liver disease. The conditions in the study were AH, AC, and healthy controls. We processed 98 PBMC RNAseq samples, 55 PBMC proteomic samples, 48 liver RNAseq samples, and 53 liver proteomic samples. First, we built separate classification and feature selection pipelines for transcriptomics and proteomics data. The liver tissue models were validated in independent liver tissue datasets. Next, we built integrated gene and protein expression models that allowed us to identify combined gene-protein biomarker panels. For liver tissue, we attained 90% nested-cross validation accuracy in our dataset and 82% accuracy in the independent validation dataset using transcriptomic data. We attained 100% nested-cross validation accuracy in our dataset and 61% accuracy in the independent validation dataset using proteomic data. For PBMCs, we attained 83% and 89% accuracy with transcriptomic and proteomic data, respectively. The integration of the two data types resulted in improved classification accuracy for PBMCs, but not liver tissue. We also identified the following gene-protein matches within the gene-protein biomarker panels: CLEC4M-CLC4M, GSTA1-GSTA2 for liver tissue and SELENBP1-SBP1 for PBMCs. In this study, machine learning models had high classification accuracy for both transcriptomics and proteomics data, across liver tissue and PBMCs. The integration of transcriptomics and proteomics into a multi-omics model yielded improvement in classification accuracy for the PBMC data. The set of integrated gene-protein biomarkers for PBMCs show promise toward developing a liquid biopsy for alcohol-associated liver disease.

The diagnostic performance of the high-sensitivity troponin T (hs-cTnT) European Society of Cardiology (ESC) 0/1-h algorithm in sex and race subgroups of US Emergency Department (ED) patients is unclear. A pre-planned subgroup analysis of the STOP-CP cohort study was conducted. Participants with 0- and 1-h hs-cTnT measures from eight US EDs (1/2017 to 9/2018) were stratified into rule-out, observation, and rule-in zones using the hs-cTnT ESC 0/1 algorithm. The primary outcome was adjudicated 30-day cardiac death or MI. The proportion with the primary outcome in each zone was compared between subgroups with Fisher's exact tests. The negative predictive value (NPV) of the ESC 0/1 rule-out zone for 30-day CDMI was calculated and compared between subgroups using Fisher's exact tests. Of the 1422 patients enrolled, 54.2% (770/1422) were male and 58.1% (826/1422) white with a mean age of 57.6 ± 12.8 years. At 30 days, cardiac death or myocardial infarction (MI) occurred in 12.9% (183/1422) of participants. Among patients stratified to the rule-out zone, 30-day cardiac death or MI occurred in 1.1% (5/436) of women versus 2.1% (8/436) of men (p = .40) and 1.2% (4/331) of non-white patients versus 1.8% (9/490) of white patients (p = .58). The NPV for 30-day cardiac death or MI was similar among women versus men (98.9% [95% confidence interval, CI: 97.3-99.6] vs. 97.9% [95% CI: 95.9-99.1]; p = .40) and among white versus non-white patients (98.8% [95% CI: 96.9-99.7] vs. 98.2% [95% CI: 96.5-99.2]; p = .39). NPVs

PurposeTo develop and evaluate a deep learning (DL) model to assess fundus photograph quality, and quantitatively measure its impact on automated POAG detection in independent study populations.MethodsImage quality ground truth was determined by manual review of 2815 fundus photographs of healthy and POAG eyes from the Diagnostic Innovations in Glaucoma Study and African Descent and Glaucoma Evaluation Study (DIGS/ADAGES), as well as 11,350 from the Ocular Hypertension Treatment Study (OHTS). Human experts assessed a photograph as high quality if of sufficient quality to determine POAG status and poor quality if not. A DL quality model was trained on photographs from DIGS/ADAGES and tested on OHTS. The effect of DL quality assessment on DL POAG detection was measured using area under the receiver operating characteristic (AUROC).ResultsThe DL quality model yielded an AUROC of 0.97 for differentiating between high- and low-quality photographs; qualitative human review affirmed high model performance. Diagnostic accuracy of the DL POAG model was significantly greater (P < 0.001) in good (AUROC, 0.87; 95% CI, 0.80-0.92) compared with poor quality photographs (AUROC, 0.77; 95% CI, 0.67-0.88).ConclusionsThe DL quality model was able to accurately assess fundus photograph quality. Using automated quality assessment to filter out low-quality photographs increased the accuracy of a DL POAG detection model.Translational relevanceIncorporating DL quality assessment into automated review of fundus photographs can help to decrease the burden of manual review and improve accuracy for automated DL POAG detection.

IntroductionIn high-burden settings, low-complexity screening tests for tuberculosis (TB) could expand the reach of community-based case-finding efforts. The potential costs and cost-effectiveness of approaches incorporating these tests are poorly understood.MethodsWe developed a microsimulation model assessing 3 approaches to community-based case-finding in hypothetical populations (India-, South Africa-, The Philippines-, Uganda-, and Vietnam-like settings) with TB prevalence 4 times that of national estimates: (1) screening with a point-of-care C-reactive protein (CRP) test, (2) screening with a more sensitive "Hypothetical Screening test" (95% sensitive for Xpert Ultra-positive TB, 70% specificity; equipment/labor costs similar to Xpert Ultra, but using a $2 cartridge) followed by sputum Xpert Ultra if positive, or (3) testing all individuals with sputum Xpert Ultra. Costs are expressed in 2023 US dollars and include treatment costs.ResultsUniversal Xpert Ultra was estimated to cost a mean $4.0 million (95% uncertainty range: $3.5 to $4.6 million) and avert 3200 (2600 to 3900) TB-related disability-adjusted life years (DALYs) per 100 000 people screened ($670 [The Philippines] to $2000 [Vietnam] per DALY averted). CRP was projected to cost $550 (The Philippines) to $1500 (Vietnam) per DALY averted but with 44% fewer DALYs averted. The Hypothetical Screening test showed minimal benefit compared to universal Xpert Ultra, but if specificity were improved to 95% and per-test cost to $4.5 (all-inclusive), this strategy could cost $390 (The Philippines) to $940 (Vietnam) per DALY averted.ConclusionsScreening tests can meaningfully improve the cost-effectiveness of community-based case-finding for TB but only if they are sensitive, specific, and inexpensive.

Artificial intelligence (AI) applications in breast imaging span a wide range of tasks including decision support, risk assessment, patient management, quality assessment, treatment response assessment and image enhancement. However, their integration into the clinical workflow has been slow due to the lack of a consensus on data quality, benchmarked robust implementation, and consensus-based guidelines to ensure standardization and generalization. Contrast-enhanced mammography (CEM) has improved sensitivity and specificity compared to current standards of breast cancer diagnostic imaging i.e., mammography (MG) and/or conventional ultrasound (US), with comparable accuracy to MRI (current diagnostic imaging benchmark), but at a much lower cost and higher throughput. This makes CEM an excellent tool for widespread breast lesion characterization for all women, including underserved and minority women. Underlining the critical need for early detection and accurate diagnosis of breast cancer, this review examines the limitations of conventional approaches and reveals how AI can help overcome them. The Methodical approaches, such as image processing, feature extraction, quantitative analysis, lesion classification, lesion segmentation, integration with clinical data, early detection, and screening support have been carefully analysed in recent studies addressing breast cancer detection and diagnosis. Recent guidelines described by Checklist for Artificial Intelligence in Medical Imaging (CLAIM) to establish a robust framework for rigorous evaluation and surveying has inspired the current review criteria.

INTRODUCTION: The objective of this study was to investigate the diagnostic potential of bacterial biomarkers by comparing the performance of molecular detection assays with clinical assessments of dogs oral health performed by veterinarians. METHODS: Supragingival and subgingival plaque samples were collected from 127 client-owned dogs, pre-booked for procedures under general anesthesia, visiting veterinary practices in the United States. DNA was extracted and bacterial biomarkers quantified using quantitative polymerase chain reaction. Gingivitis and periodontitis were recorded by a trained clinician using the Weighted Gingivitis Periodontitis Score which involved assessing the buccal surfaces of 18 teeth while under general anesthesia. Intraoral dental radiographs of the left and right mandibular first molar teeth were also obtained. These data were then used to establish the diagnostic performance of the molecular assay to detect periodontitis. RESULTS: An initial conscious, visual oral examination performed by the veterinarian identified 67.7% of dogs as having periodontitis, but examination under general anesthesia indicated a higher proportion (86.6%). Analysis of supragingival plaque samples collected by veterinarians from conscious and unconscious dogs demonstrated the assay had an accuracy of 77.7 to 80.9%, a sensitivity of 77.6 to 81.0%, and a specificity of 80.0%. DISCUSSION: Use of this molecular screening tool in conscious dogs has the potential to improve early periodontal disease detection and support veterinary decision making, ultimately improving the oral health of dogs and consequently their quality of life.

PurposeWe evaluated the impact of partial volume correction (PVC) methods on the quantification of longitudinal [18F]GTP1 tau positron-emission tomography (PET) in Alzheimer's disease and the suitability of describing the tau pathology burden temporal trajectories using linear mixed-effects models (LMEM).MethodsWe applied van Cittert iterative deconvolution (VC), 2-compartment, and 3-compartment, and the geometric transfer matrix plus region-based voxelwise methods to data acquired in an Alzheimer's disease natural history study over 18 months at a single imaging site. We determined the optimal PVC method by comparing the standardized uptake value ratio change (%ΔSUVR) between diagnostic and tau burden-level groups and the longitudinal repeatability derived from the LMEM. The performance of LMEM analysis for calculating %ΔSUVR was evaluated in a natural history study and in a multisite clinical trial of semorinemab in prodromal to mild Alzheimer's disease by comparing results to traditional per-visit estimates.ResultsThe VC, 2-compartment, and 3-compartment PVC methods had similar performance, whereas region-based voxelwise overcorrected regions with a higher tau burden. The lowest within-subject variability and acceptable group separation scores were observed without PVC. The LMEM-derived %ΔSUVR values were similar to the per-visit estimates with lower variability.ConclusionThe results indicate that the tested PVC methods do not offer a clear advantage or improvement over non-PVC images for the quantification of longitudinal [18F]GTP1 PET data. LMEM offers a robust framework for the longitudinal tau PET quantification with low longitudinal test-retest variability.Clinical trial registrationNCT02640092 and NCT03289143.

BackgroundHypoxia is a detrimental factor in solid tumors, leading to aggressiveness and therapy resistance. OMX, a tunable oxygen carrier from the heme nitric oxide/oxygen-binding (H-NOX) protein family, has the potential to reduce tumor hypoxia. [18F]Fluoromisonidazole ([18F]FMISO) positron emission tomography (PET) is the most widely used and investigated method for non-invasive imaging of tumor hypoxia. In this study, we used [18F]FMISO PET/CT (computed tomography) to assess the effect of OMX on tumor hypoxia in spontaneous canine tumors.ResultsThirteen canine patients with various tumors (n = 14) were randomly divided into blocks of two, with the treatment groups alternating between receiving intratumoral (IT) OMX injection (OMX IT group) and intravenous (IV) OMX injection (OMX IV group). Tumors were regarded as hypoxic if maximum tumor-to-muscle ratio (TMRmax) was greater than 1.4. In addition, hypoxic volume (HV) was defined as the region with tumor-to-muscle ratio greater than 1.4 on [18F]FMISO PET images. Hypoxia was detected in 6/7 tumors in the OMX IT group and 5/7 tumors in the OMX IV injection group. Although there was no significant difference in baseline hypoxia between the OMX IT and IV groups, the two groups showed different responses to OMX. In the OMX IV group, hypoxic tumors (n = 5) exhibited significant reductions in tumor hypoxia, as indicated by decreased TMRmax and HV in [18F]FMISO PET imaging after treatment. In contrast, hypoxic tumors in the OMX IT group (n = 6) displayed a significant increase in [18F]FMISO uptake and variable changes in TMRmax and HV.Conclusions[18F]FMISO PET/CT imaging presents a promising non-invasive procedure for monitoring tumor hypoxia and assessing the efficacy of hypoxia-modulating therapies in canine patients. OMX has shown promising outcomes in reducing tumor hypoxia, especially when administered intravenously, as evident from reductions in both TMRmax and HV in [18F]FMISO PET imaging.

Machine learning-based anomaly detection (AD) methods are promising tools for extending the coverage of searches for physics beyond the Standard Model (BSM). One class of AD methods that has received significant attention is resonant anomaly detection, where the BSM physics is assumed to be localized in at least one known variable. While there have been many methods proposed to identify such a BSM signal that make use of simulated or detected data in different ways, there has not yet been a study of the methods' complementarity. To this end, we address two questions. First, in the absence of any signal, do different methods pick the same events as signal-like? If not, then we can significantly reduce the false-positive rate by comparing different methods on the same dataset. Second, if there is a signal, are different methods fully correlated? Even if their maximum performance is the same, since we do not know how much signal is present, it may be beneficial to combine approaches. Using the Large Hadron Collider (LHC) Olympics dataset, we provide quantitative answers to these questions. We find that there are significant gains possible by combining multiple methods, which will strengthen the search program at the LHC and beyond.

ImportanceEarly-onset colorectal cancer (EOCRC), defined as a diagnosis at younger than age 50 years, is increasing, and so-called red flag signs and symptoms among these individuals are often missed, leading to diagnostic delays. Improved recognition of presenting signs and symptoms associated with EOCRC could facilitate more timely diagnosis and impact clinical outcomes.ObjectiveTo report the frequency of presenting red flag signs and symptoms among individuals with EOCRC, to examine their association with EOCRC risk, and to measure variation in time to diagnosis from sign or symptom presentation.Data sourcesPubMed/MEDLINE, Embase, CINAHL, and Web of Science were searched from database inception through May 2023.Study selectionStudies that reported on sign and symptom presentation or time from sign and symptom presentation to diagnosis for patients younger than age 50 years diagnosed with nonhereditary CRC were included.Data extraction and synthesisData extraction and quality assessment were performed independently in duplicate for all included studies using Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guidelines. Joanna Briggs Institute Critical Appraisal tools were used to measure risk of bias. Data on frequency of signs and symptoms were pooled using a random-effects model.Main outcomes and measuresOutcomes of interest were pooled proportions of signs and symptoms in patients with EOCRC, estimates for association of signs and symptoms with EOCRC risk, and time from sign or symptom presentation to EOCRC diagnosis.ResultsOf the 12 859 unique articles initially retrieved, 81 studies with 24 908 126 patients younger than 50 years were included. The most common presenting signs and symptoms, reported by 78 included studies, were hematochezia (pooled prevalence, 45% [95% CI, 40%-50%]), abdominal pain (pooled prevalence, 40% [95% CI, 35%-45%]), and altered bowel habits (pooled prevalence, 27% [95% CI, 22%-33%]). Hematochezia (estimate range, 5.2-54.0), abdominal pain (estimate range, 1.3-6.0), and anemia (estimate range, 2.1-10.8) were associated with higher EOCRC likelihood. Time from signs and symptoms presentation to EOCRC diagnosis was a mean (range) of 6.4 (1.8-13.7) months (23 studies) and a median (range) of 4 (2.0-8.7) months (16 studies).Conclusions and relevanceIn this systematic review and meta-analysis of patients with EOCRC, nearly half of individuals presented with hematochezia and abdominal pain and one-quarter with altered bowel habits. Hematochezia was associated with at least 5-fold increased EOCRC risk. Delays in diagnosis of 4 to 6 months were common. These findings highlight the need to identify concerning EOCRC signs and symptoms and complete timely diagnostic workup, particularly for individuals without an alternative diagnosis or sign or symptom resolution.

Biomarkers for evaluating tumor response to therapy and estimating the risk of disease relapse represent tremendous areas of clinical need. To evaluate treatment efficacy, tumor response is routinely assessed using different imaging modalities like positron emission tomography/computed tomography or magnetic resonance imaging. More recently, the development of circulating tumor DNA detection assays has provided a minimally invasive approach to evaluate tumor response and prognosis through a blood test (liquid biopsy). Integrating imaging- and circulating tumor DNA-based biomarkers may lead to improvements in the prediction of patient outcomes. For this mini-review, we searched the scientific literature to find original articles that combined quantitative imaging and circulating tumor DNA biomarkers to build prediction models. Seven studies reported building prognostic models to predict distant recurrence-free, progression-free, or overall survival. Three discussed building models to predict treatment response using tumor volume, pathologic complete response, or objective response as endpoints. The limited number of articles and the modest cohort sizes reported in these studies attest to the infancy of this field of study. Nonetheless, these studies demonstrate the feasibility of developing multivariable response-predictive and prognostic models using regression and machine learning approaches. Larger studies are warranted to facilitate the building of highly accurate response-predictive and prognostic models that are generalizable to other datasets and clinical settings.

MicroRNAs, short non-protein coding RNAs, are overexpressed in GCTs. Circulating levels of germ cell tumor (GCT)-associated miRNAs, such as miR-371a-3p, can be utilized as efficient and cost-effective alternatives in diagnosing and managing patients presenting with GCTs. This quality of miRNAs has demonstrated favorable performance characteristics as a reliable blood-based biomarker with high diagnostic accuracy compared to current serum tumor markers (STMs), including α-fetoprotein (AFP), beta human chorionic gonadotropin (β-hCG), and lactate dehydrogenase (LDH). The conventional STMs exhibit limited specificity and sensitivity. Potential clinical implications of miRNAs include impact on de-escalating or intensifying treatment, detecting recurrence at earlier stages, and lessening the necessity of cross-sectional imaging or invasive tissue biopsy for non-teratomatous GCTs. Here, we also highlight the outstanding issues that must be addressed prior to clinical implementation. Standards for measuring circulating miRNAs and determining ideal cutoff values are essential for integration into current clinical guidelines.

BackgroundKinetic modeling of 18F-florbetaben provides important quantification of brain amyloid deposition in research and clinical settings but its use is limited by the requirement of arterial blood data for quantitative PET. The total-body EXPLORER PET scanner supports the dynamic acquisition of a full human body simultaneously and permits noninvasive image-derived input functions (IDIFs) as an alternative to arterial blood sampling. This study quantified brain amyloid burden with kinetic modeling, leveraging dynamic 18F-florbetaben PET in aorta IDIFs and the brain in an elderly cohort.Methods18F-florbetaben dynamic PET imaging was performed on the EXPLORER system with tracer injection (300 MBq) in 3 individuals with Alzheimer's disease (AD), 3 with mild cognitive impairment, and 9 healthy controls. Image-derived input functions were extracted from the descending aorta with manual regions of interest based on the first 30 s after injection. Dynamic time-activity curves (TACs) for 110 min were fitted to the two-tissue compartment model (2TCM) using population-based metabolite corrected IDIFs to calculate total and specific distribution volumes (VT, Vs) in key brain regions with early amyloid accumulation. Non-displaceable binding potential ([Formula: see text] was also calculated from the multi-reference tissue model (MRTM).ResultsAmyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with [Formula: see text] analysis. [Formula: see text]and VT from kinetic models were correlated (r² = 0.46, P