Does patient age affect the PPV3 of ACR BI-RADS Ultrasound categories 4 and 5 in the diagnostic setting?

Hu, Yue; Yang, Yaping; Gu, Ran; Shen, Shi‐Li; Liu, Fengtao; Wang, Hongli; Mei, Jie; Jiang, Xin; Liu, Qiang; Su, Fengxi

doi:10.1007/s00330-017-5203-3

Cited by 19 publications

(28 citation statements)

References 26 publications

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“…It can be highly specific in the identification of metastases (12). Although our data indicated that the rate of lymph node metastasis gradually increased as the BI-RADS US category steadily increased, 12.3% (9/73) of patients with a category 4A malignant lesion also presented a positive axillary status (8). In this study, the US lymph node status had the most important contribution in predicting malignancy in the nomogram, followed by suspicious calcifications on MG. Other MG features did not show distinct predictive value in this study.…”

Section: Discussionmentioning

confidence: 47%

“…Biopsy has been the recommended management approach for all 3 subcategories because of the suspicion of malignancy. However, the malignancy rate of category 4A lesions is rather low (2-10%), and the proportion of category 4A lesions was 44.5% amongst category 4-5 lesions (8). The average reported rate of BI-RADS category 4A lesions on the diagnostic US in our center is only 6.7% and is much lower for patients under 35 years old (2.7%) (8).…”

Section: Introductionmentioning

confidence: 56%

“…However, the malignancy rate of category 4A lesions is rather low (2-10%), and the proportion of category 4A lesions was 44.5% amongst category 4-5 lesions (8). The average reported rate of BI-RADS category 4A lesions on the diagnostic US in our center is only 6.7% and is much lower for patients under 35 years old (2.7%) (8). Since most biopsies of category 4A lesions are benign, the exclusive use of biopsy can cause unnecessary health care costs and patient anxiety.…”

Section: Introductionmentioning

confidence: 88%

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A new nomogram for predicting the malignant diagnosis of Breast Imaging Reporting and Data System (BI-RADS) ultrasonography category 4A lesions in women with dense breast tissue in the diagnostic setting

Yang¹,

Hu²,

Shen³

et al. 2021

Quant Imaging Med Surg

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Background: Biopsy has been recommended for Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions. However, the malignancy rate of category 4A lesions is very low (2-10%). Therefore, most biopsies of category 4A lesions are benign, and the results will generally cause additional health care costs and patient anxiety. Methods: A prediction model was developed based on an analysis of 418 BI-RADS ultrasonography (US) category 4A patients at Sun Yat-sen Memorial Hospital. Univariate and multivariate logistic regression analyses were applied to identify significant variables for inclusion in the final nomogram. The predictive accuracy and discriminative ability were evaluated using the concordance index (C-index) and calibration curves. An independent cohort of 97 patients from the Second Affiliated Hospital of Guangzhou Medical University was used for external validation. Results: The independent risk factors from the multivariate analysis for the training cohort were family history of breast cancer (OR =4.588, P=0.004), US features [margin (OR =2.916, P=0.019), shape (irregular vs. oval, OR =2.474, P=0.044; round vs. oval, OR =1.935, P=0.276), parallel orientation vs. not parallel (OR =2.204, P=0.040)], low suspicious lymph nodes (OR =7.664, P=0.019), and suspicious calcifications on mammography (MG) (OR =6.736, P=0.001). The C-index was good in the training [0.813, 95% confidence interval (95% CI), 0.733 to 0.893] and validation cohorts (0.765, 95% CI, 0.584 to 0.946). The calibration curves showed optimal agreement between the nomogram prediction and actual observations for the probability of malignancy. Also, the cutoff score was set to 100 for discriminating high and low risk. The model performed well in discerning different risk groups.Conclusions: We developed a well-discriminated and calibrated nomogram to predict the malignancy of BI-RADS US category 4A lesions in dense breast tissue, which may help clinicians identify patients at lower or higher risk.

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Section: Discussionmentioning

confidence: 47%

Section: Introductionmentioning

confidence: 56%

Section: Introductionmentioning

confidence: 88%

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A new nomogram for predicting the malignant diagnosis of Breast Imaging Reporting and Data System (BI-RADS) ultrasonography category 4A lesions in women with dense breast tissue in the diagnostic setting

Yang¹,

Hu²,

Shen³

et al. 2021

Quant Imaging Med Surg

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“…US-guided biopsy was performed using a core instrument with a 14-gauge needle or a vacuum-assisted biopsy machine with an 8-gauge needle. More than three tissue samples were obtained and placed in formalin solution and then processed for histopathology by standard procedures 13 . Patients with indefinite histological results were recommended for surgery.…”

Section: Methodsmentioning

confidence: 99%

Predicting Breast Cancer in Breast Imaging Reporting and Data System (BI-RADS) Ultrasound Category 4 or 5 Lesions: A Nomogram Combining Radiomics and BI-RADS

Luo

Huang

et al. 2019

Sci Rep

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Radiomics reflects the texture and morphological features of tumours by quantitatively analysing the grey values of medical images. We aim to develop a nomogram incorporating radiomics and the Breast Imaging Reporting and Data System (BI-RADS) for predicting breast cancer in BI-RADS ultrasound (US) category 4 or 5 lesions. From January 2017 to August 2018, a total of 315 pathologically proven breast lesions were included. Patients from the study population were divided into a training group (n = 211) and a validation group (n = 104) according to a cut-off date of March 1 st , 2018. Each lesion was assigned a category (4A, 4B, 4C or 5) according to the second edition of the American College of Radiology (ACR) BI-RADS US. A radiomics score was generated from the US image. A nomogram was developed based on the results of multivariate regression analysis from the training group. Discrimination, calibration and clinical usefulness of the nomogram for predicting breast cancer were assessed in the validation group. The radiomics score included 9 selected radiomics features. The radiomics score and BI-RADS category were independently associated with breast malignancy. The nomogram incorporating the radiomics score and BI-RADS category showed better discrimination (area under the receiver operating characteristic curve [AUC]: 0.928; 95% confidence interval [CI]: 0.876, 0.980) between malignant and benign lesions than either the radiomics score ( P = 0.029) or BI-RADS category ( P = 0.011). The nomogram demonstrated good calibration and clinical usefulness. In conclusion, the nomogram combining the radiomics score and BI-RADS category is potentially useful for predicting breast malignancy in BI-RADS US category 4 or 5 lesions.

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“…A final US score (category 0–6, including subcategory 4A–4C) was assigned by the same radiologist immediately after scanning according to the second edition of BI-RADS US 9. Our radiologists assessed the US findings without referring to MG, because US and MG are usually in different departments in China and few radiologists routinely interpret both of them 14,15…”

Section: Methodsmentioning

confidence: 99%

<p>Does the radiologist need to rescan the breast lesion to validate the final BI-RADS US assessment made on the static images in the diagnostic setting?</p>

Mei

Jiang

et al. 2019

CMAR

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Purpose: To assess whether radiologist needs to rescan the breast lesion to validate the final American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) ultrasonography (US) assessment made on the static images in the diagnostic setting. Patients and methods: Image data on 1,070 patients with 1,070 category 3–5 breast lesions with a pathological diagnosis scanned between January and June 2016 were included. Both real-time and static image assessments were acquired for each lesion. The diagnostic performance was evaluated by receiver operating characteristic (ROC) curves. The positive predictive values (PPVs) of each category in the two groups were calculated according to the ACR BI-RADS manual and compared. Kappas were determined for agreement on two assessment approaches. Results: The sensitivity, specificity, PPV, and negative predictive value for real-time US were 98.9%, 58.2%, 44.8% and 99.4%, and for static images were 98.9%, 57.1%, 44.1% and 99.3%, respectively. The performance of the two groups was not significantly different (areas under ROCs: 0.786 vs 0.780, P =0.566) if the final assessment was only dichotomized as negative (category 3) and positive (categories 4 and 5). All PPVs of each category for each assessment were within the reference range provided by the ACR in 2013 except subcategory 4B (reference range: >10% and ≤50%) of static image evaluation, which was also significantly higher than that of real-time assessment (54.8% vs 40.7%, P =0.037). The overall agreement of the two approaches was moderate ( κ =0.43–0.56 according to different detailed assessment). Conclusion: Both static image and real-time assessment had similar diagnostic performance if only the treatment recommendations were considered, that is, follow-up or biopsy. However, as for subcategory 4B lesions without obviously benign or malignant US features, real-time scanning by the interpreter is recommended to obtain a more accurate BI-RADS assessment after assessing static images.

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Does patient age affect the PPV3 of ACR BI-RADS Ultrasound categories 4 and 5 in the diagnostic setting?

Abstract: • In patients with category 4 lesions , the likelihood of malignancy is associated with age. • In patients with category 5 lesions, the association is not definite. • Closer attention should be given to older patients in applying the ACR BI-RADS US.

Cited by 19 publications

References 26 publications

A new nomogram for predicting the malignant diagnosis of Breast Imaging Reporting and Data System (BI-RADS) ultrasonography category 4A lesions in women with dense breast tissue in the diagnostic setting

A new nomogram for predicting the malignant diagnosis of Breast Imaging Reporting and Data System (BI-RADS) ultrasonography category 4A lesions in women with dense breast tissue in the diagnostic setting

Predicting Breast Cancer in Breast Imaging Reporting and Data System (BI-RADS) Ultrasound Category 4 or 5 Lesions: A Nomogram Combining Radiomics and BI-RADS

<p>Does the radiologist need to rescan the breast lesion to validate the final BI-RADS US assessment made on the static images in the diagnostic setting?</p>

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