Evaluation Of Breast Lesions Research Articles

231 - Diagnostic effectiveness of mammography in evaluation of breast lesions with histopathological correlation

231 - Diagnostic effectiveness of mammography in evaluation of breast lesions with histopathological correlation

Kaiser score diagnosis of breast MRI lesions: Factors associated with false-negative and false-positive results

PurposeWe sought factors associated with false-negative and false-positive results in the diagnosis of breast lesions using the Kaiser score (KS) on breast magnetic resonance imaging (MRI). MethodsWe retrospectively analyzed 1058 patients with 1058 breast lesions who underwent preoperative breast MRI with successful histopathologic results. Two radiologists assessed each lesion according to KS criteria, and clinicopathologic features and MRI findings were analyzed. Multivariate regression analysis was conducted to identify factors associated with false-negative and false-positive KS results. ResultsOf the 1058 lesions, 859 were malignant and 199 were benign. Particularly high misdiagnosis rates were observed for intraductal papilloma, inflammatory lesion, and mucinous carcinoma. For breast cancer, KS yielded 821 (95.6 %) true-positive and 38 (4.4 %) false-negative results. Multivariate analysis showed that smaller lesion size (≤1 cm) (OR, 3.698; 95 %CI, 1.430–9.567; p = 0.007), absence of ipsilateral breast hypervascularity (OR, 3.029; 95 %CI, 1.370–6.693; p = 0.006), and presence of hyperintensity on T2WI (OR, 2.405; 95 %CI, 1.121–5.162; p = 0.024) were significantly associated with false-negative breast cancer results. For benign lesions, KS yielded 141 (70.9 %) true-negative and 58 (29.1 %) false-positive results. Multivariate regression analysis revealed that non-mass enhancement lesions (OR, 4.660; 95 %CI, 2.018–10.762; p＜0.001), moderate/high background parenchymal enhancement (OR, 2.402; 95 %CI, 1.180–4.892; p = 0.016), and the presence of hyperintensity on T2WI (OR, 2.986; 95 %CI, 1.386–6.433; p = 0.005) were significantly associated with false-positive KS results. ConclusionSeveral clinicopathologic and MRI features influence the accuracy of KS diagnosis. Understanding these factors may facilitate appropriate use of KS and guide alternative diagnostic approaches, ultimately improving diagnostic accuracy in the evaluation of breast lesions.

Associated factors leading to misdiagnosis of a combined diagnostic model of different types of strain imaging and conventional ultrasound in evaluation of breast lesions: Selection strategy for using different types of strain imaging in evaluation of breast lesions

ObjectiveTo evaluate the effectiveness of a decision tree that integrates conventional ultrasound (CUS) with two different strain imaging (SI) techniques for diagnosing breast lesions, and to analyze the factors contributing to false negative (FN) and false positive (FP) in the decision tree’s outcomes. Materials and MethodsImaging and clinical data of 796 cases in the training set and 351 cases in the validation set were prospectively collected. A decision tree model that combines two types of SI and CUS was constructed, and its diagnostic performance was analyzed. Univariate analysis and multivariate analysis were applied to identify independent risk factors associated with FP and FN results of the decision tree model. ResultsSize, shape, margin, vascularity, the types of internal calcifications, EI score and VTI pattern were found to be significantly independently associated with the diagnosis of benign and malignant breast lesions. Therefore, size, shape, margin, vascularity, EI score and VTI pattern were used to construct decision tree models. The Tree (EI+VTI) model had the highest AUC. Both in the training and validation groups, the AUC of Tree (EI+VTI) was significantly higher compared with that of EI, VTI, and BI-RADS (all, P < 0.05). Orientation, posterior acoustic features and the types of internal calcifications were significantly positively associated with misdiagnosis results of Tree (EI+VTI) in evaluation of breast lesions (all P < 0.05). ConclusionThe diagnostic model based on a decision tree that integrates two distinct types of SI with CUS enhances the diagnostic accuracy of each method when used individually. This integration lowers the misdiagnosis rate, potentially assisting radiologists in more effective lesion assessments. When applying the decision tree model, attention should be paid to the orientation, posterior acoustic features, and the types of internal calcifications of the lesions.

Role of P63 in Benign and Malignant Lesions of Breast

Introduction: Breast carcinoma is leading cause of cancer death in women. Breast lesions constitute heterogeneous group of diseases with wide variety of etiologies ranging from inflammatory-benign- malignant lesions. There are several reported markers for immunohistochemical detection of myoepithelial cells. Smooth muscle specific proteins, such as smooth muscle actin, smooth muscle myosin heavy chain, calponin and h-caldesmon are used to highlight myoepithelium. p63 antibody is myoepithelial cell marker that selectively stains nuclei. It is negative in stromal, myofibroblastic and adipocytic cells.Aims and Objectives: The aim of this study was to establish role of p63 expression in distinguishing benign breast lesions, premalignant lesions and malignant tumors of breast.Materials and Methods: 30 cases were selected from core biopsy, lumpectomy and mastectomy specimens ofbreast received at department of Pathology, Chalmeda Anand Rao Institute of Medical Sciences during the period of January 2021 to December 2021 and were studied prospectively. All specimens were processed according to CAP protocol and reported . Immunohistochemistry was performed to determine p63 expression in those specimens. p63 expression was evaluated as continuous positive/discontinuous positive/negative.Ethical Approval: This study was reviewed and approved by institute ethics committee, CAIMS, Karimnagar.Results: Among total 30 cases, 18 cases (60%) were benign lesions and all were positive for p63 expression. 3 cases (9.99%) were premalignant and were least positive for p63 expression. All malignant cases 9 cases (29.99%) were negative for p63 expression.Conclusion: The Positive correlation was seen between histomorphological features and p63 scoring in all the lesions, So p63 is good Immunohistochemical marker for evaluating breast lesions.

A comparative study of breast lesions using the IAC Yokohama System for reporting breast cytopathology against histopathological biopsy

Abstract Background: Breast lumps pose a significant health concern globally, contributing to both illness and death. The International Academy of Cytology (IAC) Yokohama system has established a uniform method for reporting breast cytology, categorizing it into five groups: inadequate, benign, atypical, suspicious, and malignant. Aims and Objectives: This study primarily aimed to evaluate breast lesions using the IAC Yokohama System and compare the results with those of corresponding histopathological biopsies. Additionally, the study aimed to analyze the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of breast fine-needle aspiration cytology (FNAC) and determine the risk of malignancy associated with each category. Materials and Methods: In this study, 92 cases were analyzed and categorized according to the IAC Yokohama System. Sensitivity, specificity, PPV, NPV, diagnostic accuracy, and risk of malignancy were determined based on histopathological diagnosis, which was considered the reference standard. Results: Among the 92 breast FNACs, the risk of malignancy for the categories insufficient, benign, atypical, suspicious, and malignant were 0%, 0%, 18.75%, 100%, and 100%, respectively. The highest sensitivity (100%) was achieved when considering atypical, suspicious, and malignant cases as positive results. The specificity was highest (100%) when only malignant or both malignant and suspicious cases were considered positive results. The highest diagnostic accuracy (95.65%) was observed when including malignant and suspicious cases as positive results. Conclusion: Implementing the IAC Yokohama System for reporting breast cytopathology through structured reporting will enhance the quality, clarity, and reproducibility of reports among pathologists and clinicians, which would result in enhanced patient care and management.

Ultrasound-Based Noncontrast Microvascular Imaging for Evaluation of Breast Lesions: Imaging Techniques and Review of Diagnostic Criteria.

Vascularity plays a pivotal role in the progression of breast lesions and may be associated with their aggressiveness and likelihood of being malignant. Contrast-enhanced imaging techniques are necessary to evaluate vascularity due to the limited sensitivity of conventional color Doppler techniques, in which motion artifacts are eliminated using wall filters. However, in this process, low-flow signals from small vessels also get removed unintentionally. Advancements in technology have revolutionized the way ultrasound images are generated, resulting in tremendous improvements in Doppler imaging techniques. The new, ultrasound-based noncontrast microvascular imaging techniques overcome the limitations of conventional Doppler, and are highly sensitive for detecting microvessels and low flow. The resultant high Doppler sensitivity leads to detection of vascularity in more breast lesions. It is important for radiologists to understand the imaging principles and the clinical implications of the new techniques, to optimally utilize them and aid correct diagnosis. Angio-PLUS is one such recent advancement, which uses unfocused or plane waves and three-dimensional wall filtering to analyze tissue motion in time, space, and amplitude domains that effectively distinguish between blood flow and tissue. The information is beneficial for assessing the lesion vascularity without using contrast. This article aims to explain the Doppler imaging techniques, their clinical applications, scanning methods, and review the common Doppler-based diagnostic criteria used in the evaluation of breast lesions.

Breast Imaging Reporting and Data System evaluation of breast lesions improved with virtual touch tissue imaging average grayscale values.

Early breast cancer diagnosis is of great clinical importance for selecting treatment options, improving prognosis, and enhancing the quality of patients' survival. We investigated the value of virtual touch tissue imaging average grayscale values (VAGV) helper Breast Imaging Reporting and Data System (BI-RADS) in diagnosing breast malignancy. We retrospectively analyzed 141 breast tumors in 134 patients. All breast lesions were diagnosed pathologically by biopsy or surgical excision. All patients first underwent conventional ultrasound (US) followed by virtual touch tissue imaging (VTI). The measurement of the VAGV of the lesion was performed by Image J software. BI-RADS classification was performed for each lesion according to the US. We performed a two-by-two comparison of the diagnostic values of VAGV, BI-RADS, and BI-RADS+VAGV. VAGV was lower in malignant tumors than in benign ones (35.82 ± 13.39 versus 73.58 ± 42.69, P< 0.001). The area under the receiver operating characteristic curve (AUC) value, sensitivity, and specificity of VAGV was 0.834, 84.09%, and 69.07%, respectively. Among BI-RADS, VAGV, and BI-RADS+VAGV, BI-RADS+VAGV had the highest AUC (0.926 versus 0.882, P= 0.0066; 0.926 versus 0.834, P= 0.0012). There was perfect agreement between the two radiologists using VAGV (ICC= 0.9796) and substantial agreement using BI-RADS (Kappa= 0.725). Our study shows that VAGV can accurately diagnose breast cancer. VAGV effectively improves the diagnostic performance of BI-RADS.

27 (PB-8) Poster Spotlight - Role of contrast enhanced spectral mammography (CESM) in the evaluation of breast lesions

27 (PB-8) Poster Spotlight - Role of contrast enhanced spectral mammography (CESM) in the evaluation of breast lesions

Diffusion-Weighted MRI-Based Virtual Elastography and Shear-Wave Elastography for the Assessment of Breast Lesions.

Diffusion-weighted imaging (DWI)-based virtual MR elastography (DWI-vMRE) in the assessment of breast lesions is still in the research stage. To investigate the usefulness of elasticity values on DWI-vMRE in the evaluation of breast lesions, and the correlation with the values calculated from shear-wave elastography (SWE). Prospective. 153 patients (mean age ± standard deviation: 55 ± 12 years) with 153 pathological confirmed breast lesions (24 benign and 129 malignant lesions). 1.5-T MRI, multi-b readout segmented echo planar imaging (b-values of 0, 200, 800, and 1000 sec/mm2). For DWI-vMRE assessment, lesions were manually segmented using apparent diffusion coefficient (ADC0-1000) map, then the region of interests were copied to the map of shifted-ADC (sADC200-800, sADC 200-1500). For SWE assessment, the shear modulus of the lesions was measured by US elastic modulus (μUSE). Intraclass/interclass kappa coefficients were calculated to measure the consistency. Pearson's correlation was used to assess the relationship between sADC and μUSE. A receiver operating characteristic analysis with the area under the curve (AUC) was performed to compare the diagnostic accuracy between benign and malignant breast lesions of sADC and μUSE. A P value <0.05 was considered statistically significant. There were significant differences between benign and malignant breast lesions of μUSE (24.17 ± 10.64 vs. 37.20 ± 12.61), sADC200-800 (1.38 ± 0.31 vs. 0.97 ± 0.18 × 10-3 mm2/sec), and sADC200-1500 (1.14 ± 0.30 vs. 0.78 ± 0.13 × 10-3 mm2/sec). In all breast lesions, a moderate but significant correlation was observed between μUSE and sADC200-800/sADC200-1500 (r = -0.49/-0.44). AUC values to differentiate benign from malignant lesions were as follows: μUSE, 0.78; sADC200-800, 0.89; sADC200-1500, 0.89. Both SWE and DWI-vMRE could be used for the differentiation of benign versus malignant breast lesions. Furthermore, DWI-vMRE with the use of sADC show relatively higher AUC values than SWE. 4 TECHNICAL EFFICACY: Stage 2.

Breast Carcinoma among Patients Undergoing Breast Diagnostic Ultrasonography in a Tertiary Care Hospital in Nepal

Background Ultrasonography (US) is an important modality for investigating breast lesions, as it lacks radiation exposure, differentiates between solid tumor and fluid-filled cysts, and is particularly-useful for young females with dense breast tissue. This study aimed to determine test characteristics (sensitivity, specificity, positive and negative predictive values, and accuracy), and the prevalence of breast cancer, among patients undergoing diagnostic breast US for clinically-detected abnormalities in a tertiary care cancer hospital in Nepal, comparing US findings with histopathology and cytopathology.Data and Methods A cross-sectional study was conducted among a convenience sample of 418 female patients who underwent diagnostic breast US between April 15 and September 10, 2022. Data were entered and analyzed on SPSS 25.0. Prevalence of cancer was determined among US patients who were referred for tissue diagnosis on the basis of clinical or US findings. Sensitivity, specificity, positive and negative predictive values, and accuracy of US in detecting breast lesions in comparison to histopathology and cytopathology findings were calculated. Results The study respondents’ age ranged from 13 to 75 (±11.8) years. Among 97 patients who underwent fine needle aspiration or biopsy based on US findings, 52 (12.4% of total) were diagnosed with breast carcinoma. The sensitivity, specificity, negative predictive value, positive predictive value, and accuracy of US to detect breast cancer were 94%, 100%, 93.7%, 100%, and 96.9%, respectively. Conclusion Among women with breast complaints or physical examination findings, diagnostic US revealed a high prevalence in the population investigated and demonstrated very good sensitivity, specificity, and accuracy to detect breast cancer. This study confirms the important role of ultrasound in the evaluation of breast lesions, particularly in underdeveloped countries.

Diagnostic Utility of an Adjusted DWI Lexicon Using Multiple b-values to Evaluate Breast Lesions in Combination with BI-RADS.

We aimed to investigate the diagnostic feasibility of an adjusted diffusion-weighted imaging (DWI) lexicon using multiple b values to assess breast lesions according to DWI-based breast imaging reporting and data system (BI-RADS). This Institutional Review Board (IRB)-approved prospective study included 127 patients with suspected breast cancer. Breast MRI was performed using a 3T scanner. Breast DW images were acquired using five b-values of 0, 200, 800, 1000, and 1500 s/mm2 (5b-value DWI) on 3T MRI. Two readers independently assessed lesion characteristics and normal breast tissue using DWI alone (5b-value DWI and 2b-value DWI with b = 0 and 800 s/mm2) according to DWI-based BI-RADS and in combination with the standard dynamic contrast-enhanced images (combined MRI). Interobserver and intermethod agreements were assessed using kappa statistics. The specificity and sensitivity of lesion classification were evaluated. Ninety-five breast lesions (39 malignant and 56 benign) were evaluated. Interobserver agreement for lesion assessment on 5b-value DWI was very good (k ≥ 0.82) for DWI-based BI-RADS categories, lesion type, and mass characteristics; good (k = 0.75) in breast composition; and moderate (k ≥ 0.44) in background parenchymal signal (BPS) and non-mass distribution. Intermethod agreement between assessments performed using either 5b-value DWI or combined MRI was good-to-moderate (k = 0.52-0.67) for lesion type; moderate (k = 0.49-0.59) for DWI-based BI-RADS category and mass characteristics; and fair (k = 0.25-0.40) for mass shape, BPS, and breast composition. The sensitivity and positive predictive values (PPVs) for 5b-value DWI were 79.5%, 84.6% and 60.8%, 61.1% for each reader, respectively; 74.4%, 74.4% and 63.0%, 61.7% for 2b-value DWI; and 97.4%, 97.4% and 73.1%, 76.0% for combined MRI. The specificity and negative predictive values (NPVs) were 64.3%, 62.5% and 81.8%, 85.4% for 5b-value DWI; 69.6%, 67.9% and 79.6%, 79.2% for 2b-value DWI; and 75.0%, 78.6% and 97.7%, 97.8% for combined MRI. Good observer agreement was observed in the 5b-value DWI. The 5b-value DWI based on multiple b-values might have the potential to complement the 2b-value DWI; however, their diagnostic performance tended to be inferior to that of combined MRI for the characterization of breast tumors.

Evaluations of the diagnostic performance of ZOOMit diffusion-weighted imaging and conventional diffusion-weighted imaging for breast lesions.

Diffusion-weighted imaging (DWI) is valuable in the screening, diagnosis, and grading of breast lesions. However, conventional DWI (C-DWI) is prone to chemical shift and distortion. ZOOMit DWI (Z-DWI), as an advanced magnetic resonance imaging (MRI) technique, applies two spatially selective parallel excitation pulses to focus sampling in the hope of obtaining more valuable information. This study aimed to evaluate and compare the image quality and feasibility of Z-DWI with those of C-DWI in breast lesions. The study included 51 patients with breast lesions who underwent breast MRI from May 2021 to February 2022. All patients received Z-DWI and C-DWI sequences, with b values selected as 50 and 800 s/mm2 (Z-DWIb50, Z-DWIb800, C-DWIb50, and C-DWIb800). Apparent diffusion coefficient (ADC) values based on Z-DWI and C-DWI were calculated. For qualitative analysis, four image quality parameters were selected and assessed on a 4-point Likert scale (1 = poor and 4 = excellent). For quantitative analysis, ADC, relative ADC (rADC), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and tumor-to-parenchymal contrast (TPC) values were selected for comparison. Z-DWI had higher scores compared to C-DWI in terms of lesion conspicuity, anatomical details, distortion and artifacts, and overall image quality (P<0.05). Meanwhile, the agreement between the two readers was reasonably good [intraclass correlation coefficient (ICC) range, 0.360-0.881]. The SNR of Z-DWIb800 was better than that of C-DWIb800 (P<0.001). The Z-DWI ADC and rADC values of breast lesions were statistically significantly lower than those of C-DWI (mean ADC: P<0.001; rADC; P=0.005). Z-DWI sequences were shown to have superior image quality. The ADC map of Z-DWI is more conducive to the imaging evaluation of breast lesions.

Evaluation of breast cancer malignancy, prognostic factors and molecular subtypes using a continuous-time random-walk MR diffusion model

PurposeTo assess the continuous-time random-walk (CTRW) model’s diagnostic value in breast lesions and to explore the associations between the CTRW parameters and breast cancer pathologic factors. MethodThis retrospective study included 85 patients (70 malignant and 18 benign lesions) who underwent 3.0T MRI examinations. Diffusion-weighted images (DWI) were acquired with 16b-values to fit the CTRW model. Three parameters (Dm, α, and β) derived from CTRW and apparent diffusion coefficient (ADC) from DWI were compared among the benign/malignant lesions, molecular prognostic factors, and molecular subtypes by Mann-Whitney U test. Spearman correlation was used to evaluate the associations between the parameters and prognostic factors. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC) based on the diffusion parameters. ResultsAll parameters, ADC, Dm, α, and β were significantly lower in the malignant than benign lesions (P < 0.05). The combination of all the CTRW parameters (Dm, α, and β) provided the highest AUC (0.833) and the best sensitivity (94.3%) in differentiating malignant status. And the positive status of estrogen receptor (ER) and progesterone receptor (PR) showed significantly lower β compared with the negative counterparts (P < 0.05). The high Ki-67 expression produced significantly lower Dm and ADC values (P < 0.05). Additionally, combining multiple CTRW parameters improved the performance of diagnosing molecular subtypes of breast cancer. Moreover, Spearman correlations analysis showed that β produced significant correlations with ER, PR and Ki-67 expression (P < 0.05). ConclusionsThe CTRW parameters could be used as non-invasive quantitative imaging markers to evaluate breast lesions.

Translating new breast ultrasound techniques into clinical practice: evaluating their intended uses and describing other unexpected uses for them.

Several new ultrasound tools have been developed to further evaluate breast lesions detected on B-mode ultrasound. Strain elastography (SRE) was developed to assess the likelihood of malignancy of lesions based on their stiffness. This has been incorporated into the latest edition of the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) lexicon and atlas. However, no agreed cut-off stiffness values have been established to distinguish benign from malignant lesions making the translation into routine clinical practice difficult. Superb microvascular imaging (SMI) was developed to better evaluate the vascularity within sonographic lesions and assess their likelihood of malignancy. However, there is also no agreed cut-off value for vascular index (VI) to distinguish between benign and malignant lesions. MicroPure was developed to better visualize and evaluate calcifications seen on ultrasound. Its effective use in breast screening and evaluating the calcifications detected for likelihood of malignancy have not been established. This article describes the original intended uses of these applications and reviews the studies evaluating them, showing the varying success of the translation of these tools into routine clinical practice. Also described are some other uses of these tools for which they were not originally intended. This illustrates the importance of being perceptive to alternative uses of imaging tools in their translation from bench to bedside.

Evaluation of Contrast-Enhanced Mammography and Development of Flowchart for BI-RADS Classification of Breast Lesions.

This study aimed to evaluate contrast-enhanced mammography (CEM) and to compare breast lesions on CEM and breast magnetic resonance imaging (MRI) using 5 features. We propose a flowchart for BI-RADS classification of breast lesions on CEM based on the Kaiser score (KS) flowchart for breast MRI. Sixty-eight subjects (women and men; median age 61.4 ± 11.6 years) who were suspected of having a malignant process in the breast based on digital mammography (MG) findings were included in the study. The patients underwent breast ultrasound (US), CEM, MRI and biopsy of the suspicious lesion. There were 47 patients with malignant lesions confirmed by biopsy and 21 patients with benign lesions, for each of which a KS was calculated. In the patients with malignant lesions, the MRI-derived KS was 9 (IQR 8-9); its CEM equivalent was 9 (IQR 8-9); and BI-RADS was 5 (IQR 4-5). In patients with benign lesions, MRI-derived KS was 3 (IQR 2-3); its CEM equivalent was 3 (IQR 1.7-5); and BI-RADS was 3 (IQR 0-4). There was no significant difference between the ROC-AUC of CEM and MRI (p = 0.749). In conclusion, there were no significant differences in KS results between CEM and breast MRI. The KS flowchart is useful for evaluating breast lesions on CEM.

Diagnostic Accuracy of Full-Field Digital Mammography and Digital Breast Tomosynthesis in the Evaluation of Breast Lesions

Diagnostic Accuracy of Full-Field Digital Mammography and Digital Breast Tomosynthesis in the Evaluation of Breast Lesions

Prospective validation of 18F-Fluoroethylcholine as a tracer in PET/MRI for the evaluation of breast lesions and prediction of lymph node status

PurposeTo assess 18F-Fluoroethylcholine (18F-FEC) as a PET/MRI tracer in the evaluation of breast lesions, breast cancer aggressiveness, and prediction of lymph node status.Materials and methodsThis prospective, monocentric study was approved by the ethics committee and patients gave written, informed consent. This clinical trial was registered in the EudraCT database (Number 2017-003089-29). Women who presented with suspicious breast lesions were included. Histopathology was used as reference standard. Simultaneous 18F-FEC PET/MRI of the breast was performed in a prone position with a dedicated breast coil. MRI was performed using a standard protocol before and after contrast agent administration. A simultaneous read by nuclear medicine physicians and radiologists collected the imaging data of MRI-detected lesions, including the maximum standardized 18F-FEC-uptake value of breast lesions (SUVmaxT) and axillary lymph nodes (SUVmaxLN). Differences in SUVmax were evaluated with the Mann–Whitney U test. To calculate diagnostic performance, the area under the receiver operating characteristics curve (ROC) was used.ResultsThere were 101 patients (mean age 52.3 years, standard deviation 12.0) with 117 breast lesions included (30 benign, 7 ductal carcinomas in situ, 80 invasive carcinomas). 18F-FEC was well tolerated by all patients. The ROC to distinguish benign from malignant breast lesions was 0.846. SUVmaxT was higher if lesions were malignant (p < 0.001), had a higher proliferation rate (p = 0.011), and were HER2-positive (p = 0.041). SUVmaxLN was higher in metastatic lymph nodes, with an ROC of 0.761 for SUVmaxT and of 0.793 for SUVmaxLN.ConclusionSimultaneous 18F-FEC PET/MRI is safe and has the potential to be used for the evaluation of breast cancer aggressiveness, and prediction of lymph node status.

Combined Use of Cell Block and Smear Improves the Cytological Diagnosis of Malignancy in Non-Palpable Breast Lesions Screened by Imaging.

Currently, core needle biopsy is replacing fine needle aspiration biopsy (FNAB) for pathological diagnosis of breast lesions. However, FNAB is extensively used for diagnosing breast lesions, including screened lesions, at our hospital. Furthermore, direct smears as well as cell blocks (CBs) from the FNAB specimens have been used. To prepare the CBs, hematoxylin and eosin (HE) staining as well as immunostaining with a mixture of p63 and cytokeratin 5/6 antibodies are routinely used. Therefore, in the current study, we sought to assess the efficacy of diagnosing breast lesions using conventional smears and CB immunostaining. Breast FNAB reports of direct smears and CBs from The Nagoya Medical Center between December 2014 and March 2020, were reviewed. The efficiency of diagnoses made with direct smears and CBs were compared using histology-based diagnoses. Among the 169 histologically confirmed malignant lesions, 12 lesions that were reported as unsatisfactory, benign, or atypia probably benign, using direct smears were diagnosed as malignant using CB. Histologically, these lesions were diagnosed as carcinomas with mild atypia or papillary structures. Ten (83.3%) of the twelve lesions were non-palpable and only detected upon imaging. Combined use of CB and conventional smear leads to the detection of more malignant lesions in breast FNAB specimens, particularly in lesions detected by imaging alone. Immunostaining of CB sections using a mixture of p63 and cytokeratin 5/6 antibodies provides more information than HE staining alone. Breast FNAB with CB preparation can be successfully applied for evaluation of breast lesions in developed countries.

The diagnostic value of ultrasound and mammography in detection of breast cancer in Albania

Early detection of breast cancer is essential for improving patient survival. However, non-invasive imaging test have different diagnostic value. This study aimed to assess the diagnostic accuracy of mammography and ultrasound to detect breast malignancy in Albania. The 234 patients suspected with breast lesions in Albania during 2018-2022 were subjected to both mammograph and ultrasound and then to core needle biopsy (CNB). The BI-RADS classification was used to evaluate breast lesions. The diagnostic value of ultrasound, mammography and their combination were assessed. Mean age of participants was 55.97 years (96.2% females). Ultrasound detected higher proportions of high-risk patients compared to mammography (79.1% vs. 52.6%, respectively) but the combination of the two increased this figure even further (88.9%). The sensitivity of mammography increased quickly with age, peaking to 93.2% among patients &amp;gt;60 years old, whereas ultrasound has better sensitivity among younger participants (&amp;lt;45 years and 45-60 years); overall, the combined tests had the highest sensitivity (95.1%), followed by ultrasound (87.4%) and mammography (59.3%). In conclusion, the sensitivity of mammography is best among older patients whereas ultrasound seems to be more accurate among younger patients. The combination of mammography and ultrasound seems to increase the diagnostic accuracy of breast tumors among Albanian patients.

Analysis of radiomic features derived from post-contrast T1-weighted images and apparent diffusion coefficient (ADC) maps for breast lesion evaluation: A retrospective study

IntroductionBreast cancer is the most common malignancy among women, and its diagnosis relies on medical imaging and the invasive, uncomforted biopsy. Recent advances in quantitative imaging and specifically the application of radiomics has proved to be a very promising technique, facilitating both diagnosis and therapy. The purpose of this study is to assess radiomic features derived from post-contrast T1w Magnetic Resonance Imaging (MRI) sequences and Apparent Diffusion Coefficient (ADC) maps for the evaluation of breast pathologies. MethodsMRI data from 52 women were retrospectively reviewed, involving 54 breast lesions, both malignant and benign. Diffusion Weighted Imaging (DWI) was applied as a standard MRΙ protocol, including dynamic contrast-enhanced (DCE) MRΙ in all cases. All patients were examined on a 1.5T MRI scanner, and 216 features were initially extracted from DCE-MRI images. Histological analysis of the breast lesions was performed, and a comparative analysis of the results was carried out to assess the accuracy of the method. ResultsFollowing surgery and histological analysis, 30 lesions were found to be malignant and 24 benign. Implementation of a Machine Learning (ML) classification algorithm with 5-fold cross-validation resulted in a sensitivity of 70%, specificity of 66%, Negative Predictive Value of 82% and overall accuracy of 67% in differentiating malignancy from benevolence. ConclusionTexture analysis and ML methodology based on the first post-contrast dynamic sequences and ADC maps may be employed to differentiate between malignant and benign breast lesions, offering a promising new tool for diagnostic analysis. Implications for practiceThe results of this study will enhance knowledge around application and performance of radiomics in breast MRI, thus helping MRI radiographers who use AI-enabled technologies to better delineate the pros and cons of these procedures.