Differentiation of Malignancy and Idiopathic Granulomatous Mastitis Presenting as Non-mass Lesions on MRI: Radiological, Clinical, Radiomics, and Clinical-Radiomics Models.

RATIONALE AND OBJECTIVES: To investigate the effectiveness of machine learning-based clinical, radiomics, and combined models in differentiating idiopathic granulomatous mastitis (IGM) from malignancy, both presenting as non-mass enhancement (NME) lesions on magnetic resonance imaging (MRI), and to compare these models with radiological evaluation. MATERIAL AND METHODS: A total of 178 patients (69 IGM and 109 breast cancer patients) with NME on breast MRI evaluated between March 2018 and April 2022, were included in this two-center study. Age, skin changes, presence of fistula, and abscess were recorded from hospital records. Two experienced radiologists evaluated MRI images according to the breast imaging reporting and data system 2013 lexicon. Lesions were segmented independently on T2-weighted, apparent diffusion coefficient, and post-contrast-T1-weighted sequences. Data were split into training and external testing sets. Machine learning models were built using Light GBM (light gradient-boosting machine). Radiological, clinical, radiomics, and clinical-radiomics models were created and compared. Decision curve analysis was performed. Quality of reporting and that of methodology were evaluated using CLEAR and METRICS tools. RESULTS: IGM group was younger (p = 0.014). Abscesses (p < 0.001), fistulas (p < 0.001), and skin changes (p < 0.001) were significantly more common in the IGM group. No significant difference was detected in terms of lesion size (p = 0.213). In the evaluation of NME, the lowest performance belonged to the radiologists' evaluation (AUC for training, 0.740; for testing, 0.737), while the highest AUC was achieved by the model developed by combined clinical and radiomics features (AUC for training, 0.979; for testing, 0.942). CONCLUSION: Our study has shown that the machine learning-based clinical-radiomics model might have the potential to accurately discriminate IGM and malignant lesions in evaluating NME areas.

Preoperative Role of Superb Microvascular Imaging and Shear-Wave Elastography for Prediction of Axillary Lymph Node Metastasis in Patients With Breast Cancer.

ABSTRACT: This study aims to evaluate the role of shearwave elastography (SWE) and superb microvascular imaging (SMI) for preoperative prediction of axillary lymph node metastasis (ALNM) in patients with breast cancer. In a cohort of 214 women with breast cancer, B-Mode ultrasonography (US), SMIvascular-index (SMIvi), and SWE (E-mean, E-ratio) values were recorded before tru-cut biopsy. Axillary fine-needle aspiration biopsy (FNAB) and sentinel lymph node sampling results were collected. Imaging findings and histopathological data were statistically compared. Receiver operating characteristic curve analysis was used to evaluate diagnostic performance. Reverse stepwise logistical regression analysis was conducted. Although ALNM was negative in 111 cases, it was positive in 103 patients. Axillary lymph node metastasis (+) group had larger size (P < 0.001), higher vascularization (SMIvi: 8.0 ± 6.0 versus 5.0 ± 4.3, P < 0.001), and higher elasticity value (E-mean: 129 ± 31 kPa versus 117.3 ± 40 kPa, P = 0.014). Axillary lymph node metastasis was observed statistically more frequently in Her-2 positive cases (P = 0.005). There was no significant difference between other B-mode US findings (P > 0.05), SMI Adler (P = 0.878), and E-ratio (P = 0.212). The most appropriate cutoff value for the prediction of ALNM was 23.5 mm for size, 3.8 for SMIvi, and 138.5 kPa for E-mean. The most sensitive (77%) method was the SMIvi measurement, while the most specific (86%) finding was Her-2 positivity. The combined model (being Her-2 positive, >23.5 cm, and >3.8 SMIvi) increased the specificity (78%), PPV (71%), and accuracy (68%). Although the increased size is a previously studied parameter in predicting the risk of ALNM, Her-2 and data obtained by SWE, and SMI can be used to assist conventional US.

The Diagnostic Role of Shear Wave Elastography and Superb Microvascular Imaging in the Evaluation of Suspicious Microcalcifications.

OBJECTIVES: The aim of this study was to investigate the role of superb microvascular imaging (SMI) and shear wave elastography (SWE) in the prediction of malignancy and invasiveness of isolated microcalcifications (MC) that can be visualized by ultrasonography (US). MATERIAL AND METHODS: Sixty-seven women with MC, who were considered suspicious on mammography were evaluated. Only those lesions that could be visualized by US and presented as non-mass lesion were included. They were evaluated by B-mode US, SMI, and SWE before US-guided core-needle biopsy. B-mode US, SMI (vascular index (SMIvi)), and SWE (E-mean, E-ratio) findings were compared with histopathologic features. RESULTS: Pathology confirmed 45 malignant (21 invasive and 24 in situ carcinomas) and 22 benign lesions. There was a statistically significant difference between malignant and benign groups in terms of size (P = .015), distortion (P = .028), cystic component (P < .001), E-mean (P < .001), E-ratio (P < .001), and SMIvi (P = .006). For differentiation of invasiveness E-mean (P = .002), E-ratio (P = .002), and SMIvi (P = .030) were statistically significant. According to ROC analysis E-mean (cut-off point at 38 kPa) was the most sensitive (78%) and the most specific (95%) value among four numeric parameters (size, SMI, E-mean, and E-ratio) with AUC = 0.895, PPV = 97%, and NPV = 68% in detecting malignancy. In the evaluation of invasiveness, the most sensitive (71.4%) method was SMI (cut-off point at 3.4) and the most specific (72%) method was E-mean (cut-off point at 91.5 kPa). CONCLUSION: Our study shows that adding SWE and SMI to the sonographic evaluation of MC would be an advantage for US-guided biopsy. Including suspicious areas according to SMI and SWE in the sampling area can help target the invasive part of the lesion and avoid underestimation of core biopsy.

Diagnostic Performance of Superb Microvascular Imaging in Differentiating Benign and Malignant Axillary Lymph Nodes.

ABSTRACT: The aim was to evaluate the effectiveness of superb microvascular imaging (SMI) in axillary lymph nodes (LNs).Benign and malignant LNs diagnosed via histopathological examination constituted the study subgroups. In addition to grayscale findings for morphological evaluation, vascular patterns and appearance of internal vessels were analyzed by both power Doppler ultrasound (PDUS) and SMI. The number of vascular branches was counted, and a vascularity index (VI) was calculated by SMI.Fifty-two LNs with suspicious findings in terms of metastasis (33 malignant and 19 benign) were evaluated. Diagnostic accuracy according to vascular patterns was 82% for PDUS and 92% for SMI. In the presence of asymmetric cortical thickening, there was a significant difference between benign and malignant LNs in the number of vascular branches of both thin and thick cortical sides ( P < 0.01). Mean VI was significantly higher in the malignant group ( P < 0.05). In differentiating malignancy, when a cutoff VI value was set to 9%, sensitivity was 69.7%, and specificity was 63.2%.Evaluating the vascularity of axillary LNs by SMI is a useful tool in determining the potential of axillary metastasis, especially in the absence of typical sonographic findings. Superb microvascular imaging can beneficially be used to select the most suspicious LN and suspicious area of the LN to sample.

Prediction of Molecular Subtypes Using Superb Microvascular Imaging and Shear Wave Elastography in Invasive Breast Carcinomas.

RATIONALE AND OBJECTIVES: To investigate the efficacy of the advanced imaging methods, superb microvascular imaging (SMI) and shear wave elastography (SWE) in predicting molecular subtypes in invasive breast carcinomas. MATERIALS AND METHODS: A total of 210 biopsy-proven breast carcinomas in 200 patients who underwent ultrasound (US) imaging with SMI and SWE were included in this study. Quantitative analyses were performed using mean elasticity (Emean) score by SWE and vascular index (VI) by SMI. For qualitative assessment of microvascularity, first, lesions were graded according to Adler's classification in four types. Then, a new morphological model was used to classify the microvascular architecture into six patterns: type one, no signal; type two, penetrant; type three, rim-like; type four, dot-like/linear/regional; type five, wheel-like and type six, irregular signals. The correlation between these variables and molecular subtypes, nuclear grade, the Ki-67 levels and axillary status was investigated. RESULTS: The average VI and Emean values were relatively higher in non-luminal subtypes (VI, p = 0.002; Emean, p > 0.05). The two microvascularisation models were significantly able to differentiate the molecular subtypes according to the Kruskal Wallis test (p < 0.05). Rim-like, penetrant and regional patterns were primarily observed in luminal subtypes. The dominant pattern in non-luminal subtypes was wheel-like pattern. VI, Emean, Adler's classification and morphological vascularisation model were not significantly correlated with the nuclear grade, Ki-67 index or axillary status. CONCLUSION: The proposed microvascular categorization model may be more valuable in predicting molecular subtypes of breast carcinomas compared to VI and Emean and may contribute to the management of breast carcinomas as a non-invasive variable.

Is there a potential biomarker in distinguishing invasive breast carcinomas with elevated Ki-67 levels among 2D-SWE, SMI, and 18F-FDG PET-CT/MRI-derived parameters?: A single-center data.

PURPOSE: To investigate the strength of quantitative imaging and metabolic parameters in differentiating invasive breast carcinomas with elevated Ki-67 levels. MATERIALS AND METHODS: A total of 123 patients with 129 breast lesions confirmed as invasive breast carcinoma underwent shear wave elastography (SWE), superb microvascular imaging (SMI) and positron emission tomography (PET)/CT or MRI. Adler's grade (classifying the microvascularity into four types) and Vascular Index (VI) was obtained by SMI as microvascular parameters. In addition, the stiffness value (Emean ) was evaluated in kilopascal by SWE. The average of consecutive measurements was recorded as mean VI and mean Emean . PET scan parameters were obtained as SUVmax and SULpeak . Lesions were divided into two groups according to the Ki-67 expression, low as ≤ 14 and high as >14. RESULTS: Adler's grading was the most correlated imaging parameter with high Ki-67 expression (p < 0.05), while VI and Emean had poor correlation (p > 0.05). SUVmax and SULpeak indicated a significant linear correlation with Ki-67 but a moderate correlation with the high levels of Ki-67 (p < 0,001). The sensitivity of VI, Emean , SUVmax and SULpeak was 64.6%, 66.7%, 65.7%, and 66.7% when the cut-off point was set to 5.25, 102.5, 6.59, and 2.63, respectively. SUVmax had the highest AUC value of 0.740, according to the ROC curve analysis. CONCLUSIONS: Our results suggest that the quantitative parameters obtained by advanced imaging methods may be useful in predicting the high proliferation in invasive breast carcinomas. But none of them is eligible to be used as an independent biomarker in distinguishing aggressive behavior. Nevertheless, as a noninvasive method, visual assessment of microvascular morphology using SMI increases the prognostic efficiency in invasive breast carcinomas.

A Rare Cause of Breast Swelling in Lactating Women: Aquafilling® Gel Injection.

Aquafilling® gel has been used in recent years as an alternative method to breast augmentation surgery. In this case report, we aimed to discuss radiological imaging findings and complications of Aquafilling® gel injection. Case: A 34-year-old lactating female patient presented with swelling and pain in the left breast. Ultrasonography showed massive septate fluid collections with dense content in both breasts and between the pectoral muscle fibers. On mammography, both breasts appeared dense with large mass opacities. On magnetic resonance imaging, extensive fluid-signal cystic areas were observed. Peripheral enhancement around the fluid in the left breast was present in the contrast-enhanced series. We learned from her anamnesis that Aquafilling® was applied to both breasts 5 years ago. Ultrasonography-guided sampling was performed from the cystic areas in the left breast and cytological examination revealed basophilic Aquafilling® material surrounded by diffuse inflammatory infiltrates. Breast augmentation history should be questioned in suspicious cases because Aquafilling® gel injection and its complications can present with a wide variety of symptoms and may mimic various other conditions on radiological imaging, such as cancer, abscess, granulomatous mastitis, and parasite infections.

Magnetic resonance imaging findings associated with recurrence in idiopathic granulomatous mastitis.

PURPOSE: To evaluate magnetic resonance imaging (MRI) findings related to recurrence of idiopathic granulomatous mastitis (IGM). METHODS: Demographic data [age, number of births, duration of lactation period, body mass index (BMI) and presence of recurrence] of 71 patients who were diagnosed with IGM were analyzed retrospectively. Characteristics of IGM (maximum width, location, involvement of the retroareolar region, deep tissue, skin), fibroglandular density (FGD), background parenchymal enhancement (BPE), distribution and pattern of contrast enhancement, presence of prepectoral edema, abscesses, fistulae, axillary lymphadenopathies on MRI and apparent diffusion coefficient (ADC) values from the pathological area were recorded. RESULTS: The recurrence rate in patients was 59% (42/71). We found a statistically significant relationship between recurrence and BPE (p = 0.028) and mean ADC (p = 0.035) values (for the cut-off of 1.00 × 10-3 mm2/s; sensitivity = 61.9%, specificity = 69%, AUC = 0.648). However, patients' age (p = 0.346), lactation period (p = 0.470), number of births (p = 0.774), BMI (p = 0.630) maximum width of the area of enhancement (p = 0.112), involvement of the retroareolar region (p = 0.290), deep tissue (p = 0.285), skin (p = 0.230), distribution (p = 0.857) and enhancement pattern (p = 0.157), presence of prepectoral edema (p = 0.094), abscesses (p = 0.441), fistulae (p = 0.809), lymphadenopathies (p = 0.571), and FGT (p = 0.098) were not significantly associated with recurrence. CONCLUSION: Our results revealed that recurrent IGM patients showed high BPE and lower mean ADC values. We think that high BPE and low mean ADC (<1.00 × 10-3 mm2/s) on MRI at the diagnosis stage may be a sign of possible future recurrence, and it will be beneficial to follow the patients more closely and arrange the treatment algorithms accordingly.

Primary neuroendocrine carcinomas of the breast and neuroendocrine differentiated breast cancers: Relationship between histopathological and radiological features.

PURPOSE: The aim of this study wasto investigate whole-breast imaging findings (mammography, ultrasonography (US), magnetic resonance imaging (MRI),clinical, and histopathological findings of primary neuroendocrine carcinomas of the breast (NEC) and neuroendocrine differentiated breast cancers (NEBC). METHODS: Patients withadiagnosis of breast cancer with histopathological neuroendocrine features between the years 2010 and 2021 were retrospectively screened.The lesions were divided into two main groups depending on staining with neuroendocrine markers (synaptophysin and chromogranin A). Those showing focal staining were categorized as NEBC while those with diffuse staining as NEC.The mammography, US, and MRI of the lesionswere reviewed in consensus by two breast radiologists in order to assess imaging featuresretrospectively according to the Breast Imaging Reporting and Data System (BI-RADS) 5th lexicon.The findings were compared with breast cancers without neuroendocrine features (BC-WNE) which were randomly selected from the same database. RESULTS: A total of 105 lesions [NEBC (n = 44), NEC(n = 11), BC-WNE (n = 50)] were evaluated.Patients with neuroendocrine tumors were older (p < 0.001) than those with BC-WNE. Compared with BC-WNE tumors, radiological findings typical of malignancy such as irregular shape [NEBC (7/20); NEC(3/7) vs BC-WNE (35/43); p < 0.001], spiculation [NEBC (2/20); NEC(0/7) vs BC-WNE (21/43); p < 0.001], architectural distortion [(NEBC (3/24); NEC(0/9) vs BC-WNE (31/50); p < 0.001)], calcification [(NEBC (6/24), NEC(0/9) vs BC-WNE (n = 27/50); p = 0.001)] on mamography, non-parallel orientation to skin [(NEBC (n = 17/29), NEC(n = 4/9), BC-WNE (n = 35/42); p = 0.008)], acoustic shadowing [(NEBC (n = 12/29), NEC(1/9), BC-WNE (n = 29/42); p = 0.009)], axillary lymphadenopathy [(NEBC(n = 3/30), NEC(n = 1/9), BC-WNE (21/50); p < 0.001)]on US were less common features of the neuroendocrine carcinomas of breast. Aside from shape features, there was no significant difference in contrast pattern (p = 0.866), kinetic curve (p = 0.454) and diffusion restriction (p = 0.242) on MRI. CONCLUSION: Characteristic malignant imaging features, including irregular shape, spiculated margins, suspicious calcifications, and posterior acoustic shadowing, are uncommon in neuroendocrine carcinomas of breast. These carcinomas tend to show more benign imaging features when compared with BC-WNE.