Diagnostic accuracy of MRI textural analysis in the classification of breast tumors

Visual equine lameness assessment is often unreliable, yet the full understanding of this issue is missing. Here, we investigate visual lameness assessment using near-realistic, three-dimensional horse animations presenting with 0–60 per cent movement asymmetry. Animations were scored at an equine veterinary seminar by attendees with various expertise levels. Results showed that years of experience and exposure to a low, medium or high case load had no significant effect on correct assessment of lame (P>0.149) or sound horses (P≥0.412), with the exception of a significant effect of case load exposure on forelimb lameness assessment at 60 per cent asymmetry (P=0.014). The correct classification of sound horses as sound was significantly (P<0.001) higher for forelimb (average 72 per cent correct) than for hindlimb lameness assessment (average 28 per cent correct): participants often saw hindlimb lameness where there was none. For subtle lameness, errors often resulted from not noticing forelimb lameness and from classifying the incorrect limb as lame for hindlimb lameness. Diagnostic accuracy was at or below chance level for some metrics. Rater confidence was not associated with performance. Visual gait assessment may overall be unlikely to reliably differentiate between sound and mildly lame horses irrespective of an assessor’s background.

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Microwave Breast Imaging Using Rotational Bistatic Impulse Radar for the Detection of Breast Cancer: Protocol for a Prospective Diagnostic Study (Preprint)

10.2196/preprints.17524 ◽

2019 ◽

Author(s):

Shinsuke Sasada ◽

Norio Masumoto ◽

Hang Song ◽

Akiko Emi ◽

Takayuki Kadoya ◽

...

Keyword(s):

Breast Cancer ◽

Diagnostic Accuracy ◽

Breast Imaging ◽

Molecular Subtype ◽

Breast Tumors ◽

Cancer Surveillance ◽

Benign Tumors ◽

Diagnostic Study ◽

Imaging Device ◽

Microwave Breast Imaging

BACKGROUND Mammography is the standard examination for breast cancer screening; however, it is associated with pain and exposure to ionizing radiation. Microwave breast imaging is a less invasive method for breast cancer surveillance. A bistatic impulse radar–based breast cancer detector has recently been developed. OBJECTIVE This study aims to present a protocol for evaluating the diagnostic accuracy of the novel microwave breast imaging device. METHODS This is a prospective diagnostic study. A total of 120 participants were recruited before treatment administration and divided into 2 cohorts: 100 patients diagnosed with breast cancer and 20 participants with benign breast tumors. The detector will be directly placed on each breast, while the participant is in supine position, without a coupling medium. Confocal images will be created based on the analyzed data, and the presence of breast tumors will be assessed. The primary endpoint will be the diagnostic accuracy, sensitivity, and specificity of the detector for breast cancer and benign tumors. The secondary endpoint will be the safety and detectability of each molecular subtype of breast cancer. For an exploratory endpoint, the influence of breast density and tumor size on tumor detection will be investigated. RESULTS Recruitment began in November 2018 and was completed by March 2020. We anticipate the preliminary results to be available by summer 2021. CONCLUSIONS This study will provide insights on the diagnostic accuracy of microwave breast imaging using a rotational bistatic impulse radar. The collected data will improve the diagnostic algorithm of microwave imaging and lead to enhanced device performance. CLINICALTRIAL Japan Registry of Clinical Trials jRCTs062180005; https://jrct.niph.go.jp/en-latest-detail/jRCTs062180005 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/17524

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Classification of benign and malignant breast tumors on the basis of 36 radiographic properties

Cancer ◽

10.1002/1097-0142(197302)31:2<342::aid-cncr2820310212>3.0.co;2-i ◽

1973 ◽

Vol 31 (2) ◽

pp. 342-352 ◽

Cited By ~ 20

Author(s):

Laurens V. Ackerman ◽

Anthony N. Mucciardi ◽

Earl E. Gose

Keyword(s):

Breast Tumors ◽

Malignant Breast

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Classification of Breast Tumors in Digitized Mammograms

Digital Mammography ◽

10.1007/978-3-642-59327-7_89 ◽

2003 ◽

pp. 382-386

Author(s):

C. Varela ◽

N. Karssemeijer ◽

J. M. Muller ◽

P. G. Tahoces

Keyword(s):

Breast Tumors

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Investigation of Convolutional Neural Networks in the Tasks of Medical Images Analysis and Classification of Breast Tumors

10.1109/cisp-bmei53629.2021.9624326 ◽

2021 ◽

Author(s):

Yuriy Zaychenko ◽

Helen Zaichenko ◽

Galib Hamidov

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Medical Images ◽

Breast Tumors

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Clinical Utility of Striational Antibodies in Paraneoplastic and Myasthenia Gravis Paraneoplastic Panels

Neurology ◽

10.1212/wnl.0000000000012050 ◽

2021 ◽

pp. 10.1212/WNL.0000000000012050

Author(s):

Shahar Shelly ◽

John R Mills ◽

Divyansu Dubey ◽

Andrew McKeon ◽

Anastasia Zekeridou ◽

...

Keyword(s):

Diagnostic Accuracy ◽

Myasthenia Gravis ◽

Clinical Utility ◽

Roc Analysis ◽

Thymic Cancer ◽

Diagnostic Characteristics ◽

Data Platform ◽

Neurological Phenotype ◽

Antibody Positivity

Objective:To critically assess the clinical utility of striational antibodies (StrAbs) within paraneoplastic and myasthenia gravis serological evaluations.Methods:All Mayo Clinic patients tested for StrAbs from January 1st 2012-December 31st 2018 utilizing Mayo’s Unified Data Platform (UDP) were reviewed for neurological diagnosis and cancer.Results:38,502 unique paraneoplastic and 1,899 MG patients were tested. In paraneoplastic evaluations, the StrAbs positivity rate was higher in cancer vs without cancer (5% [321/6775] vs 4% [1154/31727]; p<0.0001; OR 1.35; CI=1.19-1.53) but ROC analysis indicated no diagnostic accuracy in cancer (AUC=0.505). No neurological phenotype was significantly associated with StrAbs in the paraneoplastic group. Positivity was more common in all MG cancers compared to paraneoplastic cancers (p<0.0001). In MG evaluations, the StrAbs positivity rate was higher in those with cancer vs without (46% [217/474] vs 26% [372/1425]; p<0.0001; OR 2.39, CI 1.9-2.96) with ROC analysis indicating poor diagnostic accuracy for thymic cancer (AUC 0.634, recommended cutoff=1:60, sensitivity=56%, specificity=71%), with worse accuracy for extrathymic cancers (AUC 0.543). In paraneoplastic or MG evaluations, the value of antibody positivity did not improve cancer predictions. Paraneoplastic evaluated patients were more likely with positive StrAbs to obtain computed tomography (CT) (p=0.0001) with 3% (12/468) cancer found.Conclusion:Despite a statistically significant association with cancer, an expansive review of performance in clinical service demonstrates that StrAbs are neither specific nor sensitive in predicting malignancy or neurological phenotypes. CT imaging is over utilized with positive StrAbs results. Removal of StrAbs from paraneoplastic or MG evaluations will improve the diagnostic characteristics of the current MG test.Classification of Evidence:This study provides Class II evidence that the presence of StrAbs do not accurately identify patients with malignancy or neurological phenotypes.

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