Corrigendum: Improving the diagnostic performance of inexperienced readers for thyroid nodules through digital self-learning and artificial intelligence assistance.

[This corrects the article DOI: 10.3389/fendo.2024.1372397.].

The utility of ultrafast MRI and conventional DCE-MRI for predicting histologic aggressiveness in patients with breast cancer.

BACKGROUND: Prediction of histologic prognostic markers is important for determining management strategy and predicting prognosis. PURPOSE: To identify important features of ultrafast and conventional dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) that can predict histopathologic prognostic markers in patients with breast cancer. MATERIAL AND METHODS: Preoperative MRI scans of 158 consecutive women (mean age = 54.0 years; age range = 29-86 years) with 163 breast cancers between February 2021 and August 2022 were retrospectively reviewed. Inter-observer agreements for ultrafast MRI parameters were analyzed by two radiologists. The qualitative and quantitative MRI parameters were correlated with histopathologic prognostic markers including molecular subtypes and histologic invasiveness. RESULTS: Inter-observer agreements for ultrafast MRI parameters were excellent (intraclass correlation coefficients of area under the kinetic curve [AUC], maximum slope [MS], maximum enhancement [ME], and slope = 0.987, 0.844, 0.822, and 0.760, respectively). Triple-negative breast cancers (TNBC) were significantly associated with rim enhancement (odds ratio [OR] = 9.4, P = 0.003) and peritumoral edema (OR = 17.9, P = 0.002), compared to luminal cancers. Invasive cancers were associated with lesion type-mass, increased delayed washout, angiovolume, ME, slope, MS, and AUC, compared to in situ cancers. In regression analysis, the combination of MS (>46.2%/s) (OR = 5.7, P = 0.046) and delayed washout (>17.5%) (OR = 17.6, P = 0.01), and that of AUC (>27,410.3) (OR = 9.6, P = 0.04), delayed washout (>17.5%) (OR = 8.9, P = 0.009), and lesion-type mass (OR = 4.6, P = 0.04) were predictive of histologic invasiveness. CONCLUSION: Conventional DCE-MRI with ultrafast imaging can provide useful information for predicting histologic underestimation and aggressive molecular subtype. MS and AUC on ultrafast MRI can be potential imaging markers for predicting histologic upgrade from DCIS to invasive cancer with high reliability.

Improving the diagnostic performance of inexperienced readers for thyroid nodules through digital self-learning and artificial intelligence assistance.

Background: Data-driven digital learning could improve the diagnostic performance of novice students for thyroid nodules. Objective: To evaluate the efficacy of digital self-learning and artificial intelligence-based computer-assisted diagnosis (AI-CAD) for inexperienced readers to diagnose thyroid nodules. Methods: Between February and August 2023, a total of 26 readers (less than 1 year of experience in thyroid US from various departments) from 6 hospitals participated in this study. Readers completed an online learning session comprising 3,000 thyroid nodules annotated as benign or malignant independently. They were asked to assess a test set consisting of 120 thyroid nodules with known surgical pathology before and after a learning session. Then, they referred to AI-CAD and made their final decisions on the thyroid nodules. Diagnostic performances before and after self-training and with AI-CAD assistance were evaluated and compared between radiology residents and readers from different specialties. Results: AUC (area under the receiver operating characteristic curve) improved after the self-learning session, and it improved further after radiologists referred to AI-CAD (0.679 vs 0.713 vs 0.758, p<0.05). Although the 18 radiology residents showed improved AUC (0.7 to 0.743, p=0.016) and accuracy (69.9% to 74.2%, p=0.013) after self-learning, the readers from other departments did not. With AI-CAD assistance, sensitivity (radiology 70.3% to 74.9%, others 67.9% to 82.3%, all p<0.05) and accuracy (radiology 74.2% to 77.1%, others 64.4% to 72.8%, all p <0.05) improved in all readers. Conclusion: While AI-CAD assistance helps improve the diagnostic performance of all inexperienced readers for thyroid nodules, self-learning was only effective for radiology residents with more background knowledge of ultrasonography. Clinical Impact: Online self-learning, along with AI-CAD assistance, can effectively enhance the diagnostic performance of radiology residents in thyroid cancer.

Comparison of Abbreviated MRI with Mammography and Ultrasound in Women with a Personal History of Breast Cancer.

RATIONALE AND OBJECTIVES: To compare abbreviated MRI with mammography and US for screening in women with a personal history of breast cancer. In addition, the first and subsequent rounds of abbreviated MRI were compared. MATERIALS AND METHODS: The Institutional Review Board approved this retrospective study. Nine hundred and thirty-nine abbreviated MRI scans of 710 women with a personal history of breast cancer were included (mean age, 54.1±9.4 years). The diagnostic performances of abbreviated MRI, mammography, and US for the detection of the second breast cancer were compared. When more than one round of abbreviated MRI was performed, we compared the scans of the first and subsequent rounds. RESULTS: There were 15 (2.1%) cases of second breast cancer. Thirty-nine of the 939 abbreviated MRI scans were diagnosed as positive; of them, 11 were diagnosed as breast cancer, with a PPV2 of 28.2% (US, 19.0%; mammography, 28.6%). The AUC, sensitivity, and cancer detection rate (per 1000) were the highest for abbreviated MRI (0.829, 68.8% and 11.7) (US: 0.616, 25.0%, and 4.3; mammography: 0.560, 12.5%, and 2.1, respectively). Two hundred women underwent multiple rounds of abbreviated MRI. AUC, PPV2, and the cancer detection rates were higher during the subsequent rounds (0.987, 45.5, and 21.8) than during the first round (0.605, 11.1, and 5). CONCLUSION: Abbreviated MRI for women with a personal history of breast cancer was more sensitive for the diagnosis of second breast cancer than US or mammography. In addition, subsequent rounds of MRI showed better performance than the first round.

Diagnostic value of mammography for accompanying non-mass enhancement on preoperative breast MRI.

BACKGROUND: Successful surgical treatment for localized breast cancer can depend on accurate diagnosis for accompanying non-mass enhancement (NME) on preoperative breast magnetic resonance imaging (MRI). PURPOSE: To evaluate the diagnostic value of mammography for accompanying NME adjacent to index cancer on preoperative breast MRI. MATERIAL AND METHODS: Among 569 consecutive patients who underwent preoperative breast MRI from January 2016 to August 2018 for ultrasound-guided biopsy-proven breast cancer, 471 patients who underwent initial mammography and subsequent surgery were finally included. Two radiologists retrospectively reviewed preoperative MRI findings of the 471 patients and detected accompanying NME adjacent to index cancer. MRI, mammography, and histopathology findings of the accompanying NME were evaluated using Pearson's chi-square test, Mann-Whitney U test, and logistic regression analysis. The area under the receiver operating characteristic curve (AUC) of MRI and combined MRI and mammography was calculated in differentiating benign from malignant accompanying NME. The reference standard was surgical pathologic findings. RESULTS: MRI revealed 93 accompanying NME lesions in 92 (19.5%) of the 471 patients, showing 55 (59.1%) malignant and 38 (40.9%) benign lesions. On multivariate analysis, malignant NME lesions were more associated with mammography-positive findings (P = 0.000), clumped or clustered ring internal enhancement (P = 0.015), and extensive intraductal component presence of index tumor (P = 0.007) compared with benign lesions. The AUC increased after correlation with mammography showing 0.649 (95% confidence interval [CI] 0.533-0.765) for MRI and 0.833 (95% CI 0.747-0.919) for combined MRI and mammography. CONCLUSION: Mammography is valuable in predicting malignancy for accompanying NME on preoperative breast MRI.

The usefulness of ultrafast MRI evaluation for predicting histologic upgrade of ductal carcinoma in situ.

PURPOSE: The purpose of this study was to investigate the usefulness of ultrafast MRI with conventional dynamic contrast-enhanced (DCE)-MRI for predicting histologic upgrade of ductal carcinoma in situ (DCIS) to invasive cancer. METHODS: This retrospective study enrolled 53 biopsy-proven DCIS lesions in 53 patients and divided into two groups based on postoperative histopathologic diagnoses: non-upgrade and upgrade to invasive cancer groups. Imaging features of conventional DCE-MRI and ultrafast MRI, and histopathologic features were reviewed and compared between the two groups. Interobserver agreements for MRI features were analyzed by two radiologists. The radiologic and histopathologic parameters for predicting histologic upgrade of DCIS were identified using multiple linear regression. RESULTS: Seventeen lesions (32.1 %) were histologically upgraded to invasive cancer after surgery. The interobserver agreement for ultrafast MRI parameters was excellent, and maximum slope (MS) and maximum enhancement (ME) showed the highest reliability (intraclass correlation coefficients, 0.907 and 0.897, respectively). The upgrade group showed significantly larger lesion size on MRI (median 40 mm [25th to 75th percentiles 16.0-83.0] vs. 18.5 mm [10.0-29.8], p < 0.001), higher MS (12.1 %/s [8.2-13.9] vs. 8.7 %/s [6.4-11.1], p = 0.004), and higher ME (236.5 % [153.7-253.7] vs. 175.4 % [140.1-207.7], p = 0.027) than non-upgrade group. Lesion size (≥ 20 mm), MS (> 11.5 %), and ME (> 229.1 %) were significant predictors for histologic upgrade, which could predict 10 cases of histologic upgrade (10/17, 58.8 %) without a false-positive case. CONCLUSION: Preoperative ultrafast MRI with conventional DCE-MRI could be useful in management decisions for DCIS patients.

Accuracy of tumor size measurement on shear wave elastography (SWE): Correlation with histopathologic factors of invasive breast cancer.

The aim of this study is to investigate the accuracy of tumor size assessment by shear wave elastography (SWE) in invasive breast cancer and also evaluated histopathologic factors influencing the accuracy.A total of 102 lesions of 102 women with breast cancers of which the size was 3 cm or smaller were included and retrospectively analyzed. Tumor size on B-mode ultrasound (US) and SWE were recorded and compared with the pathologic tumor size. If tumor size measurements compared to pathological size were within ±3 mm, they were considered as accurate. The relationship between the accuracy and histopathologic characteristics were evaluated.The mean pathologic tumor size was 16.60 ±â€Š6.12 mm. Tumor sizes on SWE were significantly different from pathologic sizes (18.00 ±â€Š6.71 mm, P < 0.001). The accuracy of SWE (69.6%) was lower than that by B-mode US (74.5%). There was more size overestimation than underestimation (23.5% vs 6.9%) using SWE. Conversely, there was more size underestimation than overestimation (18.6% vs 6.9%) using B-mode US. The accuracy of SWE was associated with ER positivity (P = .004), PR positivity (P = .02), molecular subtype (P = .02), and histologic grade (P = .03). In the multivariate analysis, ER positivity (P = .002) and molecular subtype (P = .027) significantly influenced the accuracy of tumor size measurement by SWE.In conclusion, the accuracy of the tumor size measured with SWE was lower than that measured with B-mode US and SWE tends to overestimate the size. ER positivity and molecular subtype are significantly associated with the accuracy of SWE in tumor size assessment.

The additional utility of ultrafast MRI on conventional DCE-MRI in evaluating preoperative MRI of breast cancer patients.

PURPOSE: To investigate whether the additional use of ultrafast MRI can improve the diagnostic performance of conventional dynamic contrast-enhanced MRI (DCE-MRI) in evaluating MRI-detected lesions in breast cancer patients. METHODS: This retrospective study enrolled 101 consecutive breast cancer patients with 202 breast lesions (62 benign and 140 malignant) who underwent preoperative DCE-MRI with ultrafast imaging (9 image sets with 6.5-second temporal resolution). Two reviewers assessed the BI-RADS categories of breast lesions using conventional DCE-MRI and assessed the following parameters using the ultrafast MRI: initial enhancement phase, maximum relative enhancement, slope, and maximum slope (slopemax) on the kinetic curve. Interobserver agreement was analyzed between the two reviewers. The ultrafast MRI parameters were compared between benign and malignant tumors, and cut-off values were determined. For 97 additional MRI-detected lesions, the BI-RADS category was re-assessed using cut-off values, and the diagnostic performance was compared between the conventional DCE-MRI and the combined conventional and ultrafast DCE-MRI. RESULTS: All ultrafast MRI parameters differed significantly between malignant and benign tumors (p < 0.001). Initial enhancement phase by reviewer and slopemax were the top two parameters showing significant differences between benign and malignant tumors with high reliability. With the use of cut-off values for initial enhancement phase (≤phase 2) and slopemax (>9.8%/sec), the specificity of conventional DCE-MRI was significantly increased (29.4% vs 64.7%, p < 0.001) without significant loss of sensitivity (100% vs 88.2%, p = 0.157) in evaluating masses. CONCLUSIONS: The additional use of ultrafast MRI can improve the specificity of conventional DCE-MRI when evaluating MRI-detected masses in breast cancer patients.

MRI diagnostic features for predicting nipple-areolar-complex involvement in breast cancer.

PURPOSE: To evaluate magnetic resonance imaging (MRI) features including tumor-nipple enhancement for predicting nipple-areolar-complex (NAC) involvement in breast cancer. METHODS: A total of 249 breast cancer cases with available preoperative MRI data were studied. On MRI, tumor-nipple enhancement was evaluated 2 min (early) and 6 min (delayed) after contrast injection. Asymmetric nipple enhancement, mass size, tumor-nipple distance, presence of nipple discharge, and enhancement type (mass or non-mass enhancement) were evaluated. RESULTS: Of the 249 breast cancers, 24 (9.6%) showed NAC involvement. Early tumor-nipple enhancement was found in 37 (14.9%) cancers and delayed tumor-nipple enhancement in 12 (4.8%) cancers. On comparing early and delayed enhancement, 43.2% (16/37) of early tumor-nipple enhancements showed NAC involvement while 25.0% (3/12) of delayed tumor-nipple enhancements showed NAC involvement (P = 0.323). On multivariate analysis, tumor-nipple enhancement (P = 0.004) and tumor-nipple distance with 2 cm cut-off (P = 0.044) were significant. The area under the receiver-operating-characteristic curve (AUC) of early tumor-nipple enhancement was significantly higher (0.787) than that of delayed tumor-nipple enhancement (0.542, P = 0.001). The AUC was the highest when any kind of tumor-nipple enhancement was combined with a tumor-nipple distance of 1 cm (0.878). CONCLUSIONS: Tumor-nipple enhancement and tumor-nipple distance on MRI could predict NAC involvement in breast cancer. When enhancement was evaluated on both early and delayed phase images with a combined tumor-nipple distance of ≤1 cm, the prediction of NAC involvement showed the best performance.

Can Ultrasonographic Vascular and Elastographic Features of Invasive Ductal Breast Carcinoma Predict Histologic Aggressiveness?

RATIONALE AND OBJECTIVES: To investigate if preoperative ultrasonographic vascular and shear-wave elastographic examinations can predict histologic aggressiveness. MATERIALS AND METHODS: Preoperative ultrasonographic vascular features and shear-wave elasticities were retrospectively evaluated for 147 invasive ductal carcinomas. Vascular feature was assessed using four-tier vascularity score. Mean and maximum elasticities (Emean and Emax), and the lesion-to-fat ratio (Eratio) were documented. Histologic parameters were reviewed for tumor size, multiplicity, axillary lymph node status, lymphovascular invasion, histologic grade, estrogen receptor, progesterone receptor, human epidermal growth factor receptor2 (HER2), Ki-67, p53, and histologic subtype. Vascularity score and elasticities were correlated with histologic parameters and histologic parameters were compared between the group with low vascularity score and elasticities and the group with high vascularity score and elasticities using ANOVA, chi-squared test, and regression analysis. RESULTS: Vascularity score was independently associated with tumor size (p = 0.010) and HER2 (p = 0.007). Emean and Emax were associated with tumor size, histologic grade, and lymphovascular invasion, and Eratio was associated with tumor size, histologic grade, estrogen receptor, progesterone receptor, Ki-67, and histologic subtype (p < 0.05). Emean and Emax were independently associated with tumor size (p < 0.001). The group with high vascularity score and Eratio showed large tumor size (p < 0.001) and HER2 positivity (p = 0.039) in comparison to the group with low vascularity score and Eratio. CONCLUSION: Ultrasonographic vascular features were associated with tumor size and HER2. SWE elasticities were associated with tumor size, histologic grade, hormonal receptor, and histologic subtype. Therefore, preoperative vascular and elastographic examinations could predict histologic aggressiveness of invasive ductal breast carcinoma.