Difference In Diagnostic Performance Research Articles

Qualitative and quantitative strain and shear wave elastography paradigm in differentiation of breast lesions

BackgroundBreast cancer is the most common life-threatening cancer in women worldwide. A high number of women are going through biopsy procedures for characterization of breast masses every day and yet 75% of the pathological results prove these masses to be benign. Ultrasound (US) elastography is a non-invasive technique that measures tissue stiffness. It is convenient for differentiating benign from malignant breast tumors. Our study aims to evaluate the role of qualitative ultrasound elastography scoring (ES), quantitative mass strain ratio (SR), and shear wave elasticity ratio (SWER) in differentiation between benign and malignant breast lesions.ResultsAmong 51 female patients with 77 histopathologically proved breast lesions, 57 breast masses were malignant and 20 were benign. All patients were examined by B-mode ultrasound then strain and shear wave elastographic examinations using ultrasound machine (Logiq E9, GE Medical Systems) with 8.5–12 MHz high-frequency probes. Our study showed that ES best cut-off point > 3 with sensitivity, specificity, PPV, NPP, accuracy was 94.7%, 85%, 94.7%, 85%, 90.9%, respectively, and AUC = 0.926 at P < 0.001, mass SR the best cut-off point > 4.6 with sensitivity, specificity, PPV, NPP, accuracy was 96.5%, 80%, 93.2%, 88.9%, 92.2%, respectively, and AUC = 0.860 at P < 0.001, SWER the best cut-off value > 4.9 with sensitivity, specificity, PPV, NPP and accuracy was 91.2%, 80%, 92.9%, 76.2%, 93.5%, respectively, and AUC = 0.890 at P < 0.001. The mean mass strain ratio for malignant lesions is 10.1 ± 3.7 SD and for solid benign lesions 4.7 ± 4.3 SD (p value 0.001). The mean shear wave elasticity ratio for malignant lesions is 10.6 ± 5.4 SD and for benign (solid and cystic) lesions 3.6 ± 4.2 SD. Using ROC curve and Youden index, the difference in diagnostic performance between ES, SR and SWER was not significant in differentiation between benign and malignant breast lesions and also was non-significant difference when comparing them with conventional US alone.ConclusionES, SR, and SWER have a high diagnostic performance in differentiating malignant from benign breast lesions with no statistically significant difference between them.

Mesenteric abnormalities play an important role in grading intestinal fibrosis in patients with Crohn's disease: a computed tomography and clinical marker-based nomogram.

Background:While the grading of intestinal fibrosis is closely related to the therapeutic strategy of patients with Crohn’s disease (CD), it has not yet been well resolved. Mesenteric abnormalities are inextricably linked to intestinal fibrosis.Objectives:We aimed to establish an optimal model for assessing intestinal fibrosis using computed tomography enterography (CTE) and clinical markers.Design:A total of 174 patients with CD between January 2014 and June 2020 were included in this retrospective multicentre study.Methods:All patients underwent CTE within 3 months prior to surgery. Intestinal fibrosis was pathologically scored as non-mild or moderate-to-severe. Selected imaging of the intestinal walls and mesentery and/or clinical factors were used to develop the diagnostic models. The area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the discrimination performance of the models. A decision curve analysis was performed to evaluate the clinical usefulness of the models.Results:One-, two-, and three-variable models were identified as possible diagnostic models. Model 1 [mesenteric creeping fat index (MCFI)], Model 2 (mesenteric oedema and MCFI), and Model 3 (mesenteric oedema, MCFI, and disease duration) were established. The AUCs of Model 1 in training and test cohorts 1 and 2 were 0.799, 0.859, and 0.693, respectively; Model 2 was 0.851, 0.833, and 0.757, respectively; and Model 3 was 0.832, 0.821, and 0.850, respectively. We did not observe any significant difference in diagnostic performance between the training and total test cohorts in any model (all p > 0.05). The decision curves showed that Model 3 had the highest net clinical benefit in test cohort 2. The nomogram of this optimal model was constructed by considering the favourable and robust performance of Model 3.Conclusion:A nomogram integrating mesenteric abnormalities on CTE with a clinical marker was optimal for differentiating between non-mild and moderate-to-severe fibrosis in patients with CD.

Comparison of O-RADS, GI-RADS, and ADNEX for Diagnosis of Adnexal Masses: An External Validation Study Conducted by Junior Sonologists.

To externally validate the Ovarian-adnexal Reporting and Data System (O-RADS) and evaluate its performance in differentiating benign from malignant adnexal masses (AMs) compared with the Gynecologic Imaging Reporting and Data System (GI-RADS) and Assessment of Different NEoplasias in the adneXa (ADNEX). A retrospective analysis was performed on 734 cases from the Second Affiliated Hospital of Fujian Medical University. All patients underwent transvaginal or transabdominal ultrasound examination. Pathological diagnoses were obtained for all the included AMs. O-RADS, GI-RADS, and ADNEX were used to evaluate AMs by two sonologists, and the diagnostic efficacy of the three systems was analyzed and compared using pathology as the gold standard. We used the kappa index to evaluate the inter-reviewer agreement (IRA). A total of 734 AMs, including 564 benign masses, 69 borderline masses, and 101 malignant masses were included in this study. O-RADS (0.88) and GI-RADS (0.90) had lower sensitivity than ADNEX (0.95) (P < .05), and the PPV of O-RADS (0.98) was higher than that of ADNEX (0.96) (P < .05). These three systems showed good IRA. O-RADS, GI-RADS, and ADNEX showed little difference in diagnostic performance among resident sonologists. These three systems have their own characteristics and can be selected according to the type of center, access to patients' clinical data, or personal comfort.

P-32 EVALUATION OF HEPATIC FIBROSIS THROUGH NON-INVASIVE METHODS IN PATIENTS WITH CHRONIC VIRAL HEPATITIS B AND C

Biopsy has been considered the method of choice for staging fibrosis in liver disease. However, as it is an invasive method subject to sampling errors and morbidity, new non-invasive methods have been proposed for the assessment of liver fibrosis. To evaluate and compare serum fibrosis biomarkers (APRI and FIB4) with transient liver elastography (THE), gold standard in this study in patients with chronic viral hepatitis B and C. Cross-sectional study of patients with chronic hepatitis B or C virus undergoing THE. The patients were evaluated using serum liver fibrosis markers APRI and FIB4. The degree of fibrosis ≥ 2 of the Metavir classification was defined as significant fibrosis. The diagnostic performance of both methods was calculated and compared using the ROC curve (AUROC). The study included 73 patients, 50 with HBV and 23 with HCV; 50.7% were female, mean age 48.6 ± 13.3 years. Significant fibrosis was observed in 31 patients. The accuracy of serum markers in the diagnosis of liver fibrosis was determined by AUROC, APRI 0.79 and FIB4 0.76 (P = .0.42); PPV and NPV APRI 91.7% and 76.9% respectively; FIB4, PPV = 87.5% and NPV = 77.8%. The study demonstrated that there was no difference in diagnostic performance between the APRI and FIB4 methods, which were considered tests with good accuracy in the diagnosis of significant fibrosis in patients with chronic viral hepatitis.

Effect of Point Spread Function Deconvolution in Reconstruction of Brain 18F-FDG PET Images on the Diagnostic Thinking Efficacy in Alzheimer's Disease.

Purpose: This study aims to determine the effect of applying Point Spread Function (PSF) deconvolution, which is known to improve contrast and spatial resolution in brain 18F-FDG PET images, to the diagnostic thinking efficacy in Alzheimer's disease (AD).Methods: We compared Hoffman 3-D brain phantom images reconstructed with or without PSF. The effect of PSF deconvolution on AD diagnostic clinical performance was determined from digital brain 18F-FDG PET images of AD (n = 38) and healthy (n = 35) subjects compared to controls (n = 36). Performances were assessed with SPM at the group level (p < 0.001 for the voxel) and at the individual level by visual interpretation of SPM T-maps (p < 0.005 for the voxel) by the consensual analysis of three experienced raters.Results: A mix of large hypometabolic (1,483cm3, mean value of −867 ± 492 Bq/ml) and intense hypermetabolic (902 cm3, mean value of 1,623 ± 1,242 Bq/ml) areas was observed in the PSF compared to the no PSF phantom images. Significant hypometabolic areas were observed in the AD group compared to the controls, for reconstructions with and without PSF (respectively 23.7 and 26.2 cm3), whereas no significant hypometabolic areas were observed when comparing the group of healthy subjects to the control group. At the individual level, no significant differences in diagnostic performances for discriminating AD were observed visually (sensitivity of 89 and 92% for reconstructions with and without PSF respectively, similar specificity of 74%).Conclusion: Diagnostic thinking efficacy performances for diagnosing AD are similar for 18F-FDG PET images reconstructed with or without PSF.

Diffusion-weighted imaging versus dynamic contrast-enhanced imaging for pre-operative diagnosis of deep myometrial invasion in endometrial cancer: A meta-analysis

PurposeThis study investigates the differences in diagnostic performance between diffuse-weighted imaging (DWI) and dynamic contrast-enhanced imaging (DCE), either alone or in combination with T2-weighted imaging (T2WI), for diagnosing deep myometrial invasion (dMI) of endometrial cancers (EC). MethodsWe performed a comprehensive search for published studies comparing DWI and DCE for preoperatively diagnosing dMI of EC. The overall diagnostic accuracy of each test was calculated using the areas under the summary receiver operating characteristic curves (AUCs). The sensitivities and specificities were compared using bivariate meta-regression. ResultsPooled analysis of nineteen studies with 961 patients (main group) showed that DWI had a larger AUC (0.943, 95% confidence interval (CI) = 0.921–0.967) than DCE (0.922, 95% CI = 0.893–0.953). For the subgroup comprising 7 studies, DWI combined with T2WI and DCE combined with T2WI showed AUCs of 0.959 (95% CI, 0.932–0.986) and 0.929 (95% CI, 0.847–1.000), respectively. None of the differences in AUCs were statistically significant. All comparisons of the sensitivities and specificities of the main group and subgroup also showed no significant differences. ConclusionThis meta-analysis found no significant difference in diagnostic performance between DWI and DCE for diagnosis of dMI in EC. DWI may be preferred for its ease of use in clinical practice.

Evaluation of the LI-RADS treatment response algorithm in hepatocellular carcinoma after trans-arterial chemoembolization

PurposeTo evaluate the diagnostic performance of LI-RADS treatment response algorithm (LR-TRA) and modified RECIST (mRECIST) for the detection of viable hepatocellular carcinoma (HCC) on MRI after trans-arterial chemoembolization (TACE). Materials and methodsThis retrospective study includes cirrhotic patients that underwent trans-arterial chemoembolization prior to liver transplantation from 2013 to 2017 with a pre- and post-treatment MRI available. Three blinded readers assigned a LR-TRA and mRECIST category to each lesion. Lesions on MRI and explant pathology were matched and characterized as complete (100% necrosis) or incomplete necrosis (≤99% necrosis). Diagnostic performance of LR-TRA and mRECIST were calculated with a generalized estimating equation. ResultsA total of 52 patients with 71 lesions were included, 47 with incomplete and 24 with complete necrosis. In consensus, 45 lesions were categorized as LR-TR Nonviable, of which 62.2% (28/45) had incomplete and 37.8% (17/45) had complete necrosis. Six lesions were categorized as LR-TR Equivocal, of which 33.3% (2/6) had incomplete and 66.7% (4/6) had complete necrosis. Twenty lesions were categorized as LR-TR Viable of which 85.0% (17/20) had incomplete and 15.0% (3/20) had complete necrosis. The sensitivity of LR-TR Viable for detecting incompletely necrotic tumor when LR-TR Equivocal was considered as viable, in consensus was 40.4%; specificity 70.8%; accuracy 50.7%. The sensitivity of mRECIST for detecting incompletely necrotic tumor was 37.0%; specificity 79.2%; accuracy 51.4%. There was no significant difference in diagnostic performance between mRECIST and LR-TRA (p = 0.14–0.33). Agreement for LR-TRA category was moderate (k = 0.53 [95% CI: 0.45, 0.67]). ConclusionLI-RADS treatment response algorithm demonstrates high specificity and low to moderate sensitivity for the detection of viable HCC after TACE in a North American cirrhotic cohort, without significant difference in diagnostic performance between LR-TRA and mRECIST.

Application of Diffusion Weighted Imaging Techniques for Differentiating Benign and Malignant Breast Lesions.

To explore the value of apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM), and diffusional kurtosis imaging (DKI) based on diffusion weighted magnetic resonance imaging (DW-MRI) in differentiating benign and malignant breast lesions. A total of 215 patients with breast lesions were prospectively collected for breast MR examination. Single exponential, IVIM, and DKI models were calculated using a series of b values. Parameters including ADC, perfusion fraction (f), tissue diffusion coefficient (D), perfusion-related incoherent microcirculation (D*), average kurtosis (MK), and average diffusivity (MD) were compared between benign and malignant lesions. ROC curves were used to analyze the optimal diagnostic threshold of each parameter, and to evaluate the diagnostic efficacy of single and combined parameters. ADC, D, MK, and MD values were significantly different between benign and malignant breast lesions (P<0.001). Among the single parameters, ADC had the highest diagnostic efficiency (sensitivity 91.45%, specificity 82.54%, accuracy 88.84%, AUC 0.915) and the best diagnostic threshold (0.983 μm2/ms). The combination of ADC and MK offered high diagnostic performance (sensitivity 90.79%, specificity 85.71%, accuracy 89.30%, AUC 0.923), but no statistically significant difference in diagnostic performance as compared with single-parameter ADC (P=0.268). The ADC, D, MK, and MD parameters have high diagnostic value in differentiating benign and malignant breast lesions, and of these individual parameters the ADC has the best diagnostic performance. Therefore, our study revealed that the use of ADC alone should be useful for differentiating between benign and malignant breast lesions, whereas the combination of MK and ADC might improve the diagnostic performance to some extent.

Diagnostic Accuracy and Failure Mode Analysis of a Deep Learning Algorithm for the Detection of Cervical Spine Fractures.

Artificial intelligence decision support systems are a rapidly growing class of tools to help manage ever-increasing imaging volumes. The aim of this study was to evaluate the performance of an artificial intelligence decision support system, Aidoc, for the detection of cervical spinal fractures on noncontrast cervical spine CT scans and to conduct a failure mode analysis to identify areas of poor performance. This retrospective study included 1904 emergent noncontrast cervical spine CT scans of adult patients (60 [SD, 22] years, 50.3% men). The presence of cervical spinal fracture was determined by Aidoc and an attending neuroradiologist; discrepancies were independently adjudicated. Algorithm performance was assessed by calculation of the diagnostic accuracy, and a failure mode analysis was performed. Aidoc and the neuroradiologist's interpretation were concordant in 91.5% of cases. Aidoc correctly identified 67 of 122 fractures (54.9%) with 106 false-positive flagged studies. Diagnostic performance was calculated as the following: sensitivity, 54.9% (95% CI, 45.7%-63.9%); specificity, 94.1% (95% CI, 92.9%-95.1%); positive predictive value, 38.7% (95% CI, 33.1%-44.7%); and negative predictive value, 96.8% (95% CI, 96.2%-97.4%). Worsened performance was observed in the detection of chronic fractures; differences in diagnostic performance were not altered by study indication or patient characteristics. We observed poor diagnostic accuracy of an artificial intelligence decision support system for the detection of cervical spine fractures. Many similar algorithms have also received little or no external validation, and this study raises concerns about their generalizability, utility, and rapid pace of deployment. Further rigorous evaluations are needed to understand the weaknesses of these tools before widespread implementation.

The preoperative localisation of small parathyroid adenomas improves when adding Tc-99m-Sestamibi SPECT to multiphase contrast-enhanced CT

ObjectivesTo investigate the incremental value of Sestamibi SPECT combined with a non-enhanced and contrast-enhanced CT, using SPECT/CT, for the preoperative localisation of small parathyroid adenomas (PTA).MethodsRetrospectively, 147 patients surgically cured from primary hyperparathyroidism, as verified by biochemistry 6 months postoperatively, were included. All patients had preoperatively undergone a dual time 99mTechnetium-Sestamibi SPECT (S) with multiphase CT including native (N), arterial (A) and venous (V) phases. Independently, two radiologists blinded from both the surgical and the preoperative imaging reports, sequentially performed PTA localisation starting with either [A] or [V], thereafter [A + N] or [V + N] and finally with the complete [A + N + S] or [V + N + S]. PTA localisation was reported for each image-set. The readers results were combined and the diagnostic performance for each image set was determined. Sensitivity was also calculated for the different quartiles of PTA weight distribution.ResultsThe median adenoma weight was 315 mg. No statistically significant differences in diagnostic performance between arterial and venous based image sets were found. The net effect of adding [N] was to increase specificity. Sestamibi SPECT significantly increased the overall diagnostic accuracy for arterial- and venous-based image sets, p = 0.0008 and p = 0.001, respectively. [A + N + S] was found to have the highest diagnostic performance with 86.5% sensitivity and 94.9% overall accuracy. [A + N + S] was particularly advantageous for locating PTA in the lower weight quartiles.ConclusionsNative CT-phase and dual time point Sestamibi SPECT increase specificity and sensitivity, respectively. These, in combination with a single contrast-enhanced CT-phase is the most optimal examination protocol for preoperative localisation of PTA using SPECT/CT.

Differentiation between benign and malignant vertebral compression fractures using qualitative and quantitative analysis of a single fast spin echo T2-weighted Dixon sequence

ObjectivesTo determine and compare the qualitative and quantitative diagnostic performance of a single sagittal fast spin echo (FSE) T2-weighted Dixon sequence in differentiating benign and malignant vertebral compression fractures (VCF), using multiple readers and different quantitative methods.MethodsFrom July 2014 to June 2020, 95 consecutive patients with spine MRI performed prior to cementoplasty for acute VCFs were retrospectively included. VCFs were categorized as benign (n = 63, mean age = 76 ± 12 years) or malignant (n = 32, mean age = 63 ± 12 years) with a best valuable comparator as a reference. Qualitative analysis was independently performed by four radiologists by categorizing each VCF as either benign or malignant using only the image sets provided by FSE T2-weighted Dixon sequences. Quantitative analysis was performed using two different regions of interest (ROI1-2) and three methods (signal drop, fat fraction (FF) from ROIs, FF maps). Diagnostic performance was compared using ROC curves analyses. Interobserver agreement was assessed using kappa statistics and intraclass correlation coefficients (ICC).ResultsThe qualitative diagnostic performance ranged from area under the curve (AUC) = 0.97 (95% CI: 0.91–1.00) to AUC = 0.99 (95% CI: 0.95–1.0). The quantitative diagnostic performance ranged from AUC = 0.82 (95% CI: 0.73–0.89) to AUC = 0.97 (95% CI: 0.91–0.99). Pairwise comparisons showed no statistical difference in diagnostic performance (all p > 0.0013, Bonferroni-corrected p < 0.0011). All five cases with disagreement among the readers were correctly diagnosed at quantitative analysis using ROI2. Interobserver agreement was excellent for both qualitative and quantitative analyses.ConclusionsA single FSE T2-weighted Dixon sequence can be used to differentiate benign and malignant VCF with high diagnostic performance using both qualitative and quantitative analyses, which can provide complementary information.Key Points• Qualitative analysis of a single FSE T2-weighted Dixon sequence yields high diagnostic performance and excellent observer agreement for differentiating benign and malignant compression fractures.• The same FSE T2-weighted Dixon sequence allows quantitative assessment with high diagnostic performance.• Quantitative data can readily be extracted from the FSE T2-weighted Dixon sequence and may provide complementary information to the qualitative analysis, which may be useful in doubtful cases.

Comparison of electrodiagnosis, neurosonography and MR neurography in localization of ulnar neuropathy at the elbow

IntroductionIn patients with ulnar neuropathy at the elbow (UNE) the precise determination of the site of lesion is important for subsequent differential diagnostic considerations and therapeutic management. Due to a paucity of comparable data, to better define the role of different diagnostic tests, we performed the first prospective study comparing the diagnostic accuracy of short segment nerve stimulation, nerve ultrasonography, MR neurography (MRN), and diffusion tensor imaging (DTI) in patients with UNE. MethodsUNE was clinically diagnosed in 17 patients with 18 affected elbows. For all 18 affected elbows in patients and 20 elbows in 10 healthy volunteers, measurements of all different diagnostic tests were performed at six anatomical positions across the elbow with measuring points from distal (D4) to proximal (P6) in relation to the medial epicondyle (P0). Additional qualitative assessment regarding structural changes of surrounding nerve anatomy was conducted. ResultsThe difference between affected arms of patients and healthy control arms were most frequently the largest at measure intervals D2 to P0 and P0 to P2 for electrophysiological testing, or measure points P0 and P2 for all other devices, respectively. At both levels P0 and at P2, T2 contrast-to-noise ratio (CNR) of MRN and mean diffusivity (MD) of DTI-based MRN showed best accuracies. DiscussionThis study revealed differences in diagnostic performance of tests concerning a specific location of UNE, with better results for T2 contrast to noise ratio (CNR) in MRN and mean diffusivity of DTI-based MRN. Additional testing with MRN and nerve ultrasonography is recommended to uncover anatomical changes.

Fibrinogen performs better than D-dimer for the diagnosis of periprosthetic joint infection: a meta-analysis of diagnostic trials

PurposeD-dimer and fibrinogen, both belonging to coagulation parameters, are controversial for the diagnosis of periprosthetic joint infection (PJI). This meta-analysis was conducted to compare their diagnostic accuracies for PJI by synthesizing currently available evidence.MethodsCochrane Library, MEDLINE, Web of Science, and Embase up to March 1, 2020, and other relevant articles were searched. Five hundred and eighty-one articles were identified after initial research, and 11 studies were included finally. No threshold effects were found between studies. The pooled sensitivity, specificity, and positive and negative likelihood ratio were reported to evaluate the diagnostic performance with heterogeneity analysis. Z test statistics was used to analyze the difference of diagnostic performance between D-dimer and fibrinogen.ResultsThe pooled sensitivity, specificity, and positive and negative likelihood ratio of D-dimer for PJI were 0.79 (95% [CI], 0.72–0.85), 0.77 (0.67–0.84), 3.38 (2.21–5.18), and 0.27 (0.18–0.41), respectively. As for fibrinogen, the pooled sensitivity, specificity, and positive and negative likelihood ratio for PJI were 0.75 (0.68–0.80), 0.85 (0.82–0.88), 5.12 (4.22–6.22), and 0.30 (0.23–0.37), respectively. Great heterogeneity was found in studies for D-dimer, and univariate meta-regression analysis revealed that number of involved joints, disease spectrum, comorbidities influencing D-dimer, and sample sources were the source of heterogeneity. Z test found that the pooled specificity of fibrinogen was significantly higher than D-dimer (0.85 ± 0.01 versus 0.77 ± 0.04, p = 0.03). The pooled positive likelihood ratio of fibrinogen was significantly higher than D-dimer (5.12 ± 0.51 versus 3.38 ± 0.74, p = 0.03).ConclusionBased on currently available evidence, the meta-analysis suggests that fibrinogen performs better than D-dimer as a rule-in diagnostic tool for its higher specificity. However, more prospective trials with larger size are still needed to provide further confirmation.Trial registrationThis meta-analysis was prospectively registered on PROSPERO (International prospective register of systematic reviews), and the registering number was CRD42020177176.

Differential diagnosis of parkinsonism: a head-to-head comparison of FDG PET and MIBG scintigraphy

[18F]fluorodeoxyglucose (FDG) PET and [123I]metaiodobenzylguanidine (MIBG) scintigraphy may contribute to the differential diagnosis of neurodegenerative parkinsonism. To identify the superior method, we retrospectively evaluated 54 patients with suspected neurodegenerative parkinsonism, who were referred for FDG PET and MIBG scintigraphy. Two investigators visually assessed FDG PET scans using an ordinal 6-step score for disease-specific patterns of Lewy body diseases (LBD) or atypical parkinsonism (APS) and assigned the latter to the subgroups multiple system atrophy (MSA), progressive supranuclear palsy (PSP), or corticobasal syndrome. Regions-of-interest analysis on anterior planar MIBG images served to calculate the heart-to-mediastinum ratio. Movement disorder specialists blinded to imaging results established clinical follow-up diagnosis by means of guideline-derived case vignettes. Clinical follow-up (1.7 ± 2.3 years) revealed the following diagnoses: n = 19 LBD (n = 17 Parkinson’s disease [PD], n = 1 PD dementia, and n = 1 dementia with Lewy bodies), n = 31 APS (n = 28 MSA, n = 3 PSP), n = 3 non-neurodegenerative parkinsonism; n = 1 patient could not be diagnosed and was excluded. Receiver operating characteristic analyses for discriminating LBD vs. non-LBD revealed a larger area under the curve for FDG PET than for MIBG scintigraphy at statistical trend level for consensus rating (0.82 vs. 0.69, p = 0.06; significant for investigator #1: 0.83 vs. 0.69, p = 0.04). The analysis of PD vs. MSA showed a similar difference (0.82 vs. 0.69, p = 0.11; rater #1: 0.83 vs. 0.69, p = 0.07). Albeit the notable differences in diagnostic performance did not attain statistical significance, the authors consider this finding clinically relevant and suggest that FDG PET, which also allows for subgrouping of APS, should be preferred.

Diagnostic performance of MRI for HCC according to contrast agent type: a systematic review and meta-analysis.

Conflicting results have been reported between the use of extracellular contrast agent (ECA) and hepatobiliary contrast agent (HBA) when magnetic resonance imaging (MRI) is used for the diagnosis of hepatocellular carcinoma (HCC). Therefore, we aimed to compare the diagnostic performance of MRI using ECA (ECA-MRI) and HBA (HBA-MRI). Original studies reporting the diagnostic performance of contrast-enhanced MRI for the diagnosis of HCC published between January 2010 and February 2020 were identified in a Pubmed, EMBASE, and Cochrane Library database search. The pooled sensitivity and specificity of ECA-MRI and HBA-MRI were calculated using a bivariate random effects model and compared using a joint-model bivariate meta-regression. Subgroup analyses were performed to compare the diagnostic performance of ECA-MRI and HBA-MRI according to study design, underlying liver disease, lesion size, reference standard, and imaging criteria. Of the 1760 screened articles, 31 studies were included: 15 studies included 2890 lesions imaged using ECA-MRI and 19 studies included 3893 lesions imaged using HBA-MRI. The pooled sensitivity and specificity were not significantly different between ECA-MRI (sensitivity, 72% [95% confidence interval 65-79%]; specificity 92% [89-95%]) and HBA-MRI (76% [68-83%]; 92% [87-95%], p = 0.72). Subgroup analyses did not find differences in diagnostic performance between ECA-MRI and HBA-MRI according to study design (p ≥ 0.11), underlying disease (p ≥ 0.09), lesion size (≤ 2cm, p = 0.97), reference standard (p = 0.70), or imaging criteria (p = 0.33). ECA-MRI showed similar performance to HBA-MRI in the diagnosis of HCC. The contrast agent might be selected with consideration of the advantages of each agent.

Laboratory testing for the diagnosis of COVID-19

Rapid and accurate laboratory diagnosis of active COVID-19 infection is one of the cornerstones of pandemic control. With the myriad of tests available in the market, the use of correct specimen type and laboratory-testing technique in the right clinical scenario could be challenging for non-specialists. In this mini-review, we will discuss the difference in diagnostic performance for different upper and lower respiratory tract specimens, and the role of blood and fecal specimens. We will analyze the performance characteristics of laboratory testing techniques of nucleic acid amplification tests, antigen detection tests, antibody detection tests, and point-of-care tests. Finally, the dynamics of viral replication and antibody production, and laboratory results interpretation in conjunction with clinical scenarios will be discussed.

Reading High Breast Density Mammograms: Differences in Diagnostic Performance between Radiologists from Hong Kong SAR/Guangdong Province in China and Australia

Background:Variations in the performance of radiologists reading mammographic images are well reported, but key parameters explaining such variations in different countries are not fully explored. The main aim of this study is to investigate performances of Chinese (Hong Kong SAR and Guangdong Province) and Australian radiologists in interpreting dense breast mammographic images. Methods:A test set, contained 60 mammographic examinations with high breast density, was used to assess radiologists’ performance. Twelve Chinese and thirteen Australian radiologists read all the cases independently and were asked to identify all lesions and provide a grade from 1 to 5 to each lesion. Case sensitivity, specificity, lesion sensitivity, AUC and JAFROC were used to assess radiologists’ performances. Demographic information and reading experience were also collected from the readers. Performance scores were compared between the two populations and the relationships between performance scores and their reading experience were discovered. Results:For radiologists who were less than 40-year-old, lesion sensitivity, AUC and JAFROC were significantly lower in Chinese radiologists than those in Australian (52.10% vs 71.45%, p=0.043; 0.76 vs 0.84, p=0.031; 0.59 vs 0.72, p=0.045; respectively). Australian radiologists with less than 10 years of reading experience had higher AUC and JAFROC scores compared with their Chinese counterparts (0.83 vs 0.76, p=0.039; 0.70 vs 0.56, p=0.020, respectively). Conclusions:We found that younger Australian radiologists performed better at reading dense breast cases which is likely to be linked to intensive fellowship training, immersion in a screening program and exposure to the benefits of a performance-measuring education tool.

Comparison of the diagnostic performance of magnetic resonance elastography and Wisteria foribunda agglutinin-positive Mac-2-binding protein in the determination of advanced liver fibrosis stages in patients with chronic liver disease.

The present study aimed to compare the accuracy of Wisteria floribunda agglutinin-positive Mac-2-binding protein (WFA+-M2BP) and magnetic resonance elastography (MRE) in determining the liver fibrosis stage in patients with chronic liver disease. A retrospective review of a prospectively maintained database was performed. The eligible patients had hepatic tumors and chronic liver disease, including hepatitis B (HBV) and HCV. All patients underwent blood sampling, MRE and hepatectomy at Changhua Christian Hospital (Changhua, Taiwan). Surgical specimens were used to determine definitive histopathological diagnoses and liver fibrosis stages. Measurement of liver stiffness was performed via MRI. The value of WFA+-M2BP in each patient was also assessed. The area under the receiver operating characteristic (ROC) curve (AUC) was measured to compare the diagnostic accuracy of the two examinations. The results indicated that the serum WFA+-M2BP levels were able to detect severe liver fibrosis (≥F3) in patients with chronic liver disease and performed as well as MRE in patients with HCV. Of the 238 patients enrolled in the present study, 135 had chronic HBV 75 had chronic HCV, 92 had early liver fibrosis (F1-F2) and 139 patients had advanced liver fibrosis (F3-F4). In predicting fibrosis stages ≥F3, MRE had an AUC of 0.89 with a cutoff value of 3.76 and serum WFA+-M2BP had an AUC of 0.65 with a cutoff value of 1.32. MRE had higher AUCs than serum WFA+-M2BP for predicting the severity based on the fibrosis stage in the total cohort and the HBV subgroup. In patients with HCV, no significant differences in diagnostic performance were identified between MRE and serum WFA+-M2BP. In conclusion, determination of WFA+-M2BP as a biomarker for predicting severe liver fibrosis (≥F3) is a reliable and non-invasive method and performs as well as MRE in patients with chronic liver disease, particularly those with HCV.

Image-guided core needle biopsy for Ewing sarcoma of bone: a 10-year single-institution review.

To evaluate the performance of image-guided core needle biopsy (IGCNB) for the diagnosis of Ewing sarcoma of bone. All patients with a confirmed diagnosis of Ewing sarcoma who underwent IGCNB between January 2007 and December 2016 were included in this retrospective study. Analysis included mean age, skeletal distribution, imaging modality used for biopsy guidance, type of anaesthesia, needle type, number of passes, type of tissue sampled, and complications. The study included 139 patients (94 males and 45 females; mean age 18.7years) who underwent 141 image-guided core needle biopsies as the primary diagnostic test. Of these, 101 were CT-guided, 38 ultrasound-guided, and 2 utilised both CT and ultrasound guidance. A total of 97.9% were diagnostic at first procedure. Of the 3 non-diagnostic cases, 2 underwent a further IGCNB and were positive, while 1 patient required an open surgical procedure. Only 1 patient (0.7%) suffered an immediate complication, and there were no recorded delayed complications. IGCNB is a safe procedure providing a positive diagnosis of Ewing sarcoma of bone in a very high percentage of cases. It should be the first-line method for establishing a diagnosis in suspected Ewing sarcoma of bone. • Image-guided core needle biopsy is a safe procedure providing a positive diagnosis of Ewing sarcoma of bone in a very high percentage of cases. • Image-guided core needle biopsy should be the first-line method for establishing a definitive diagnosis in Ewing sarcoma and should be performed at a specialist sarcoma referral centre. • When technically feasible, extra-osseous soft tissue alone can be sampled with confidence as there is no difference in diagnostic performance whether bone or an extra-osseous soft tissue component of the tumour is sampled.

Comparison of 3 deep learning neural networks for classifying the relationship between the mandibular third molar and the mandibular canal on panoramic radiographs.

The aim of this study was to compare time and storage space requirements, diagnostic performance, and consistency among 3 image recognition convolutional neural networks (CNNs) in the evaluation of the relationships between the mandibular third molar and the mandibular canal on panoramic radiographs. Of 600 panoramic radiographs, 300 each were assigned to noncontact and contact groups based on the relationship between the mandibular third molar and the mandibular canal. The CNNs were trained twice by using cropped image patches with sizes of 70 × 70 pixels and 140 × 140 pixels. Time and storage space were measured for each system. Accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) were determined. Intra-CNN and inter-CNN consistency values were calculated. Time and storage space requirements depended on the depth of CNN layers and number of learned parameters, respectively. The highest AUC values ranged from 0.88 to 0.93 in the CNNs created by 70 × 70 pixel patches, but there were no significant differences in diagnostic performance among any of the models with smaller patches. Intra-CNN and inter-CNN consistency values were good or very good for all CNNs. The size of the image patches should be carefully determined to ensure acquisition of high diagnostic performance and consistency.