Review and management of breast lesions detected with breast tomosynthesis but not visible on mammography and ultrasonography

Background Breast tomosynthesis is more sensitive than mammography and can detect lesions that are not always visible with conventional methods such as digital mammography (MG) and ultrasonography (US). No standardized approach is available for the management of lesions that are detectable with tomosynthesis but are not visible on MG or US. Purpose To review suspicious breast lesions detected with tomosynthesis but not visible on two-dimensional (2D) MG or US and to determine the management options for these lesions. Material and Methods Ethical committee approval was obtained. The radiological records, biopsy or surgery results, and follow-up findings of 107 patients who had a tomosynthesis-positive but MG- or US-negative breast lesion between 2011 and 2016 were retrospectively evaluated. Results Of 107 lesions visible only with tomosynthesis, 74% were architectural distortions and 26% were asymmetrical opacities. All patients underwent magnetic resonance imaging (MRI) for further evaluation. Among the 48 (45%) MRI-negative lesions, none had a suspicious alteration during the follow-up period. Among the MRI-positive lesions, 28% of the 50 architectural distortions and 11% of the nine asymmetrical opacities were malignant. Conclusion Given the inherent high false-positive rate of breast tomosynthesis, breast MRI prior to biopsy may reduce the number of unnecessary biopsies for suspicious breast lesions that are tomosynthesis-positive only.

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DYNAMIC MRI FOR TUMOR ENHANCEMENT: AN EXPERIMENTAL BREAST CANCER MODEL

Biomedical Engineering Applications Basis and Communications ◽

10.4015/s1016237213500117 ◽

2013 ◽

Vol 25 (01) ◽

pp. 1350011 ◽

Cited By ~ 2

Author(s):

Ting-Kai Leung ◽

Pai-Jung Huang ◽

Chi-Ming Lee ◽

Chih-Hsiung Wu ◽

Yi-Fan Chen ◽

...

Keyword(s):

False Positive Rate ◽

Maximum Intensity Projection ◽

Breast Mri ◽

Dynamic Mri ◽

Future Research ◽

Post Processing ◽

Contrast Enhanced ◽

Novel Drugs ◽

Positive Rate ◽

Magnetic Resonance Imaging Mri

Dynamic contrast-enhanced magnetic resonance imaging (MRI) with post-processing is routinely used for the analysis of tumors. However, although breast MRI has gained broad clinical recognition, the relationship between imaging findings and tumor pathogenesis has yet to be fully elucidated. We grafted tumors on rats, to examine dynamic MRI images of the tumors, using post-processing subtraction with 3D maximum intensity projection (sMIP). We established a preliminary platform for analysis to compare hemodynamic-based images with histopathological findings and to further biomolecular research. This platform could facilitate future research on the mechanisms of breast tumor enhancement using MRI, improvements to MRI analysis and reduction of the false positive rate, and the development of novel drugs and contrast media.

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Improving diagnosis of acute appendicitis with atypical findings by Tc-99m HMPAO leukocyte scan

Nuklearmedizin ◽

10.1055/s-0038-1623994 ◽

2002 ◽

Vol 41 (01) ◽

pp. 37-41 ◽

Cited By ~ 3

Author(s):

S. Shung-Shung ◽

S. Yu-Chien ◽

Y. Mei-Due ◽

W. Hwei-Chung ◽

A. Kao

Keyword(s):

Acute Appendicitis ◽

False Positive ◽

False Positive Rate ◽

Accurate Method ◽

Clinical Findings ◽

Pathological Findings ◽

Lower Quadrant ◽

Predictive Values ◽

Positive Rate

Summary Aim: Even with careful observation, the overall false-positive rate of laparotomy remains 10-15% when acute appendicitis was suspected. Therefore, the clinical efficacy of Tc-99m HMPAO labeled leukocyte (TC-WBC) scan for the diagnosis of acute appendicitis in patients presenting with atypical clinical findings is assessed. Patients and Methods: Eighty patients presenting with acute abdominal pain and possible acute appendicitis but atypical findings were included in this study. After intravenous injection of TC-WBC, serial anterior abdominal/pelvic images at 30, 60, 120 and 240 min with 800k counts were obtained with a gamma camera. Any abnormal localization of radioactivity in the right lower quadrant of the abdomen, equal to or greater than bone marrow activity, was considered as a positive scan. Results: 36 out of 49 patients showing positive TC-WBC scans received appendectomy. They all proved to have positive pathological findings. Five positive TC-WBC were not related to acute appendicitis, because of other pathological lesions. Eight patients were not operated and clinical follow-up after one month revealed no acute abdominal condition. Three of 31 patients with negative TC-WBC scans received appendectomy. They also presented positive pathological findings. The remaining 28 patients did not receive operations and revealed no evidence of appendicitis after at least one month of follow-up. The overall sensitivity, specificity, accuracy, positive and negative predictive values for TC-WBC scan to diagnose acute appendicitis were 92, 78, 86, 82, and 90%, respectively. Conclusion: TC-WBC scan provides a rapid and highly accurate method for the diagnosis of acute appendicitis in patients with equivocal clinical examination. It proved useful in reducing the false-positive rate of laparotomy and shortens the time necessary for clinical observation.

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Role of Invasive Urodynamic Studies in Establishing Cauda Equina Syndrome and Postoperative Recovery

Global Spine Journal ◽

10.1177/2192568220979640 ◽

2020 ◽

pp. 219256822097964

Author(s):

Abhinandan Reddy Mallepally ◽

Bibhudendu Mohapatra ◽

Kalidutta Das

Keyword(s):

Clinical Symptoms ◽

False Positive Rate ◽

Cauda Equina ◽

Postoperative Recovery ◽

Normal Bladder ◽

Acontractile Detrusor ◽

Positive Rate ◽

Acute Radiculopathy ◽

Operative Recovery

Study design: Retrospective with prospective follow-up. Objective: Confirming the diagnosis of CES based purely on symptoms and signs is unreliable and usually associated with high false positive rate. A missed diagnosis can permanently disable the patient. Present study aims to determine the relationship between clinical symptoms/ signs (bladder dysfunction) with UDS, subsequently aid in surgical decision making and assessing post-operative recovery. Methods: A prospective follow-up of patients with disc herniation and bladder symptoms from January 2018 to July 2020 was done. All patients underwent UDS and grouped into acontractile, hypocontractile and normal bladder. Data regarding PAS, VAC, GTP, timing to surgery and onset of radiculopathy and recovery with correlation to UDS was done preoperatively and post operatively. Results: 107 patients were studied (M-63/F-44). Patients with PAS present still had acontractile (61%) or hypocontractile (39%) detrusor and with VAC present, 57% had acontractile and 43% hypocontractile detrusors. 10 patients with both PAS and VAC present had acontractile detrusor. 82% patients with acute radiculopathy (<2 days) improved when operated <24 hrs while only 47% showed improvement with chronic radiculopathy. The detrusor function recovered in 66.1% when operated <12 hours, 40% in <12-24 hours of presentation. Conclusion: Adjuvant information from UDS in combination with clinicoradiological findings help in accurate diagnosis even in patients with no objective motor and sensory deficits. Quantitative findings on UDS are consistent with postoperative recovery of patient’s urination power, representing improvement and can be used as a prognostic factor.

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Comparative Study of Digital Breast Tomosynthesis (DBT) with and without Ultrasound versus Breast Magnetic Resonance Imaging (MRI) in Detecting Breast Lesion

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph19020759 ◽

2022 ◽

Vol 19 (2) ◽

pp. 759

Author(s):

Janice Hui Ling Goh ◽

Toh Leong Tan ◽

Suraya Aziz ◽

Iqbal Hussain Rizuana

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Diagnostic Performance ◽

Breast Lesion ◽

Breast Magnetic Resonance Imaging ◽

Digital Breast Tomosynthesis ◽

Resonance Imaging ◽

Breast Tomosynthesis ◽

Breast Magnetic Resonance ◽

Magnetic Resonance Imaging Mri

Digital breast tomosynthesis (DBT) is a fairly recent breast imaging technique invented to overcome the challenges of overlapping breast tissue. Ultrasonography (USG) was used as a complementary tool to DBT for the purpose of this study. Nonetheless, breast magnetic resonance imaging (MRI) remains the most sensitive tool to detect breast lesion. The purpose of this study was to evaluate diagnostic performance of DBT, with and without USG, versus breast MRI in correlation to histopathological examination (HPE). This was a retrospective study in a university hospital over a duration of 24 months. Findings were acquired from a formal report and were correlated with HPE. The sensitivity of DBT with or without USG was lower than MRI. However, the accuracy, specificity and PPV were raised with the aid of USG to equivalent or better than MRI. These three modalities showed statistically significant in correlation with HPE (p < 0.005, chi-squared). Generally, DBT alone has lower sensitivity as compared to MRI. However, it is reassuring that DBT + USG could significantly improve diagnostic performance to that comparable to MRI. In conclusion, results of this study are vital to centers which do not have MRI, as complementary ultrasound can accentuate diagnostic performance of DBT.

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dtectDx Breast: A serum biomarker test for breast cancer detection used in conjunction with traditional mammography screening.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.26_suppl.18 ◽

2013 ◽

Vol 31 (26_suppl) ◽

pp. 18-18

Author(s):

Meredith C. Henderson ◽

Keri Sweeten ◽

Sherri Borman ◽

Christa Corn ◽

Lindsey Gordon ◽

...

Keyword(s):

Breast Cancer ◽

False Positive Rate ◽

Standard Of Care ◽

Patient Characteristics ◽

Protein Biomarkers ◽

Time Period ◽

Positive Rate ◽

Previous Clinical Study

18 Background: Provista Diagnostics has developed a test that analyzes serum concentrations of 5 protein biomarkers in order to detect breast cancer. The dtectDx Breast test utilizes a proprietary algorithm that has been described previously (Weber et al. 2010). In this study, it was noted that the algorithm performs best in women under age 50. The aim of this study was to evaluate the performance characteristics of dtectDx Breast in women under age 50 in a commercial setting and compare the results with data from the previous clinical study. Methods: The dtectDx Breast test measures the concentrations of IL-8, IL-12, VEGF, CEA, and HGF via ELISA. These data combined with select patient characteristics and Provista’s proprietary algorithm result in a test value that is characterized as normal or elevated. dtectDx Breast test reports issued for women under age 50 were reviewed from a 3-year time period and prescribing physicians were interviewed regarding follow-up care and outcome measures (largely imaging studies, if warranted). Results: Of the 908 patients, 8 samples were rejected based on serum quality. Of the remaining 900 patients, 121 were reported as elevated (12.7%). In 4 cases, these elevated results were confirmed cases of breast cancer. Of these, 2 patients initially showed no screening evidence of cancer, but upon further evaluation (after receipt of dtectDx Breast results) were diagnosed with breast cancer. dtectDx correctly identified DCIS 66% of the time (n=2). Conclusions: These results describe the use of dtectDx Breast in a clinical setting and confirm that the assay behaves similarly to previously published results (Weber et al 2010). While the false-positive rate is higher than predicted (12.7% vs 6.8%), the assay correctly identified 4 of 4 invasive cancers and 2 of 3 DCIS cases. Since two of the invasive cancer cases were originally not detected via standard screening procedures, the assay has demonstrated important clinical utility when used in conjunction with mammography/standard of care. Here we show that, in the commercial patient population, when combined with standard of care, dtectDx Breast improves the detection of breast cancer in women under 50.

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Prospective study of magnetic resonance imaging (MRI) and multiparameter gene expression assay in ductal carcinoma in situ (DCIS): A trial of the ECOG-ACRIN Cancer Research Group (E4112).

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.534 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. 534-534 ◽

Cited By ~ 1

Author(s):

Seema Ahsan Khan ◽

Constantine Gatsonis ◽

Brad Snyder ◽

Constance D Lehman ◽

Joseph A. Sparano ◽

...

Keyword(s):

Ductal Carcinoma ◽

Breast Mri ◽

Invasive Disease ◽

Primary Objective ◽

Surgical Margins ◽

Magnetic Resonance Imaging Mri ◽

Combined Impact ◽

Clinical Trial Information

534 Background: Prior retrospective studies have evaluated breast MRI in DCIS, and prospective-retrospective biomarker studies have shown that the DCIS Score is prognostic for recurrence after BCS alone. E4112 is a prospective cohort study designed to assess the combined impact of breast MRI and DCIS Score on surgical and RT management. Methods: Women diagnosed with screen-detected DCIS on core biopsy, if BCS eligible, underwent breast MRI. Those remaining so following MRI and related biopsies, with no invasive disease, underwent BCS. If final surgical margins were ≥2 mm, the DCIS lesion was submitted for DCIS Score assay. Women with low DCIS Score (≤39, LS) were advised that RT could be avoided; RT was recommended to those with high/intermediate (H/I) scores. The primary objective was to estimate the fraction converting to mastectomy (Mx) following MRI. Secondary objectives included estimation of re-operation rates after first BCS, and DCIS Score distribution.A sample size of 333 evaluable women would allow estimation of Mx rate of 12% with 95% confidence interval 9-16%. Results: 334 enrolled women had completed surgery; the first surgical procedure was Mx in 54 (16.2%) and BCS in 280 (83.8%), of whom 62 (22.1%) required at least one re-excision, and 11 (3.9%) converted to Mx. DCIS Scores were obtained on 171 patients who completed BCS, of whom 82 were LS and 89 were H/I. Demographics were similar between the two groups, other features will be reported. Only 7/82 (8.5%) of the LS group received RT, whereas 82/89 (92.1%) of the H/I group received RT. Of the 98 BCS patients who did not qualify for DCIS Score-based therapy, 23 had invasive disease, 34 had final surgical margins < 2 mm, and 13 had both. There was insufficient tissue for DCIS Score in 11, and 17 did not complete follow-up. Conclusions: In this study, among DCIS patients who were BCS-eligible following MRI, total mastectomy rate was 19.5%; re-excision rate was 22.1% for women who had BCS. Approximately half had low DCIS Scores, and RT recommendations based on the DCIS Score were acceptable to most women. Clinical trial information: E4112.

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Pregnancy data enable identification of relevant biomarkers and a partial prognosis of autism at birth

10.1101/2020.07.08.192989 ◽

2020 ◽

Author(s):

Hugues Caly ◽

Hamed Rabiei ◽

Perrine Coste-Mazeau ◽

Sebastien Hantz ◽

Sophie Alain ◽

...

Keyword(s):

Behavioral Interventions ◽

Statistical Tests ◽

False Positive Rate ◽

Familial Risk ◽

Autism Spectrum ◽

Gradient Boosting ◽

Decision Tree Classification ◽

Positive Rate ◽

History Of

AbstractAttempts to extract early biomarkers and expedite detection of Autism Spectrum Disorder (ASD) have been centered on postnatal measures of babies at familial risk. Here, we suggest that it might be possible to do these tasks already at birth relying on ultrasound and biological measurements routinely collected from pregnant mothers and fetuses during gestation and birth. We performed a gradient boosting decision tree classification analysis in parallel with statistical tests on a population of babies with typical development or later diagnosed with ASD. By focusing on minimization of the false positive rate, the cross-validated specificity of the classifier reached to 96% with a sensitivity of 41% and a positive predictive value of 77%. Extracted biomarkers included sex, maternal familial history of auto-immune diseases, maternal immunization to CMV, IgG CMV level, timing of fetal rotation on head, femoral length in the 3rd trimester, white cells in the 3rd trimester, fetal heart rate during labour, newborn feeding and newborn’s temperature difference between birth and one day after. Statistical models revealed that 38% of babies later diagnosed with ASD had significantly larger fetal cephalic perimeter than age matched neurotypical babies, suggesting an in-utero origin of the bigger brains of toddlers with ASD. Results pave the way to use pregnancy follow-up measurements to provide an early prognosis of ASD and implement pre-symptomatic behavioral interventions to attenuate efficiently ASD developmental sequels.

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Deep Learning Model Improves Radiologists’ Performance in Detection and Classification of Breast Lesions

10.21203/rs.3.rs-746374/v1 ◽

2021 ◽

Author(s):

Ying-Shi Sun ◽

Yu-Hong Qu ◽

Dong Wang ◽

Yi Li ◽

Lin Ye ◽

...

Keyword(s):

Artificial Intelligence ◽

Deep Learning ◽

Roc Curve ◽

False Positive ◽

Large Scale ◽

False Positive Rate ◽

Training Dataset ◽

Validation Dataset ◽

Breast Lesions ◽

Positive Rate

Abstract Background: Computer-aided diagnosis using deep learning algorithms has been initially applied in the field of mammography, but there is no large-scale clinical application.Methods: This study proposed to develop and verify an artificial intelligence model based on mammography. Firstly, retrospectively collected mammograms from six centers were randomized to a training dataset and a validation dataset for establishing the model. Secondly, the model was tested by comparing 12 radiologists’ performance with and without it. Finally, prospectively multicenter mammograms were diagnosed by radiologists with the model. The detection and diagnostic capabilities were evaluated using the free-response receiver operating characteristic (FROC) curve and ROC curve.Results: The sensitivity of model for detecting lesion after matching was 0.908 for false positive rate of 0.25 in unilateral images. The area under ROC curve (AUC) to distinguish the benign from malignant lesions was 0.855 (95% CI: 0.830, 0.880). The performance of 12 radiologists with the model was higher than that of radiologists alone (AUC: 0.852 vs. 0.808, P = 0.005). The mean reading time of with the model was shorter than that of reading alone (80.18 s vs. 62.28 s, P = 0.03). In prospective application, the sensitivity of detection reached 0.887 at false positive rate of 0.25; the AUC of radiologists with the model was 0.983 (95% CI: 0.978, 0.988), with sensitivity, specificity, PPV, and NPV of 94.36%, 98.07%, 87.76%, and 99.09%, respectively.Conclusions: The artificial intelligence model exhibits high accuracy for detecting and diagnosing breast lesions, improves diagnostic accuracy and saves time.Trial registration: NCT, NCT03708978. Registered 17 April 2018, https://register.clinicaltrials.gov/prs/app/ NCT03708978

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OS08.6.A Glioblastoma treatment response machine learning monitoring biomarkers: a systematic review and meta-analysis

Neuro-Oncology ◽

10.1093/neuonc/noab180.036 ◽

2021 ◽

Vol 23 (Supplement_2) ◽

pp. ii11-ii12

Author(s):

T C Booth ◽

A Chelliah ◽

A Roman ◽

A Al Busaidi ◽

H Shuaib ◽

...

Keyword(s):

Machine Learning ◽

Treatment Response ◽

Meta Analysis ◽

False Positive Rate ◽

Risk Of Bias ◽

Response Monitoring ◽

Reference Standard ◽

Positive Rate ◽

Test Sets

Abstract BACKGROUND The aim of the systematic review was to assess recently published studies on diagnostic test accuracy of glioblastoma treatment response monitoring biomarkers in adults, developed through machine learning (ML). MATERIAL AND METHODS PRISMA methodology was followed. Articles published 09/2018-01/2021 (since previous reviews) were searched for using MEDLINE, EMBASE, and the Cochrane Register by two reviewers independently. Included study participants were adult patients with high grade glioma who had undergone standard treatment (maximal resection, radiotherapy with concomitant and adjuvant temozolomide) and subsequently underwent follow-up imaging to determine treatment response status (specifically, distinguishing progression/recurrence from progression/recurrence mimics - the target condition). Risk of bias and applicability was assessed with QUADAS 2. A third reviewer arbitrated any discrepancy. Contingency tables were created for hold-out test sets and recall, specificity, precision, F1-score, balanced accuracy calculated. A meta-analysis was performed using a bivariate model for recall, false positive rate and area-under the receiver operator characteristic curve (AUC). RESULTS Eighteen studies were included with 1335 patients in training sets and 384 in test sets. To determine whether there was progression or a mimic, the reference standard combination of follow-up imaging and histopathology at re-operation was applied in 67% (13/18) of studies. The small numbers of patient included in studies, the high risk of bias and concerns of applicability in the study designs (particularly in relation to the reference standard and patient selection due to confounding), and the low level of evidence, suggest that limited conclusions can be drawn from the data. Ten studies (10/18, 56%) had internal or external hold-out test set data that could be included in a meta-analysis of monitoring biomarker studies. The pooled sensitivity was 0.77 (0.65–0.86). The pooled false positive rate (1-specificity) was 0.35 (0.25–0.47). The summary point estimate for the AUC was 0.77. CONCLUSION There is likely good diagnostic performance of machine learning models that use MRI features to distinguish between progression and mimics. The diagnostic performance of ML using implicit features did not appear to be superior to ML using explicit features. There are a range of ML-based solutions poised to become treatment response monitoring biomarkers for glioblastoma. To achieve this, the development and validation of ML models require large, well-annotated datasets where the potential for confounding in the study design has been carefully considered. Therefore, multidisciplinary efforts and multicentre collaborations are necessary.

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