Diagnostic Performance Measures Research Articles

Abstract TMP54: Development and testing of a fully automated tool for the detection, segmentation, and characterization of cervical carotid atherosclerotic disease

Background: Rapid, accurate diagnosis and characterization of carotid atherosclerosis can help prevent disabling strokes. Although carotid plaques can be identified on CT angiography (CTA), interpretation is challenging for frontline physicians. Quantification of plaque volume/composition requires much manual effort. We developed and tested a fully automated tool for segmenting carotid lumens and delineating atherosclerotic plaque, distinguishing between calcific and hypodense components. Methods: We used 528 consecutive cases with CTA head/neck from a population of 7,745 patients with ischemic stroke and transient ischemic attack in an entire province (Alberta) presenting from 1-April-2016 to 31-March-2017. Trained readers supervised by a radiologist manually segmented right and left carotid artery lumens from 3 vertebral bodies below the bulb to 3 above, and segmented regions of carotid atherosclerotic plaque, regardless of degree of stenosis, separately labelling calcific and hypodense components. Cases were split 80/20 between training and testing datasets. The fully automated pipeline included coarse-scale detection of regions of interest, a two-stream U-shaped network for detection and segmentation of lumens and plaques, and a geometry-based inference algorithm to distinguish left and right labels. We evaluated plaque detection using diagnostic performance measures and segmentation using the Dice coefficient. Results: 422 cases were used for training and 106 for testing. In testing data, the fully automated tool achieved excellent performance for bilateral segmentation of carotid lumens (Dice 0.91, 95%CI:0.90-0.92, e.g. Figure 1 ). For detection of calcific and hypodense plaque components, respectively, the model achieved sensitivity of 96.5% (95%CI:89.3-99.1%) and 97.3% (89.6-99.5%), specificity of 95.2% (74.1-99.8%) and 75.8% (57.4-88.3%), positive predictive value of 98.8% (92.6-99.9%) and 89.9% (80.5-95.2%), negative predictive value of 87.0% (65.3-96.6%) and 92.6% (74.2-98.7%), and accuracy of 96.2% (90.1-98.8%) and 90.6% (82.9-95.1%, e.g. Figure 2 ). Dice score was 0.73 (0.69-0.76) for calcific plaque and 0.53 (0.49-0.57) for hypodense plaque. Conclusions: Our fully automated tool achieved good performance for detection and segmentation of carotid plaques. Calcific and hypodense plaque volumes can be automatically generated from these labels. Efforts are underway to further optimize the specificity and segmentation performance for hypodense plaques.

Diagnostic accuracy of 4D-MRA for the detection and localization of spinal dural arteriovenous fistulas: A retrospective 10-year cohort study.

The goal of this study was to assess the diagnostic accuracy of spinal time-resolved contrast-enhanced MR angiography (4D-MRA) for the detection and localization of spinal dural arteriovenous fistulas (SDAVF) in our institution. Single center retrospective cohort study of patients with the clinical suspicion of a SDAVF. Patients were included who had undergone spinal 4D-MRA in the period January 2010-February 2021. A subgroup was identified, who had subsequent digital subtraction angiography (DSA), or clinical/radiological follow-up. Diagnostic performance measures of 4D-MRA were calculated (sensitivity, positive predictive value, specificity, and negative predictive value) with DSA serving as the reference standard. Overall, 120 patients with the clinical suspicion of having a SDAVF and who underwent spinal 4D-MRA were identified. A subgroup of 30 patients had both 4D-MRA and DSA, or follow-up. In this group, the sensitivity of 4D-MRA for the detection of a SDAVF was 100% and specificity was 91% (positive predictive value of 95% and a negative predictive value of 100%). Sidedness was correctly identified on 4D-MRA in 74% of the cases and the level of the SDAVF in 68%. The results indicate that 4D-MRA has a high sensitivity and specificity for the detection and localization of a SDAVF, which is in line with previous studies published in literature. Furthermore, 4D-MRA can serve to guide DSA and shorten the procedural time, which reduces the risk of angiography related complications, and decreases patient discomfort.

A prevalence-robust measure of diagnostic test performance

A prevalence-robust measure of diagnostic test performance

Harbingers of sepsis misdiagnosis among pediatric emergency department patients.

To identify clinical presentations that acted as harbingers for future sepsis hospitalizations in pediatric patients evaluated in the emergency department (ED) using the Symptom Disease Pair Analysis of Diagnostic Error (SPADE) methodology. We identified patients in the Pediatric Health Information Systems (PHIS) database admitted for sepsis between January 1, 2004 and December 31, 2023 and limitedthe study cohort to those patients who had an ED treat-and-release visit in the 30days prior to admission. Using thelook-back approach of the SPADE methodology, we identified the most common clinical presentations at theinitial ED visit and used an observed to expected (O:E)analysis to determine which presentations were overrepresented. We then employed a graphical, temporal analysis with a comparison group to identify which overrepresented presentations most likely represented harbingers for future sepsis hospitalization. We identified 184,157 inpatient admissions for sepsis, of which 15,331 hospitalizations (8.3 %) were preceded by a treat-and-release ED visit in the prior 30days. Based on the O:E and temporal analyses, the presentations of fever and dehydration were both overrepresented in the study cohort and temporally clustered close to sepsis hospitalization. ED treat-and-release visits for fever or dehydration preceded 1.2 % of all sepsis admissions. In pediatric patients presenting to the ED, fever and dehydration may represent harbingers for futuresepsis hospitalization. The SPADE methodology couldbe applied to the PHIS database to develop diagnostic performance measures across a wide range of pediatric hospitals.

The Diagnostic Value of Transthoracic Echocardiography for Pulmonary Hypertension: A Systematic Review and Meta-Analysis

Purpose Pulmonary hypertension (PH) is an important cause of morbidity and mortality. A commonly proposed non-invasive method in the diagnosis and assessment of PH is Transthoracic Echocardiography (TTE). In this systematic review and meta-analysis, our aim was to assess the accuracy of echocardiography in the diagnosis of PH. Methods The search was done up to the 31st of January 2023 using MEDLINE, Scopus, CENTRAL, and Web of Sciences databases. The studies were included if they were randomized controlled trials or observational in design and evaluated the diagnostic performance of TTE in diagnosing PH in comparison to right-sided heart catheterization as a reference method. The diagnostic performance measures included sensitivity, specificity, Diagnostic Odds Ratio (DOR), Positive Likelihood Ratio (PLR), and Negative Likelihood Ratio (NLR). Results The total number of the included patients was 4,523 from 38 articles. The overall sensitivity and specificity of echocardiography in diagnosing pulmonary hypertension were 54.8% (95%CI: 45.7%-63.6%) and 52.1% (95%CI: 39.0%-64.9%), respectively. Moreover, the pooled DOR was 1.321 (95%CI: 0.695-2.51). The pooled PLR and NLR were 1.145 (95%CI: 0.830-1.579) and 0.867 (95%CI: 0.628-1.197), respectively. The highest diagnostic performance of TTE was among group 1 and 3 PH patients. Conclusion Our analysis revealed that TTE had low diagnostic sensitivity, specificity, and accuracy. Due to the overall poor diagnostic performance of TTE, the diagnosis of PH and the assessment of response to therapies require right-sided heart catheterization. Future prospective studies to improve the diagnostic performance of TTE in the diagnosis of PH are needed.

Assessment of peroneal tendon lesions using 2-dimensional and 3-dimensional isotropic magnetic resonance imaging with surgical correlation.

Accurate diagnoses of peroneal pathologies remains a challenge due to limitations of conventional 2D (dimensional) imaging, which can impact long-term patient outcomes. This study evaluates MRI accuracy and inter-reader reliability of peroneal compartment pathology for 2D and 3D MRI. A consecutive series of patients who underwent peroneal compartment surgery with preoperative 1.5- or 3.0-Tesla ankle MRIs from 2009 to 2024 included 32 scans (22 with 2D, 10 with 2D+3D) from 31 patients (ages 17-74 years, all genders). Three musculoskeletal readers blinded to surgical findings independently analyzed MRI scans for common peroneal tenosynovitis, peroneus brevis and peroneus longus tenosynovitis, tendinopathy, and tears. Inter-reader reliability and diagnostic performance measures were calculated. Using majority vote, overall accuracy, sensitivity, and specificity for peroneal tendons using 2D MRI were 80%, 81%, and 79%, respectively. Using 3D MRI sequences, whether in isolation or combination with 2D MRI, accuracy, sensitivity, and specificity increased to 85%, 88%, and 83%, respectively. The inter-reader reliability for peroneus brevis lesions was 0.45-0.75 for 2D, 0.25-0.35 for 3D, and 0.31-0.54 for combined 2D+3D, while for peroneus longus lesions, it was 0.45-0.90 for 2D, 0.20-0.71 for 3D, and 0.64-0.81 for combined 2D+3D scans. The inter-reader reliability for tenosynovitis ranged from 0.62-0.64 for 2D, 0.25-0.37 for 3D, and 0.57-0.66 for combined 2D+3D scans. The addition of 3D MRI to 2D high-resolution ankle MRI protocol or 3D MRI alone increases accuracy of peroneal compartment lesion detection with minor decrease in inter-reader reliability for peroneal brevis tendon assessment. Larger studies may help validate our findings.

Evaluation of QuantiFERON-TB Gold for the Diagnosis of Mycobacterium tuberculosis Infection in HTLV-1-Infected Patients.

Human T-cell leukemia virus type 1 (HTLV-1) is associated with an increased risk of tuberculosis (TB). This study aimed to evaluate the performance of the QuantiFERON-TB Gold (QFT) test for the diagnosis of Mycobacterium tuberculosis (MTB) infection in HTLV-1-infected individuals. HTLV-1-infected participants were divided into four groups: HTLV-1-infected individuals with a history of tuberculosis (HTLV/TB), individuals with positive HTLV and tuberculin skin tests (HTLV/TST+) or negative TST (HTLV/TST-), and HTLV-1-negative individuals with positive TST results (HN/TST+). We compared the diagnostic performance of the QFT assay with that of the TST as a reference and evaluated test sensitivity, specificity, accuracy, likelihood ratio, and diagnostic odds ratio. The results showed a higher frequency of positive TST results and induration diameter ≥10 mm in HTLV-1-infected individuals than in the controls. The QFT test was more frequently positive in the HTLV/TB group than in the other groups, while a combined analysis of HTLV/TB and HTLV/TST+ indicated a QFT sensitivity of 57.5%. No significant differences were found in the other diagnostic performance measures, as QFT test results were in agreement with TST results, particularly in TST-negative individuals. Given the low sensitivity of QFT for LTBI in individuals infected with HTLV-1, the TST may be preferable in regions where both infections are endemic.

Efficient modelling of infectious diseases in wildlife: A case study of bovine tuberculosis in wild badgers.

Bovine tuberculosis (bTB) has significant socio-economic and welfare impacts on the cattle industry in parts of the world. In the United Kingdom and Ireland, disease control is complicated by the presence of infection in wildlife, principally the European badger. Control strategies tend to be applied to whole populations, but better identification of key sources of transmission, whether individuals or groups, could help inform more efficient approaches. Mechanistic transmission models can be used to better understand key epidemiological drivers of disease spread and identify high-risk individuals and groups if they can be adequately fitted to observed data. However, this is a significant challenge, especially within wildlife populations, because monitoring relies on imperfect diagnostic test information, and even under systematic surveillance efforts (such as capture-mark-recapture sampling) epidemiological events are only partially observed. To this end we develop a stochastic compartmental model of bTB transmission, and fit this to individual-level data from a unique > 40-year longitudinal study of 2,391 badgers using a recently developed individual forward filtering backward sampling algorithm. Modelling challenges are further compounded by spatio-temporal meta-population structures and age-dependent mortality. We develop a novel estimator for the individual effective reproduction number that provides quantitative evidence for the presence of superspreader badgers, despite the population-level effective reproduction number being less than one. We also infer measures of the hidden burden of infection in the host population through time; the relative likelihoods of competing routes of transmission; effective and realised infectious periods; and longitudinal measures of diagnostic test performance. This modelling framework provides an efficient and generalisable way to fit state-space models to individual-level data in wildlife populations, which allows identification of high-risk individuals and exploration of important epidemiological questions about bTB and other wildlife diseases.

Impact of discordance in cardiac troponin T versus I on the performance of triage pathways for myocardial infarction

Abstract Background Biological, analytical, and regulatory differences between high-sensitivity cardiac troponin T (hs-cTnT) and hs-cTnI could lead to an underestimation of the performance of a hs-cTnT-based triage-algorithm if evaluated against a hs-cTnI-based reference standard, and vice versa. Unfortunately, the impact of hs-cTnT/hs-cTnI-discordance on diagnostic performance measures is largely unknown. Methods We quantified the impact of hs-cTnT/hs-cTnI-discordance on the diagnostic performance of the three most widely used and guideline recommended hs-cTnT/I-based triage algorithms for patients presenting with symptoms suggestive of myocardial infarction (MI): the ESC 0/1h-algorithm, the ESC 0/2h-algorithm and the High-STEACS pathway. For the central adjudication of the final diagnosis (reference standard), two independent cardiologists had access to all available clinical information and applied the 4th universal definition of MI, one time with serial hs-cTnT-Elecsys measurements (gold standard T) and a second time with serial hs-cTnI-Architect measurements (gold standard I). The primary diagnostic endpoint for the rule-out of NSTEMI was sensitivity, while for rule-in of NSTEMI specificity. Results Among 7728 eligible patients, the final diagnosis was NSTEMI in 1463 patients (18.9%). Of these, NSTEMI was diagnosed with only one of the two adjudication methods (either gold standard T or I) in 167 (11.4%) patients. When the three hs-cTnT-based early-triage algorithms were evaluated using gold standard T and gold standard I, sensitivity was very high and comparable. In contrast, when the three hs-cTnI-based early-triage algorithms were evaluated using gold standard T and gold standard I, sensitivity was again very high, but consistently lower when using gold standard T as compared to gold standard I. The difference in sensitivity was 1.1% (95%CI, 0.6–1.7) for ESC hs-cTnI-0/1h (Table 1A), 1.0% (95% CI, 0.5—1.6) for ESC hs-cTnI-0/2h (Table 1B), and 2.6% (95%CI, 1.7—3.5) for High-STEACS (Table 2). The differences observed in specificity mirrored those for sensitivity, i.e. always lower specificity when using the other hs-cTnT/I-assay for adjudication. Conclusion The impact of hs-cTnT/hs-cTnI-discordance on the diagnostic performance of hs-cTnT/I-based triage algorithms is modest, but large enough to result in a fallacious underestimation of the rule-out safety when evaluating hs-cTnI-based strategies using a hs-cTnT-based reference standard.

Anthropometric equation has sufficient diagnostic capacity to identify sarcopenia in women with breast cancer

BackgroundSarcopenia is a common condition in women with breast cancer, however still presents limitations for an effective diagnosis. This study aimed to evaluate the agreement and diagnostic accuracy of an anthropometric equation in diagnosing sarcopenia in women with breast cancer based on different constructs.MethodsCross-sectional study carried out with women with breast cancer aged ≥ 20 years. Sarcopenia was identified according to the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) criteria. Muscle strength was obtained by the handgrip strength test (HGS) and muscle mass (MM) by dual-energy x-ray absorptiometry (DXA) and by the anthropometric predictive equation. For the diagnosis of sarcopenia, eight constructs were proposed based on the MM assessment method (equation or DXA) and different cutoff points. Agreement analyses using Cohen’s Kappa test and diagnostic performance measures were performed. The significance level for all tests was 5%.ResultsA total of 122 women, with a mean age of 55.3 ± 11.4 years, were evaluated. There was a predominance of brown participants (50.8%), insufficiently active (57.4%), with diagnosis time ≤ 3 months (54.1%), and with invasive breast carcinoma (69.7%). The prevalence of sarcopenia ranged from 3.3 to 8.2%, depending on the construct used. The constructs determined from the cutoff points < 16.0 kg/< 7.58 m² and < 23.0 kg/< 7.58 m² were the ones that showed the best ability to detect sarcopenia.ConclusionThe anthropometric equation showed sufficient diagnostic capacity to be used as an alternative in identifying sarcopenia in women with breast cancer.

Artificial intelligence in commercial fracture detection products: a systematic review and meta-analysis of diagnostic test accuracy

Conventional radiography (CR) is primarily utilized for fracture diagnosis. Artificial intelligence (AI) for CR is a rapidly growing field aimed at enhancing efficiency and increasing diagnostic accuracy. However, the diagnostic performance of commercially available AI fracture detection solutions (CAAI-FDS) for CR in various anatomical regions, their synergy with human assessment, as well as the influence of industry funding on reported accuracy are unknown. Peer-reviewed diagnostic test accuracy (DTA) studies were identified through a systematic review on Pubmed and Embase. Diagnostic performance measures were extracted especially for different subgroups such as product, type of rater (stand-alone AI, human unaided, human aided), funding, and anatomical region. Pooled measures were obtained with a bivariate random effects model. The impact of rater was evaluated with comparative meta-analysis. Seventeen DTA studies of seven CAAI-FDS analyzing 38,978 x-rays with 8,150 fractures were included. Stand-alone AI studies (n = 15) evaluated five CAAI-FDS; four with good sensitivities (> 90%) and moderate specificities (80–90%) and one with very poor sensitivity (< 60%) and excellent specificity (> 95%). Pooled sensitivities were good to excellent, and specificities were moderate to good in all anatomical regions (n = 7) apart from ribs (n = 4; poor sensitivity / moderate specificity) and spine (n = 4; excellent sensitivity / poor specificity). Funded studies (n = 4) had higher sensitivity (+ 5%) and lower specificity (-4%) than non-funded studies (n = 11). Sensitivity did not differ significantly between stand-alone AI and human AI aided ratings (p = 0.316) but specificity was significantly higher the latter group (p < 0.001). Sensitivity was significant lower in human unaided compared to human AI aided respectively stand-alone AI ratings (both p ≤ 0.001); specificity was higher in human unaided ratings compared to stand-alone AI (p < 0.001) and showed no significant differences AI aided ratings (p = 0.316). The study demonstrates good diagnostic accuracy across most CAAI-FDS and anatomical regions, with the highest performance achieved when used in conjunction with human assessment. Diagnostic accuracy appears lower for spine and rib fractures. The impact of industry funding on reported performance is small.

Comparative Analysis of Somatosensory-Evoked Potentials and Transcranial Doppler Ultrasound for Cerebral Ischemia Detection in Carotid Endarterectomy: Insights from Network Meta-Analysis and Clinical Data

OBJECTIVEThis study aims to compare the diagnostic efficacy of somatosensory-evoked potentials (SEP) and transcranial Doppler sonography (TCD) for monitoring cerebral tissue ischemia during carotid endarterectomy (CEA) using network meta-analysis and retrospective analysis of clinical data. METHODSFor the meta-analysis, we conducted a comprehensive search of four electronic databases (PubMed, EMBASE, Cochrane, and Web of Science) from inception to September 2023, resulting in the inclusion of 52 relevant articles. Additionally, a retrospective study was conducted at our hospital, involving patients who underwent CEA surgery from July 2019 to July 2021. RESULTSThe network meta-analysis incorporated 52 articles, with ranking results indicating that SEP demonstrated superior performance in specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy , with surface under the cumulative ranking curve (SUCRA) values of 99.9%, 93.8%, 96.6%, and 99.9%, respectively. Furthermore, TCD exhibited the highest sensitivity with a SUCRA value of 92.0%. A total of 190 patients meeting inclusion criteria were included in the retrospective study. The area under the curve (AUC) for SEP's receiver operating characteristic (ROC) curve was 0.787, compared to TCD's AUC of 0.606. SEP demonstrated a sensitivity of 66.67%, with a specificity of 90.76%, PPV of 19.05%, NPV of 98.82%, and accuracy of 90%. For TCD, the diagnostic performance measures included a sensitivity of 50.00%, specificity of 71.19%, PPV of 5.35%, NPV of 97.76%, and accuracy of 70.53%. The Fisher's exact test for sensitivity yielded a result of P=1.000. The χˆ2 test for specificity resulted in χˆ2=22.863, with P<0.001. Continuous correction χˆ2 tests for PPV and NPV showed χˆ2=2.005 (P=0.157) and χˆ2=0.069 (P=0.793), respectively. Additionally, the χˆ2 test for accuracy showed χˆ2=22.742, with P<0.001. CONCLUSIONSDuring CEA, SEP appears to provide a slightly more reliable indication of the ischemic condition in cerebral tissues compared to TCD.

Peripheral facial palsy in children: Serum Borrelia antibodies may reduce the need for lumbar puncture.

We aimed to investigate the causes of acute peripheral facial palsy (PFP) in Danish children and to explore whether neuroborreliosis-related PFP could be diagnosed without lumbar puncture using clinical symptoms and serum Borrelia burgdorferi (Bb) antibodies. This retrospective population-based cohort study included children undergoing lumbar puncture for PFP between 2019 and 2023 in Denmark's Capital Region. Diagnostic performance measures for neuroborreliosis-related PFP were compared between serum Bb IgG alone and clinical risk scores combining Bb IgG with clinical parameters. Of the 326 patients with PFP, 137 (42%) were diagnosed with neuroborreliosis and 151 (46%) had Bell's palsy. Positive predictive value for serum Bb IgG alone was 88% (95% CI 79-93) and negative predictive value was 83% (95% CI 75-88). The positive predictive value of a risk score with seven additional parameters was 90% (95% CI 81-95) and negative predictive value 87% (95% CI 80-92). The positive predictive value of serum Bb IgG alone was high in our setting, where nearly half of children with PFP had neuroborreliosis. In high endemic settings, lumbar punctures may be reduced by (i) treating all children with PFP with doxycycline or (ii) treating Bb IgG positive children and performing lumbar puncture in seronegative children.

Prognostication Following Aneurysmal Subarachnoid Hemorrhage: The Modified Hunt and Hess Grading Scale

Background This study proposes a modification to the traditional Hunt and Hess (tHH) grading scale for prognostication in aneurysmal subarachnoid hemorrhage (aSAH), which differentiates the most severe‐grade patients based on the presence or absence of brainstem dysfunction [determined by Glasgow Coma Scale (GCS) scores 3‐5]. Methods Weighted aSAH hospitalizations were retrospectively identified in the National Inpatient Sample from 2015 to 2019 and were stratified by tHH and modified HH (mHH) grades. mHH grade 5 was defined as tHH grade 5 with GCS score 3–5, while mHH grade 4 comprised tHH grade 5 with GCS score 6–8 and tHH grade 4. HH grades 1–3 do not differ between the traditional and modified scales. Measures of diagnostic performance were compared for the primary study end point [poor outcome as determined by the previously validated NIS‐SAH Outcome Measure (NIS‐SOM), shown to have high concordance with modified Rankin Scale scores &gt; 2]. External validation of the mHH was performed using data from a prospectively maintained aSAH registry. Results Among 6130 aSAH hospitalizations, 2245 (36%) were tHH grade 5. Seven hundred and eighty‐five (35%) of these had a GCS 3–5 and were designated as mHH grade 5. Poor outcomes were identified in 78% and 77% of grade 4 tHH and mHH, respectively, and in 83% and 95% of grade 5 tHH and mHH, respectively. In comparison with the tHH, the mHH achieved superior discrimination [c‐statistic 0.793 (95% CI 0.768, 0.818) versus 0.780 (95% CI 0.750, 0.807); DeLong p &lt; 0.001] for poor outcome, as well as improved specificity (0.929 versus 0.304) and positive predictive value (PPV) (0.949 versus 0.827). External registry validation of the mHH demonstrated excellent discrimination [c‐statistic 0.835 (95% CI 0.801, 0.870)], with a specificity of 0.950 and PPV of 0.905. Conclusion The mHH achieved a favorable diagnostic performance profile using retrospective data and may aid in the prognostication of high‐severity patients with aSAH.

Ghost Sign on Diffusion-Weighted Imaging Generated Apparent Diffusion Coefficient Map: Additional MRI Diagnostic Marker for Extremity Osteomyelitis

Objective The aim of this study was to determine the sensitivity and specificity and inter-reader reliability of previously known “ghost sign” and “penumbra sign” on T1-weighted (T1W) imaging and “ghost sign” on apparent diffusion coefficient (ADC) map in osteomyelitis (OM) of the extremities. Materials and Methods In this cross-sectional retrospective study, two fellowship-trained musculoskeletal readers blinded to final diagnosis of OM versus no OM were asked to report the penumbra sign and ghost sign on T1W images and ghost sign on ADC map, as well as diagnosis of OM. Cohen's kappa was used. Diagnostic performance measures including sensitivity, specificity, and accuracy were calculated. Results A sample of 178 magnetic resonance imaging (MRI) scans of pathology-proven cases were included in this study, with 41 being positive for OM and 137 being negative for OM. There was a fair inter-reader agreement for imaging signs, and moderate agreement of 0.60 for OM. The sensitivities of the penumbra sign on T1W imaging, ghost sign on T1W imaging, and ghost sign on ADC map for OM are 3.7, 9.8, and 19.5%, respectively, while their respective specificities are 98.9, 97.8, and 94.5%, respectively. All three imaging signs showed a similar (good) accuracy of 76 to 78%. Conclusion The ghost sign on ADC can be used as an additional marker for OM and is a similarly highly specific but a more sensitive sign for OM than the conventionally used penumbra sign and ghost sign on T1W imaging. Key Points

Diagnostic Performance of 18F-FDG PET/CT According to Delay After Treatment to Detect Subclinical Recurrence of Head and Neck Squamous Cell Carcinoma.

Head and neck squamous cell carcinoma (HNSCC) remains a malignancy with high rates of locoregional recurrence and poor prognosis for recurrent cases. Early detection of subclinical lesions is challenging but critical for effective patient management. Imaging surveillance after treatment, particularly 18F-FDG PET/CT, has shown promise in the diagnosis of HNSCC recurrence. The aim was to evaluate the diagnostic performance of 18F-FDG PET/CT according to delay after treatment in detecting subclinical recurrence (SCR) in HNSCC patients. Methods: In this retrospective study, all 18F-FDG PET/CT scans were performed at a single center. All adults with histologically proven HNSCC who were treated with curative intent between January 1, 2006, and December 31, 2021, were included. They had a normal clinical examination before each scan. Patients who underwent an intensive follow-up strategy after treatment had 18F-FDG PET/CT with an intravenous contrast agent at 3-6 mo and annually thereafter for 5 y. The primary endpoint was diagnostic performance (positive and negative predictive values, sensitivity, specificity, and accuracy). Results: In total, 2,566 18F-FDG PET/CT scans were performed among 852 patients, with an average of 3 scans per patient. The overall diagnostic performance measures were as follows: positive predictive value (88%), negative predictive value (98%), sensitivity (98%), specificity (89%), and accuracy (93%). There were no significant differences in diagnostic performance over time. The scans detected 126 cases of SCR (14.8%) and 118 cases of metachronous cancer (13.8%). The incidence of SCR decreased over time, with the highest detection rate in the first 2 y after treatment. Positive predictive value improved over time, reaching 90% for the digital Vision 600 system (third period) compared with 76% for the analog Gemini GXLi system (first period, P < 0.001). Multivariate analysis identified advanced stage, high body mass index, and initial PET/CT upstaging as predictive factors for detection of SCR. Conclusion: Our study demonstrates that 18F-FDG PET/CT has high diagnostic performance in detecting SCR during follow-up after treatment of HNSCC, especially in the first 2 y. Advanced tumor stage, initial PET/CT upstaging, and high body mass index were associated with a higher likelihood of SCR detection. The routine use of 18F-FDG PET/CT during follow-up seems justified for patients with HNSCC.

Diagnostic accuracy of point-of-care cardiac ultrasound for acute coronary syndromes in patients presenting with chest pain to the emergency department: a single-center prospective study.

The diagnostic accuracy of focused cardiac ultrasound (FoCUS) performed in patients presenting to the emergency department (ED) with chest pain is currently unknown. The objective of this study was to assess the diagnostic accuracy of regional wall motion abnormalities detected with FoCUS for non-ST-elevation acute coronary syndrome (NSTE-ACS) diagnosis. A Single-center prospective observational study conducted in 2022 in the ED of the University Hospital Careggi, Italy. Adult patients presenting to the ED with acute nontraumatic chest pain were enrolled, irrespective of the presence of previous regional wall motion abnormalities. Patients with ST-segment elevation myocardial infarctions and patients with hemodynamic instability were excluded. FoCUS was performed at presentation by a trained ED physician. The final diagnosis of NSTE-ACS vs. alternative diagnosis was adjudicated by an ED physician blinded to FoCUS results after a 30-day follow-up. To assess if regional wall motion abnormalities were an independent predictor of NSTE-ACS, a multivariable logistic regression model was built. Diagnostic performance measures were calculated. A sensitivity analysis considering only type-1 NSTEMIs (i.e. plaque rupture/thrombosis) was conducted. Among 686 patients, NSTE-ACS was adjudicated in 106 (15.5%) patients, 67 of which were NSTEMIs. A total of 87 (12.7%) patients had regional wall motion abnormalities detected by FoCUS, which were an independent predictor of NSTE-ACS in the multivariable logistic regression analysis. Regional wall motion abnormalities had a sensitivity of 42.5% (33.0-51.9), a specificity of 92.8% (90.6-94.9), a negative predictive value of 89.8% (87.4-92.2), and a positive predictive value of 51.7% (41.2-62.2), for NSTE-ACS. Results were consistent in the sensitivity analysis. In ED patients with chest pain and no ST elevation, the detection of regional wall motion abnormalities was a predictor of NSTE-ACS. Despite a high specificity, which indicated a possible role of FoCUS in the rule-in of NSTE-ACS, sensitivity was too low to allow a safe rule-out using FoCUS results alone.

Influence of Covariates on 18F-FDG PET/CT Diagnostic Accuracy for Liver Metastasis.

(1) Background: 18F-FDG PET/CT diagnostic accuracy for liver metastasis (LM) could be influenced by technical parameters, lesion size, and the patient's covariates. This retrospective study aimed to evaluate these covariates' impact on PET/CT sensitivity. (2) Methods: Consecutive patients with suspected LMs who underwent 18F-FDG PET/CT scans were included. PET/CT scans were interpreted visually. The reference standard integrated histopathological and imaging follow-up. Logistic regression modeling and average marginal predictions were used to calculate per-lesion diagnostic performance measures with cluster robust 95% confidence intervals and to assess the covariates' impact on PET/CT sensitivity. (3) Results: We included 192 patients with 330 lesions. 18F-FDG PET/CT exhibited a per-lesion sensitivity, specificity, positive predictive value, and negative predictive value of 86%, 79%, 91%, and 69%, respectively. In multivariate analysis, TOF PET/CT exhibited a higher sensitivity than non-TOF PET/CT (91% vs. 78%, p = 0.02). Sensitivity was reduced for lesions < 10 mm compared to larger lesions (56% vs. 93%, p < 0.001). A 5 kg/m2 increase in BMI led to an average 5% sensitivity reduction (p < 0.001). Age, sex, blood glucose level below 11 mmol/L, and liver density did not significantly impact sensitivity (p > 0.05). (4) Conclusions: 18F-FDG PET/CT sensitivity might be reduced with non-TOF PET, lesions < 10 mm, and higher BMI.

Comparative Evaluation of Chest Ultrasonography and Computed Tomography as Predictors of Malignant Pleural Effusion: A Prospective Study.

Malignant pleural effusion (MPE) is a manifestation of advanced cancer that requires a prompt and accurate diagnosis. Ultrasonography (US) and computed tomography (CT) are valuable imaging techniques for evaluating pleural effusions; however, their relative predictive ability for a malignant origin remains debatable. This prospective study aimed to compare chest US with CT findings as predictors of malignancy in patients with undiagnosed exudative pleural effusion. Fifty-four adults with undiagnosed exudative pleural effusions underwent comprehensive clinical evaluation including chest US, CT, and histopathologic biopsy. Blinded radiologists evaluated the US and CT images for features suggestive of malignancy, based on predefined criteria. Diagnostic performance measures were calculated using histopathology as a reference standard. Of the 54 patients, 33 (61.1%) had MPEs confirmed on biopsy. No significant differences between US and CT were found in detecting parietal pleural abnormalities, lung lesions, chest wall invasion, or liver metastasis. US outperformed CT in identifying diaphragmatic pleural thickening ≥10 mm (33.3% vs. 6.1%, p < 0.001) and nodularity (45.5% vs. 3%, p < 0.001), whereas CT was superior for mediastinal thickening (48.5% vs. 15.2%, p = 0.002). For diagnosing MPE, diaphragmatic nodularity detected by US had 45.5% sensitivity and 100% specificity, whereas CT mediastinal thickening had 48.5% sensitivity and 90.5% specificity. Both US and CT demonstrate reasonable diagnostic performance for detecting MPE, with particular imaging findings favoring a malignant origin. US may be advantageous for evaluating diaphragmatic pleural involvement, whereas CT is more sensitive to mediastinal abnormalities.

White light computer-aided optical diagnosis of diminutive colorectal polyps in routine clinical practice.

Background and study aims Artificial Intelligence (AI) systems could make the optical diagnosis (OD) of diminutive colorectal polyps (DCPs) more reliable and objective. This study was aimed at prospectively evaluating feasibility and diagnostic performance of AI-standalone and AI-assisted OD of DCPs in a real-life setting by using a white light-based system (GI Genius, Medtronic Co, Minneapolis, Minnesota, United States). Patients and methods Consecutive colonoscopy outpatients with at least one DCP were evaluated by 11 endoscopists (5 experts and 6 non-experts in OD). DCPs were classified in real time by AI (AI-standalone OD) and by the endoscopist with the assistance of AI (AI-assisted OD), with histopathology as the reference standard. Results Of the 480 DCPs, AI provided the outcome "adenoma" or "non-adenoma" in 81.4% (95% confidence interval [CI]: 77.5-84.6). Sensitivity, specificity, positive and negative predictive value, and accuracy of AI-standalone OD were 97.0% (95% CI 94.0-98.6), 38.1% (95% CI 28.9-48.1), 80.1% (95% CI 75.2-84.2), 83.3% (95% CI 69.2-92.0), and 80.5% (95% CI 68.7-82.8%), respectively. Compared with AI-standalone, the specificity of AI-assisted OD was significantly higher (58.9%, 95% CI 49.7-67.5) and a trend toward an increase was observed for other diagnostic performance measures. Overall accuracy and negative predictive value of AI-assisted OD for experts and non-experts were 85.8% (95% CI 80.0-90.4) vs. 80.1% (95% CI 73.6-85.6) and 89.1% (95% CI 75.6-95.9) vs. 80.0% (95% CI 63.9-90.4), respectively. Conclusions Standalone AI is able to provide an OD of adenoma/non-adenoma in more than 80% of DCPs, with a high sensitivity but low specificity. The human-machine interaction improved diagnostic performance, especially when experts were involved.