scholarly journals Qualitative analysis of contrast-enhanced ultrasound in the diagnosis of small, TR3–5 benign and malignant thyroid nodules measuring ≤1 cm

2020 ◽  
Vol 93 (1111) ◽  
pp. 20190923
Author(s):  
Xin Li ◽  
Feng Gao ◽  
Fan Li ◽  
Xiao-xia Han ◽  
Si-hui Shao ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Qualitative Analysis ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Diagnostic Performance ◽  
Thyroid Nodules ◽  
Area Under The Curve ◽  
Contrast Enhanced Ultrasound ◽  
Contrast Enhanced ◽  
Sensitivity Specificity

Objective: To evaluate the performance of contrast-enhanced ultrasound in the diagnosis of small, solid, TR3–5 benign and malignant thyroid nodules (≤1 cm). Methods: From January 2016 to March 2018, 185 thyroid nodules from 154 patients who underwent contrast enhanced ultrasound (CEUS) and fine-needle aspiration or thyroidectomy in Shanghai General Hospital were included. The χ2 test was used to compare the CEUS characteristics of benign and malignant thyroid nodules, and the CEUS features of malignant nodules assigned scores. The total score of the CEUS features and the scores of the above nodules were evaluated according to the latest 2017 version of the Thyroid Imaging Reporting and Data System (TI-RADS). The diagnostic performance of the two were compared based on the receiver operating characteristic curves generated for benign and malignant thyroid nodules. Results: The degree, enhancement patterns, boundary, shape, and homogeneity of enhancement in thyroid small solid nodules were significantly different (p＜0.05). No significant differences were seen between benign and malignant thyroid nodules regarding completeness of enhancement and size of enhanced lesions (p＞0.05). The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the TI-RADS classification TR5 in diagnosis of malignant nodules were 90.10%, 55.95%, 74.59%, 72.22%, and 82.46%, respectively (area under the curve [AUC]=0.738; 95% confidence interval[CI], 0.663–0.813). The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the total score of CEUS qualitative analysis indicators were 86.13%, 89.29%, 87.57%, 90.63%, and 84.27% respectively (AUC = 0.916; 95% CI, 0.871–0.961). Conclusion: CEUS qualitative analysis is superior to TI-RADS in evaluating the diagnostic performance of small, solid thyroid nodules. Qualitative analysis of CEUS has a significantly higher specificity for diagnosis of malignant thyroid nodules than TI-RADS. Advances in knowledge: The 2017 version of TI-RADS has recently suggested the malignant stratification of thyroid nodules by ultrasound. In this paper we applied this system and CEUS to evaluate 185 nodules and compare the results with pathological findings to access the diagnostic performance.

scholarly journals The Value of Contrast-Enhanced Ultrasound versus Doppler Ultrasound in Grading Renal Artery Stenosis

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Yanhua Cui ◽  
Quanbin Zhang ◽  
Jiping Yan ◽  
Ji Wu
Keyword(s):  
Positive Predictive Value ◽  
Renal Artery ◽  
Renal Artery Stenosis ◽  
Negative Predictive Value ◽  
Doppler Ultrasound ◽  
Predictive Value ◽  
Artery Stenosis ◽  
Contrast Enhanced Ultrasound ◽  
Contrast Enhanced ◽  
Sensitivity Specificity

Objective. This study is aimed at exploring the accuracy of contrast-enhanced ultrasound (CEUS) in grading renal artery stenosis. Methods. 122 renal arteries with suspected renal artery stenosis were selected. DSA, DUS, and CEUS were performed for all patients with suspected renal artery stenosis in the research. DSA was selected as the gold standard. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of CEUS or Doppler ultrasound (DUS) in the diagnosis of renal artery stenosis were analyzed. The consistency between CEUS and digital subtraction angiography (DSA) was compared. The accuracy of DUS or CEUS in grading renal artery stenosis was assessed by the area under the receiver operating characteristic (ROC) curves and compared between groups. Results. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of CEUS in the diagnosis of renal artery stenosis were 88.9%, 87.8%, 88.5%, 93.5%, and 80.0%, respectively. There was no significant difference in grading renal artery stenosis between CEUS and DSA (X2=0.643, P=0.424). 77 of the 122 renal arteries were diagnosed with the stenosis rate more than 30% by CEUS. Compared with the results of DSA, the kappa value of CEUS was 0.749 (P<0.05). Conclusion. CEUS is accurate in grading renal artery stenosis, and it may represent the method of choice in diagnosing renal artery stenosis.

scholarly journals AIBx, artificial intelligence model to risk stratify thyroid nodules

2021 ◽  
Author(s):  
Johnson Thomas ◽  
Tracy Haertling
Keyword(s):  
Artificial Intelligence ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Thyroid Nodules ◽  
Classification Systems ◽  
Image Similarity ◽  
Ultrasound Images ◽  
Similarity Model ◽  
Sensitivity Specificity

AbstractBackgroundCurrent classification systems for thyroid nodules are very subjective. Artificial intelligence (AI) algorithms have been used to decrease subjectivity in medical image interpretation. 1 out of 2 women over the age of 50 may have a thyroid nodule and at present the only way to exclude malignancy is through invasive procedures. Hence, there exists a need for noninvasive objective classification of thyroid nodules. Some cancers have benign appearance on ultrasonogram. Hence, we decided to create an image similarity algorithm rather than image classification algorithm.MethodsUltrasound images of thyroid nodules from patients who underwent either biopsy or thyroid surgery from February of 2012 through February of 2017 in our institution were used to create AI models. Nodules were excluded if there was no definitive diagnosis of benignity or malignancy. 482 nodules met the inclusion criteria and all available images from these nodules were used to create the AI models. Later, these AI models were used to test 103 thyroid nodules which underwent biopsy or surgery from March of 2017 through July of 2018.ResultsNegative predictive value of the image similarity model was 93.2%. Sensitivity, specificity, positive predictive value and accuracy of the model was 87.8%, 78.5%, 65.9% and 81.5% respectively.ConclusionWhen compared to published results of ACR TIRADS and ATA classification system, our image similarity model had comparable negative predictive value with better sensitivity specificity and positive predictive value. By using image similarity AI models, we can eliminate subjectivity and decrease the number of unnecessary biopsies. Using image similarity AI model, we were able to create an explainable AI model which increases physician’s confidence in the predictions.

Comparative Analysis of Diagnostic Value for Shear Wave Elastography and Real-Time Elastographic Imaging for Thyroid Nodules

2019 ◽  
Vol 9 (2) ◽  
pp. 334-338
Author(s):  
Qing Yang ◽  
Wenhong Zhou ◽  
Jiyu Li ◽  
Guojun Wu ◽  
Feng Ding ◽  
...  
Keyword(s):  
Differential Diagnosis ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Shear Wave ◽  
Predictive Value ◽  
Thyroid Nodules ◽  
Shear Wave Elastography ◽  
Roc Curves ◽  
Diagnostic Value ◽  
Sensitivity Specificity

Objective: To compare the diagnostic value of shear wave elastography (SWE) and real-time elastography (RTE) in the diagnosis of benign and malignant thyroid nodules. Methods: A total of 34 patients who ever received thyroidectomy in our hospital from January 2016 to January 2018 were identified. Meanwhile, all the patients received SWE and RTE before surgery, and all the diagnoses were confirmed by pathological examinations. With respect to SWE technique, the Subject Operating Characteristics (ROC) curves were drawn, in order to obtain the optimal threshold and then make differential diagnoses of benign and malignant thyroid nodules. In terms of RTE, the Rago 5 scoring method was utilized to make differential diagnoses of benign and malignant thyroid nodules. Besides, the pathological examinations after surgery could be considered as the golden standard. At last, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of SWE and RTE were calculated, respectively. Results: A total of 51 thyroid nodules were identified, and 41 nodules were benign, 10 nodules were malignant. On the basis of ROC curves, with respect to SWE, the best threshold for differential diagnosis of benign and malignant thyroid nodules is 38.3 kPa. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of SWE were 72.7% (8/11), 85% (34/40), 82.4% (42/51), 68.4% (13/19), and 87.5% (35/40), respectively. And the diagnostic indicators of RTE were 81.8% (9/11), 87.5% (35/40), 84.3% (43/51), 73.7% (14/19), and 90.0% (36/40). The sensitivity of quasi-static elastography in differential diagnosis of benign and malignant thyroid nodules with diameter ≤1 cm was 87.5% (7/8), and the sensitivity of SWE was 50.0% (5/10). In addition, the accuracy of SWE in differential diagnosis of benign and malignant thyroid nodules with diameter ≥3 cm was 100% (6/6), and the accuracy of RTE for this kind of thyroid nodules was 66.7% (4/6). Conclusion: Both SWE and RTE technology have good application value in differential diagnosis of benign and malignant thyroid nodules. But, SWE is preferable when making diagnosis of benign and malignant thyroid nodules with diameter ≥3 cm, and RTE was superior in detecting benign and malignant thyroid nodules with diameter ≤1 cm.

scholarly journals Unenhanced breast MRI: could it replace dynamic breast MRI in detecting and characterizing breast lesions?

2020 ◽  
Vol 51 (1) ◽  
Author(s):  
Reham Khalil ◽  
Noha Mohamed Osman ◽  
Nivine Chalabi ◽  
Enas Abdel Ghany
Keyword(s):  
Positive Predictive Value ◽  
Diagnostic Accuracy ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Breast Mri ◽  
Breast Lesions ◽  
Dce Mri ◽  
Contrast Enhanced ◽  
Mri Protocol ◽  
Sensitivity Specificity

Abstract Background We aimed to evaluate the unenhanced MRI of the breast (UE-MRI) as an effective substitute for dynamic contrast-enhanced breast MRI (DCE-MRI) in both detecting and characterizing breast lesions. We enrolled in our retrospective study 125 females (232 breasts, as 18 patients had unilateral mastectomy) with breast mass at MRI of variable pathologies. Routine DCE-MRI protocol of the breast was conducted. We compared the conventional unenhanced images including STIR, T2, and DWIs to the DCE-MRI by two blinded radiologists, to detect and characterize breast lesions, and then we compared their results with the final reference diagnoses supplied by the histopathology or serial negative follow-ups. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for UE-MRI and DCE-MRI were calculated. UE-MRI results of each observer were also compared with DCE- MRI. Results The calculated UE-MRI sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for the first observer were 95%, 80%, 83%, 94%, and 89% respectively, and for the second observer, they were 94%, 79%, 81%, 93%, and 86%. On the other hand, those for the DCE-MRI by the first observer were 98%, 82%, 84%, 98%, and 90% and were 97%, 81%, 84%, 97%, and 89% by the second observer. The intraobserver agreement between the UE-MRI and DCE-MRI results of each observer was 94% and 95%, while the interobserver agreement for each section was 97.4% for UE-MRI and 98.3% for DCE-MRI. Conclusion UE-MRI of the breast can be a reliable and effective substitute for breast DCE-MRI. It can be used with comparable accuracy to DCE-MRI whenever contrast administration is not feasible or contraindicated.

scholarly journals The Stroke Assessment of Fall Risk (SAFR): predictive validity in inpatient stroke rehabilitation

2014 ◽  
Vol 28 (12) ◽  
pp. 1218-1224 ◽  
Author(s):  
Terry P Breisinger ◽  
Elizabeth R Skidmore ◽  
Christian Niyonkuru ◽  
Lauren Terhorst ◽  
Grace B Campbell
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Fall Risk ◽  
Stroke Rehabilitation ◽  
Assessment Tool ◽  
Area Under The Curve ◽  
University Hospital ◽  
Sensitivity Specificity ◽  
Stroke Assessment

Objective: To evaluate relative accuracy of a newly developed Stroke Assessment of Fall Risk (SAFR) for classifying fallers and non-fallers, compared with a health system fall risk screening tool, the Fall Harm Risk Screen. Design and setting: Prospective quality improvement study conducted at an inpatient stroke rehabilitation unit at a large urban university hospital. Participants: Patients admitted for inpatient stroke rehabilitation ( N = 419) with imaging or clinical evidence of ischemic or hemorrhagic stroke, between 1 August 2009 and 31 July 2010. Interventions: Not applicable. Main outcome measure(s): Sensitivity, specificity, and area under the curve for Receiver Operating Characteristic Curves of both scales’ classifications, based on fall risk score completed upon admission to inpatient stroke rehabilitation. Results: A total of 68 (16%) participants fell at least once. The SAFR was significantly more accurate than the Fall Harm Risk Screen ( p < 0.001), with area under the curve of 0.73, positive predictive value of 0.29, and negative predictive value of 0.94. For the Fall Harm Risk Screen, area under the curve was 0.56, positive predictive value was 0.19, and negative predictive value was 0.86. Sensitivity and specificity of the SAFR (0.78 and 0.63, respectively) was higher than the Fall Harm Risk Screen (0.57 and 0.48, respectively). Conclusions: An evidence-derived, population-specific fall risk assessment may more accurately predict fallers than a general fall risk screen for stroke rehabilitation patients. While the SAFR improves upon the accuracy of a general assessment tool, additional refinement may be warranted.

Contrast-enhanced Ultrasound for Diagnosis of Renal Cystic Mass

2021 ◽  
Vol 17 ◽  
Author(s):  
Qingqing Xia ◽  
Xinchun Yuan ◽  
Meifeng Huang ◽  
Xiling Zhou ◽  
Zhiyu Zhou
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Cyst Wall ◽  
Predictive Value ◽  
Renal Cysts ◽  
Cystic Mass ◽  
Imaging Method ◽  
Contrast Enhanced Ultrasound ◽  
Contrast Enhanced ◽  
Cystic Masses

Background: Cystic Renal Cell Carcinoma (CRCC) is often challenging to differentiate from complex cysts with sonographic manifestations of renal carcinoma. Contrast-Enhanced Ultrasound (CEUS) is a new technology, and its clinical utility in the diagnosis of renal cystic mass has not been established. Objective: To analyze the characteristics of CEUS of renal cystic masses and to explore the clinical significance and value of CEUS in the diagnosis of CRCC. Methods: This study was a retrospective study. A total of 32 cystic masses from January 2018 to December 2019 were selected. The images of conventional ultrasound (US) and CEUS were confirmed via surgical pathology. The routine US was used to observe the location, shape, size, boundary, cyst wall, internal echo, and blood supply of each cystic mass. CEUS observed contrast enhancement of the cyst wall, cystic septa, and solid nodules of cystic masses. Results: There were 26 cases of CRCC, 5 cases of renal cysts, and 1 case of renal tuberculosis. The enhancement pattern, degree of enhancement, and pseudocapsular sign by CEUS in benign and malignant masses had statistically significant differences (P<.05). In the diagnosis of CRCC, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 92.3%, 83.3%, 90.6%, 96.0%, and 71.4% for CEUS; 57.6%, 66.7%, 59.3%, 88.2%, and 26.7% for conventional US, respectively. CEUS had a higher sensitivity and accuracy than the conventional US (P<.05). However, the diagnostic specificity, positive predictive value, and negative predictive value of the two methods were not significantly different (P>.05). Conclusion: CEUS is more accurate in the diagnosis of renal cystic masses, and it can be used as an effective imaging method.

scholarly journals The Value of Contrast-Enhanced Ultrasound (CEUS) in Differentiating Testicular Masses: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 11 (19) ◽  
pp. 8990
Author(s):  
Antonio Tufano ◽  
Rocco Simone Flammia ◽  
Luca Antonelli ◽  
Rocco Minelli ◽  
Giorgio Franco ◽  
...  
Keyword(s):  
Systematic Review ◽  
Predictive Value ◽  
Diagnostic Performance ◽  
Meta Analysis ◽  
Contrast Enhanced Ultrasound ◽  
Summary Receiver Operating Characteristic ◽  
Diagnostic Modality ◽  
Contrast Enhanced ◽  
Meta Analyses ◽  
Sensitivity Specificity

Ultrasound (US) still represents the mainstay of scrotal imaging. However, contrast-enhanced ultrasound (CEUS) is a relatively novel, but increasingly utilized diagnostic modality. In consequence, we performed a systematic review (SR) and pooled meta-analysis to investigate the diagnostic performance of CEUS in the evaluation of testicular masses (TM). A SR up to June 2021 was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The diagnostic performance of CEUS was evaluated basing on two different endpoints: neoplastic vs. non-neoplastic and malignant vs. benign TM. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) from eligible studies were pooled and summary receiver operating characteristic (SROC) curves were constructed for each endpoint. Overall, six qualified studies were deemed suitable for this meta-analysis. Diagnostic performance of CEUS showed an accuracy of 0.96 in detecting neoplastic masses (sensitivity of 0.89, PPV of 0.85, specificity of 0.62, and NPV of 0.69) and an accuracy of 0.96 in detecting malignant masses (sensitivity of 0.86, PPV of 0.73, specificity of 0.87, and NPV of 0.91). Taken together, CEUS may represent a promising minimally invasive diagnostic tool for characterization of TM, since it allows clinicians to identify neoplastic lesions and exclude malignant tumor.

scholarly journals Foundational Statistical Principles in Medical Research: Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value

Medicina ◽  
2021 ◽  
Vol 57 (5) ◽  
pp. 503
Author(s):  
Thomas F. Monaghan ◽  
Syed N. Rahman ◽  
Christina W. Agudelo ◽  
Alan J. Wein ◽  
Jason M. Lazar ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Medical Literature ◽  
Disease Prevalence ◽  
Positive Test Result ◽  
Predictive Values ◽  
Sensitivity Specificity ◽  
Test Result ◽  
Test Probability

Sensitivity, which denotes the proportion of subjects correctly given a positive assignment out of all subjects who are actually positive for the outcome, indicates how well a test can classify subjects who truly have the outcome of interest. Specificity, which denotes the proportion of subjects correctly given a negative assignment out of all subjects who are actually negative for the outcome, indicates how well a test can classify subjects who truly do not have the outcome of interest. Positive predictive value reflects the proportion of subjects with a positive test result who truly have the outcome of interest. Negative predictive value reflects the proportion of subjects with a negative test result who truly do not have the outcome of interest. Sensitivity and specificity are inversely related, wherein one increases as the other decreases, but are generally considered stable for a given test, whereas positive and negative predictive values do inherently vary with pre-test probability (e.g., changes in population disease prevalence). This article will further detail the concepts of sensitivity, specificity, and predictive values using a recent real-world example from the medical literature.

Diagnostic accuracy of monofilament test to detect diabetic neuropathy

2021 ◽  
Vol 10 (1) ◽  
pp. 20-25
Author(s):  
Sujan Shrestha ◽  
Mamen Prasad Gorhaly ◽  
Manil Ratna Bajracharya
Keyword(s):  
Peripheral Neuropathy ◽  
Positive Predictive Value ◽  
Diagnostic Accuracy ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Diabetic Peripheral Neuropathy ◽  
Perception Threshold ◽  
Sensitivity Specificity ◽  
Vibration Perception ◽  
Monofilament Test

Background Diabetic peripheral neuropathy (DPN) is a significant independent risk factor for diabetic foot, and an effective screening instrument is required to diagnose DPN early to prevent future ulceration and amputation. This study aims to determine the diagnostic accuracy of monofilament test to detect diabetic peripheral neuropathy. Methods This cross-sectional study was conducted in National Academy of Medical Sciences, Bir hospital, Mahabouddha, Kathmandu from February 2016 to January 2017. A total of 96 diabetic patients attending inpatient and outpatient Department were selected. Diabetic peripheral neuropathy was assessed by measurement of loss of protective sensation (LOPS) by monofilament test and compared with vibration perception threshold by standard biothesiometer. The sensitivity, specificity, positive predictive value and negative predictive value of monofilament test were calculated. Results The prevalence of diabetic peripheral neuropathy was 26%. The sensitivity, specificity, positive predictive value and negative predictive value of monofilament test were found to be 92.0%, 95.8%, 88.5% and 97.1% respectively. There was strong association between LOPS by monofilament and vibration perception threshold by biothesiometer. Conclusion This study showed a strong diagnostic accuracy of monofilament test to detect DPN when compared with biothesiometer. As monofilament test is a cheap, easily available, and portable, it can be used in the periphery where biothesiometer is not available.  

DIAGNOSTIC ACCURACY OF GRAY SCALE ULTRASONOGRAPHY VERSUS COLOR DOPPLER IN SUSPECTED CASES OF ACUTE APPENDICITIS

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Tahir Iqbal ◽  
Muhammad Usman Shahid ◽  
Ishfaq Ahmad Shad ◽  
Shahzad Karim Bhatti ◽  
Syed Amir Gilani ◽  
...  
Keyword(s):  
Acute Appendicitis ◽  
Positive Predictive Value ◽  
Diagnostic Accuracy ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Color Doppler ◽  
Diagnostic Tools ◽  
Gray Scale ◽  
Versus Color ◽  
Sensitivity Specificity

ABSTRACT: BACKGROUND: A common surgical emergency is acute appendicitis. Various diagnostic tools are available to diagnosis acute appendicitis. Radiological investigations play an important role in making accurate and early diagnosis and thus preventing morbidity associated with the disease. OBJECTIVE: To determine the diagnostic accuracy of gray scale ultrasonography versus color Doppler in suspected cases of acute appendicitis. MATERIALS AND METHODS: The study was carried in the department of Radiology of Mayo Hospital, Lahore. A total of 75 patients were enrolled of age 18-40 years, both genders who were suspected cases of acute appendicitis. All patients underwent baseline investigations along with gray scale ultrasonography and color Doppler. All patients were subjected to surgery to confirm the diagnosis and findings were subjected to statistical analysis. RESULTS: The mean age of the patients was 23.25 ±10.55 and mean transverse diameter of appendix was 8.37 ±3.39. There were 62.7% males and 37.3%females. Findings of gray scale ultrasonography and color Doppler were then correlated with surgical findings to calculate the diagnostic accuracy of these modalities. The results revealed that gray scale ultrasonography sensitivity, specificity, positive predictive value, negative predictive value and accuracy was 92.7%, 94.32%, 95%, 91.4% and 93.3% respectively, whereas color Doppler had sensitivity, specificity, positive predictive value, negative predictive value and accuracy of 97.7%, 93.9%, 95.3%, 97% and 96% respectively. Diagnostic accuracy of both modalities together was 98.6%. CONCLUSION: Color Doppler has better diagnostic accuracy than gray scale ultrasonography for diagnosis of acute appendicitis and the combination of both modalities yields diagnostic accuracy that is similar to gold standard.

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