Comparative accuracy of preoperative tumor size assessment on mammography, sonography, and MRI: Is the accuracy affected by breast density or cancer subtype?

Tumor size and stage assessment accuracy of MRI and ultrasound versus pathological measurements in early breast cancer patients

BACKGROUND

Accurate size and stage estimation is important to monitor tumor response and plan further treatment in breast cancer patients undergoing neoadjuvant chemotherapy. To evaluate the accuracy of imaging findings [ultrasound (US) and magnetic resonance imaging (MRI)] for tumor size and stage estimations in early breast cancer patients and to elucidate the factors influencing tumor stage assessment.

METHODS

We retrospectively enrolled consecutive women having pathologically confirmed breast cancer (stage T1/T2, 199 patients and 201 lesions) and preoperative records available for both US and MRI. The concordance between imaging-determined and pathological tumor size and stage was explored. The McNemar's test was conducted to compare the concordance between imaging-determined tumor size and imaging-determined tumor stage. Multivariate logistic regression was used to analyze the factors that influenced the accuracy.

RESULTS

The concordance between US-determined and pathological tumor size (71.1%) was comparable to MRI-pathology concordance (72.6%). MRI-determined stage concordance (73.6%) was comparable to US-determined stage concordance (69.2%). Tumors with a larger pathological size, were more likely to be underestimated by US or MRI in terms of tumor size and stage (all P < 0.05).

CONCLUSION

Tumor size and tumor stage concordance did not significantly differ between US and MRI in early breast cancer patients; US could be the first choice for tumor size estimation and tumor staging.

Breast cancer staging with contrast-enhanced imaging. The benefits and drawbacks of MRI, CEM, and dedicated breast CT

Pretherapeutic breast cancer staging is pivotal for patient-centered disease management, guiding treatment stratification and assessing prognostic outcomes. Breast imaging plays a key role in both anatomic and prognostic staging by providing comprehensive insights into disease extent, localization, and tumor aggressiveness characteristics. To date, clinical image-based staging relies on conventional modalities such as digital mammography (DM), digital breast tomosynthesis (DBT), and ultrasound. Considering the phenotypic disparities of breast cancer and their relation to treatment response, other imaging techniques based on contrast-enhanced mechanisms, which highlight areas of increased neovascularity, appear indispensable in breast cancer staging. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) offers a comprehensive 3-dimensional assessment of extent of disease and characterization of lesions, capturing both morphological and functional aspects which are crucial for treatment and monitoring of the disease. Based on this established approach, contrast-enhanced x-ray-based techniques, with high spatial resolution, such as contrast-enhanced mammography (CEM) and dedicated contrast-enhanced breast computed tomography (dCEBCT), have emerged. This review outlines the current status, limitations, and ongoing challenges associated with each one contrast-enhanced imaging modality, while emphasis is given to key breast cancer manifestations and the optimal interpretation of their imaging phenotypes, in the current era of image-based (anatomic and prognostic) breast cancer staging.

Correlation of preoperative sonographic staging and postoperative histopathologic staging in patients with invasive breast cancer

PURPOSE

To assess the accuracy of preoperative sonographic staging in patients with primary invasive breast cancer.

METHODS

We retrospectively analyzed a prospectively kept service database of patients with newly diagnosed, unifocal, cT1-3, invasive breast cancer. All patients were diagnosed at a single center institution between January 2013 and December 2021. Clinical T stage was assessed preoperatively by ultrasound and correlated with the definite postoperative pathologic T stage. Demographics, clinical and pathological characteristics were collected. Factors influencing accuracy, over- and underdiagnosis of sonographic staging were analyzed with multivariable regression analysis.

RESULTS

A total of 2478 patients were included in the analysis. Median patients' age was 65 years. 1577 patients (63.6%) had clinical T1 stage, 864 (34.9%) T2 and 37 (1.5%) T3 stage. The overall accuracy of sonography and histology was 76.5% (n = 1896), overestimation was observed in 9.1% (n = 225) of all cases, while underestimation occurred in 14.4% (n = 357) of all cases. Accuracy increased when clinical tumor stage cT was higher (OR 1.23; 95% CI 1.10-1.38, p ≤ 0.001). The highest accuracy was seen for patients with T2 stage (82.8%). The accuracy was lower in Luminal B tumors compared to Luminal A tumors (OR 0.71; 95% CI 0.59-0.87, p ≤ 0.001). We could not find any association between sonographic accuracy in HER2 positive patients, and demographic characteristics, or tumor-related factors.

CONCLUSION

Our unicentric study showed a high accuracy of sonography in predicting T stage, especially for tumors with clinical T2 stage. Tumor stage and biological tumor factors do affect the accuracy of sonographic staging.

Imaging the dense breast

The sensitivity of mammography reduces as breast density increases, which impacts breast screening and locoregional staging in breast cancer. Supplementary imaging with other modalities can offer improved cancer detection, but this often comes at the cost of more false positives. Magnetic resonance imaging and contrast-enhanced mammography, which assess tumour enhancement following contrast administration, are more sensitive than digital breast tomosynthesis and ultrasound, which predominantly rely on the assessment of tumour morphology.

Machine Learning to Predict the Need for Postmastectomy Radiotherapy after Immediate Breast Reconstruction

Background

Post mastectomy radiotherapy (PMRT) is an independent predictor of reconstructive complications. PMRT may alter the timing and type of reconstruction recommended. This study aimed to create a machine learning model to predict the probability of requiring PMRT after immediate breast reconstruction (IBR).

Methods

In this retrospective study, breast cancer patients who underwent IBR from January 2017 to December 2020 were reviewed and data were collected on 81 preoperative characteristics. Primary outcome was recommendation for PMRT. Four algorithms were compared to maximize performance and clinical utility: logistic regression, elastic net (EN), logistic lasso, and random forest (RF). The cohort was split into a development dataset (75% of cohort for training-validation) and 25% used for the test set. Model performance was evaluated using area under the receiver operating characteristic curve (AUC), precision-recall curves, and calibration plots.

Results

In a total of 800 patients, 325 (40.6%) patients were recommended to undergo PMRT. With the training-validation dataset (n = 600), model performance was logistic regression 0.73 AUC [95% confidence interval (CI) 0.65-0.80]; RF 0.77 AUC (95% CI, 0.74-0.81); EN 0.77 AUC (95% CI, 0.73-0.81); logistic lasso 0.76 AUC (95% CI, 0.72-0.80). Without significantly sacrificing performance, 81 predictive factors were reduced to 12 for prediction with the EN method. With the test dataset (n = 200), performance of the EN prediction model was confirmed [0.794 AUC (95% CI, 0.730-0.858)].

Conclusion

A parsimonious accurate machine learning model for predicting PMRT after IBR was developed, tested, and translated into a clinically applicable online calculator for providers and patients.

Preoperative imaging accuracy in size determination of prostate cancer in men undergoing radical prostatectomy for clinically localised disease

OBJECTIVES

To compare the accuracy of pre-surgical prostate size measurements using mpMRI and USWE with imaging-based 3D-printed patient-specific whole-mount moulds facilitated histopathology, and to assess whether size assessment varies between clinically significant and non-significant cancerous lesions including their locations in different zones of the prostate.

METHODS

The study population included 202 men with clinically localised prostate cancer opting for radical surgery derived from two prospective studies. Protocol-based imaging data was used for measurement of size of prostate cancer in clinically localised disease using MRI (N = 106; USWE (N = 96). Forty-eight men overlapped between two studies and formed the validation cohort. The primary outcome of this study was to assess the accuracy of pre-surgical prostate cancerous size measurements using mpMRI and USWE with imaging-based 3D-printed patient-specific whole-mount moulds facilitated histopathology as a reference standard. Independent-samples T-tests were used for the continuous variables and a nonparametric Mann-Whitney U test for independent samples was applied to examine the distribution and median differences between mpMRI and USWE groups.

RESULTS

A significant number of men had underestimation of prostate cancer using both mpMRI (82.1%; 87/106) and USWE (64.6%; 62/96). On average, tumour size was underestimated by a median size of 7 mm in mpMRI, and 1 mm in USWE. There were 327 cancerous lesions (153 with mpMRI and 174 for USWE). mpMRI and USWE underestimated the majority of cancerous lesions (108/153; 70.6%) and (88/174; 50.6%), respectively. Validation cohort data confirmed these findings MRI had a nearly 20% higher underestimation rate than USWE (χ² (1, N = 327) = 13.580, p = 0.001); especially in the mid and apical level of the gland. Clinically non-significant cancers were underestimated in significantly higher numbers in comparison to clinically significant cancers.

CONCLUSIONS

Size measurement of prostate cancers on preoperative imaging utilising maximum linear extent technique, underestimated the extent of cancer. Further research is needed to confirm our observations using different sequences, methods and approaches for cancer size measurement.

Can Supine Breast Magnetic Resonance Imaging After a Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging Provide Information for Supine Procedures?

METHODS

A retrospective analysis was conducted on 75 lesions in 50 patients with pathologically proven breast cancer who underwent MRI in prone and supine positions between December 2019 and December 2020. The transverse, anteroposterior, and craniocaudal dimensions (in millimeters) of the tumor in the x-, y-, and z-axes were measured. Distances from the center of the tumor to the chest wall and the adjacent skin were measured on transverse and reformatted sagittal images. In cases where multifocal lesions were present, the transverse, anteroposterior, and craniocaudal distances between the tumor centers in the x-, y-, and z-axes were measured. Differences between measurements in supine and prone MRI were evaluated with the Mann-Whitney U and the Wilcoxon tests. P values of less than 0.05 were considered to indicate a statistically significant difference.

RESULTS

The analysis revealed 31 MRIs with 1 and 20 with multifocal lesions. The x-axis dimension of the lesions in prone and supine positions did not significantly differ (P = 0.198) between the 2 positions. A significant difference in the y- and z-axes dimensions was observed between the prone and supine position (P = 0.00 for both). The distance from the tumor to the chest wall and the adjacent skin showed significant difference (P = 0.00 for both). For multifocal lesions, the distance between the lesions showed a significant difference on the y-axis (P = 0.00).

CONCLUSIONS

This study showed a significant difference in the tumor size, location, and tumor-to-tumor distances due to change of patient position, from the standard prone MRI to the supine position in the operating room, resulting in distortion, spatial repositioning, and convergence of the lesions. Supine MRI may be considered in providing a less extensive surgery.

Surgical Planning after Neoadjuvant Treatment in Breast Cancer: A Multimodality Imaging-Based Approach Focused on MRI

Neoadjuvant chemotherapy (NACT) today represents a cornerstone in the treatment of locally advanced breast cancer and highly chemo-sensitive tumors at early stages, increasing the possibilities of performing more conservative treatments and improving long term outcomes. Imaging has a fundamental role in the staging and prediction of the response to NACT, thus aiding surgical planning and avoiding overtreatment. In this review, we first examine and compare the role of conventional and advanced imaging techniques in preoperative T Staging after NACT and in the evaluation of lymph node involvement. In the second part, we analyze the different surgical approaches, discussing the role of axillary surgery, as well as the possibility of non-operative management after-NACT, which has been the subject of recent trials. Finally, we focus on emerging techniques that will change the diagnostic assessment of breast cancer in the near future.

Accuracy of different sonomammographic imaging modalities in assessment of breast tumor size

Background

Accurate breast cancer size is crucial for staging and an important prognostic factor in patient management. Therapeutic decisions heavily depend on tumor size detection by radiological imaging. The purpose of our prospective comparative study is to compare the diagnostic accuracy of different sonomammographic breast imaging modalities, namely DM, DBT, CESM, 2D US and 3D US in the preoperative tumor size measurement.

Results

CESM, 3D US and 2D US achieved moderately strong correlation with the pathological size measurements, while (DM) and (DBT) showed fair correlation with the pathology. CESM showed the highest correlation coefficient (0.789), while (DBT) showed the lowest correlation coefficient (0.411). Regarding the agreement, there was good agreement of the size measured by CESM, 3D US and 2D US with the pathology as the ICC was (0.798), (0.769) and (0.624), respectively. The highest agreement with the pathology was achieved with CESM. The agreement of the size measured by (DM) and (DBT) with the pathology was moderate as the ICC was (0.439) and (0.416), respectively. The lowest agreement was achieved with the size measured by (DBT).

Conclusions

CESM and 3D US are more superior to DM, 2D US and DBT regarding preoperative size measurement. 3D US can be used as preoperative noninvasive technique, especially in patients with impaired renal function who cannot tolerate CESM.

Neoadjuvant afatinib with paclitaxel for triple-negative breast cancer and the molecular characteristics in responders and non-responders

BACKGROUND

The prognosis of triple-negative breast cancer (TNBC) is worse and a major proportion of TNBC expresses epidermal growth factor receptor (EGFR). Afatinib can inhibit EGFR signal pathway; however, its treatment effect for TNBC is unknown. Thus, we aimed to assess the efficacy and biomarkers of afatinib in combination with paclitaxel in a neoadjuvant setting.

METHODS

Patients with stage II to III TNBC were enrolled. They received 40 mg of afatinib daily for 14 days, followed by daily afatinib and weekly paclitaxel (80 mg/m2) every 21 days for four to six cycles. To explore the mechanisms of responsiveness and non-responsiveness, 409 cancer-associated genes were sequenced.

RESULTS

Twenty-one patients were enrolled and one patient achieved a complete clinical response; however, a 2 mm residual tumor was noted in the surgical specimen. Overall, 33.0% patients were responders. Fifteen patients received molecular testing. No activated mutation of EGFR or Her2 were found. Activated PI3K or JAK2 pathway were trended to associate with non-responder (p = 0.057). Mutation of homologous recombination (HR) genes were correlated with non-responsiveness (p = 0.005). Seven patients did not have altered PI3K, JAK2 or HR pathway; six (85.7%) of them were responder. Patients with the amplified DAXX gene was associated with a favorable trend of response (p = 0.109).

CONCLUSION

Adding afatinib to neoadjuvant paclitaxel generated a modest effect in TNBC. Exploratory molecular analysis suggested that activated PI3K, JAK2 pathways and mutation of HR genes were associated with therapeutic non-responsiveness, and amplification of DAXX genes was associated with responsiveness to afatinib in combination with paclitaxel.

Accuracy of conventional ultrasound, contrast-enhanced ultrasound and dynamic contrast-enhanced magnetic resonance imaging in assessing the size of breast cancer

OBJECTIVE

This study was performed to investigate the accuracy of conventional ultrasound (US), contrast-enhanced US (CEUS), and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in assessing the size of breast cancer.

METHODS

In total, 49 breast cancer lesions of 48 patients were included in this study. The inclusion criteria were the performance of total mastectomy or breast-conserving surgery for treatment of breast cancer in our hospital from January 2017 to December 2020 with complete pathological results, as well as the performance of conventional US, CEUS, and DCE-MRI examinations with complete results. The exclusion criteria were non-mass breast cancer shown on conventional US or DCE-MRI, including that found on CEUS with no boundary with surrounding tissues and no confirmed tumor scope; a tumor too large to be completely displayed in the US section, thus affecting the measurement results; the presence of two nodules in the same breast that were too close to each other to be distinguished by any of the three imaging methods; and treatment with preoperative chemotherapy. Preoperative conventional US, CEUS, and DCE-MRI examinations were performed. The postoperative pathological results were taken as the gold standard. The lesion size was represented by its maximum diameter. The accuracy, overestimation, and underestimation rates of conventional US, CEUS, and DCE-MRI were compared.

RESULTS

The maximum lesion diameter on US, CEUS, DCE-MRI and pathology were 1.62±0.63 cm (range, 0.6-3.5 cm), 2.05±0.75 cm (range, 1.0-4.0 cm), 1.99±0.74 cm (range, 0.7-4.2 cm) and 1.92±0.83 cm (range, 0.5-4.0 cm), respectively. The lesion size on US was significantly smaller than that of postoperative pathological tissue (P <  0.05). However, there was no significant difference between the CEUS or DCE-MRI results and the pathological results. The underestimation rate of conventional US (55.1%, 27/49) was significantly higher than that of CEUS (20.4%, 10/49) and DCE-MRI (24.5%, 12/49) (P <  0.001 and P = 0.002, respectively). There was no significant difference in the accuracy of CEUS (36.7%, 18/49) and DCE-MRI (34.7%, 17/49) compared with conventional US (26.5%, 13/49); however, the accuracy of both groups tended to be higher than that of conventional US. The overestimation rate of CEUS (42.9%, 21/49) and DCE-MRI (40.8%, 20/49) was significantly higher than that of conventional US (18.4%, 9/49) (P = 0.001 and P = 0.015, respectively).

CONCLUSIONS

CEUS and DCE-MRI show similar performance when evaluating the size of breast cancer. However, CEUS is more convenient, has a shorter operation time, and has fewer restrictions on its use. Notably, conventional US is more prone to underestimate the size of lesions, whereas CEUS and DCE-MRI are more prone to overestimate the size.

Advances in Imaging in Evaluating the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer

Neoadjuvant chemotherapy (NAC) is increasingly widely used in breast cancer treatment, and accurate evaluation of its response provides essential information for treatment and prognosis. Thus, the imaging tools used to quantify the disease response are critical in evaluating and managing patients treated with NAC. We discussed the recent progress, advantages, and disadvantages of common imaging methods in assessing the efficacy of NAC for breast cancer.

Evaluation of Breast Cancer Size Measurement by Computer-Aided Diagnosis (CAD) and a Radiologist on Breast MRI

Purpose: This study aimed to evaluate cancer size measurement by computer-aided diagnosis (CAD) and radiologist on breast magnetic resonance imaging (MRI) relative to histopathology and to determine clinicopathologic and MRI factors that may affect measurements. Methods: Preoperative MRI of 208 breast cancers taken between January 2017 and March 2021 were included. We evaluated correlation between CAD-generated size and pathologic size as well as that between radiologist-measured size and pathologic size. We classified size discrepancies into accurate and inaccurate groups. For both CAD and radiologist, clinicopathologic and imaging factors were compared between accurate and inaccurate groups. Results: The mean sizes as predicted by CAD, radiologist and pathology were 2.66 ± 1.68 cm, 2.54 ± 1.68 cm, and 2.30 ± 1.61 cm, with significant difference (p < 0.001). Correlation coefficients of cancer size measurement by radiologist and CAD in reference to pathology were 0.898 and 0.823. Radiologist’s measurement was more accurate than CAD, with statistical significance (p < 0.001). CAD-generated measurement was significantly more inaccurate for cancers of larger pathologic size (>2 cm), in the presence of an extensive intraductal component (EIC), with positive progesterone receptor (PR), and of non-mass enhancement (p = 0.045, 0.045, 0.03 and 0.002). Radiologist-measured size was significantly more inaccurate for cancers in presence of an in situ component, EIC, positive human epidermal growth factor receptor 2 (HER2), and non-mass enhancement (p = 0.017, 0.008, 0.003 and <0.001). Conclusion: Breast cancer size measurement showed a very strong correlation between CAD and pathology and radiologist and pathology. Radiologist-measured size was significantly more accurate than CAD size. Cancer size measurement by CAD and radiologist can both be inaccurate for cancers with EIC or non-mass enhancement.

Prediction of tumor size in patients with invasive ductal carcinoma using FT-IR spectroscopy combined with chemometrics: a preliminary study

Precise detection of tumor size is essential for early diagnosis, treatment, and evaluation of the prognosis of breast cancer. However, there are some errors between the tumor size of breast cancer measured by conventional imaging methods and the pathological tumor size. Invasive ductal carcinoma (IDC) is a common pathological type of breast cancer. In this study, serum Fourier transform infrared spectroscopy (FT-IR) combined with chemometric methods was used to predict the maximum diameter and maximum vertical diameter of tumors in IDC patients. Three models were evaluated based on the pathological tumor size measured after surgery and included grid search support vector machine regression (GS-SVR), back propagation neural network optimized by genetic algorithm (GA-BP-ANN), and back propagation neural network optimized by particle swarm optimization (PSO-BP-ANN). The results show that three models can accurately predict tumor size. The GA-BP-ANN model provided the best fitting quality of the largest tumor diameter with the determination coefficients of 0.984 in test set. And the GS-SVR model provided the best fitting quality of the largest vertical tumor diameter with the determination coefficients of 0.982 in test set. The GS-SVR model had the highest prediction efficiency and the lowest time complexity of the models. The results indicate that serum FT-IR spectroscopy combined with chemometric methods can predict tumor size in IDC patients. In addition, compared with traditional imaging methods, we found that the experimental results of the three models are better than traditional imaging methods in terms of correlation and fitting degree. And the average fitting error of PSO-BP-ANN and GA-BP-ANN models was less than 0.3 mm. The minimally invasive detection method is expected to be developed into a new clinical diagnostic method for tumor size estimation to reduce the diagnostic trauma of patients and provide new diagnostic experience for patients. Graphical Abstract.

Value of ultrafast and standard dynamic contrast-enhanced magnetic resonance imaging in the evaluation of the presence and extension of residual disease after neoadjuvant chemotherapy in breast cancer

PURPOSE

To evaluate the diagnostic performance of ultrafast and standard dynamic contrast-enhanced (DCE)-MRI in evaluating the residual disease after neoadjuvant chemotherapy (NAC) for breast cancer.

MATERIALS AND METHODS

Sixty-seven consecutive patients underwent MRI after NAC. Visual analysis of enhancement was performed on ultrafast and standard DCE-MRI, and compared between no residual disease and residual disease groups. The lesion diameters measured on the last phase of ultrafast DCE-MRI and early and delayed phases of standard DCE-MRI were compared with pathological diameter of entire residual cancer and residual invasive ductal carcinoma (IDC).

RESULTS

The visual analysis in the delayed phase of standard DCE-MRI exhibited the highest sensitivity (90%), whereas ultrafast DCE-MRI revealed the highest positive predictive value (92%). There were no significant differences between the diameters in the delayed phase of the standard DCE-MRI and the pathological entire residual cancer (p = 0.97), and the diameters in ultrafast DCE-MRI and the pathological residual IDC (p = 0.97).

CONCLUSION

The delayed phase of standard DCE-MRI may be effective for detecting the residual disease and evaluating the extension of entire residual cancer. Enhancement in ultrafast DCE-MRI may be strongly suggestive of the presence of residual disease, and effective for evaluating the extension of residual IDC.

Breast Cancer Staging: Updates in the AJCC Cancer Staging Manual, 8th Edition, and Current Challenges for Radiologists, From the AJR Special Series on Cancer Staging

The standardization of the AJCC TNM staging system for breast cancer allows physicians to evaluate patients with breast cancer using standard language and criteria, assess treatment response, and compare patient outcomes. Previous editions of the AJCC Cancer Staging Manual relied on the anatomic TNM method of staging that incorporates imaging and uses population-level survival data to predict patient outcomes. Recent advances in therapy based on biomarker status and multigene panels have improved treatment strategies. In the newest edition of the AJCC Cancer Staging Manual (8th edition, adopted on January 1, 2018), breast cancer staging integrates anatomic staging with tumor grade, biomarker data regarding hormone receptor status, oncogene expression, and gene expression profiling to assign a prognostic stage. This article reviews the 8th edition of the AJCC breast cancer staging system with a focus on anatomic staging and the challenges that anatomic staging poses for radiologists. We highlight key imaging findings that impact patient treatment and discuss the role of imaging in evaluating response to neoadjuvant therapy. Finally, we discuss biomarkers and multigene panels and how these impact prognostic stage. The review will help radiologists identify critical findings that affect breast cancer staging and understand ongoing limitations of imaging in staging.

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 ± 6.12 mm. Tumor sizes on SWE were significantly different from pathologic sizes (18.00 ± 6.71 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.

Breast Ultrasound Versus MRI in Prediction of Pathologic Complete Response to Neoadjuvant Chemotherapy for Breast Cancer: A Systematic Review and Meta-Analysis

Introduction:

Neoadjuvant chemotherapy (NAC) is widely used to treat breast cancer. Sentinel lymph node biopsy has replaced axillary lymph node dissection in patients who convert to node-negative status, after NAC. However, few studies have evaluated the diagnostic performance of ultrasonography (US) and magnetic resonance imaging (MRI) in determining axillary lymph node status after NAC. The aim of this study was to evaluate the diagnostic performance of breast US and MRI in predicting a response to NAC, for breast cancer.

Methods:

A systematic search, in PubMed, the Cochrane Library, and Web of Science, for original studies was performed. The Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to assess the methodological quality of the included studies. Patient, study, and imaging characteristics were extracted, and sufficient data were used to reconstruct 2 × 2 tables. Data pooling, heterogeneity testing, forest plot construction, meta-regression analysis, and sensitivity analysis were performed using Meta-DiSc and Stata version 14.0 (StataCorp LP, College Station, TX, USA).

Results:

Nine studies met all the eligibility criteria and were included. The pooled sensitivity and specificity of MRI were 0.78 and 0.92, while the corresponding values for US were 0.80 and 0.90, respectively. The prevalence of pathologic complete response (pCR), among breast cancer patients, after neoadjuvant therapy was 26%. The prevalence of patients with estrogen receptor (ER)-, human epidermal growth factor receptor (HER)-, and progesterone receptor (PR)-positive tumors were 65%, 22%, and 37%, respectively.

Conclusion:

These results showed that MRI and US have almost the same accuracy in predicting pCR in patients with breast cancer undergoing neoadjuvant surgery. There is still a need for further investigations to prove that US is not inferior to MRI for this diagnosis.

Accuracy of breast MRI in patients receiving neoadjuvant endocrine therapy: comprehensive imaging analysis and correlation with clinical and pathological assessments

Purpose

To assess the accuracy of magnetic resonance imaging (MRI) measurements in locally advanced oestrogen receptor-positive and human epidermal growth factor receptor 2-negative breast tumours before, during and after neoadjuvant endocrine treatment (NET) for evaluation of tumour response in comparison with clinical and pathological assessments.

Methods

This prospective study enrolled postmenopausal patients treated neoadjuvant with letrozole and exemestane given sequentially in an intra-patient cross-over regimen. Fifty-four patients were initially recruited, but only 35 fulfilled the inclusion criteria and confirmed to participate with a median age of 77. Tumours were scanned with MRI prior to treatment, during the eighth week of treatment and prior to surgery. Additionally, changes in longest diameter on clinical examination (CE) and tumour size at pathology were determined. Pre- and post-operative measurements of tumour size were compared in order to evaluate tumour response.

Results

The correlation between post-treatment MRI size and pathology was moderate and higher with a correlation coefficient (r) 0.64 compared to the correlation between CE and pathology r = 0.25. Post-treatment MRI and clinical results had a negligible bias towards underestimation of lesion size. Tumour size on MRI and CE had 0.82 cm and 0.52 cm lower mean size than tumour size measured by pathology, respectively.

Conclusions

The higher correlation between measurements of residual disease obtained on MRI and those obtained with pathology validates the accuracy of imaging assessment during NET. MRI was found to be more accurate for estimating complete responses than clinical assessments and warrants further investigation in larger cohorts to validate this finding.

Electronic supplementary material

The online version of this article (10.1007/s10549-020-05852-7) contains supplementary material, which is available to authorized users.

Tumor size estimation of the breast cancer molecular subtypes using imaging techniques

Background and aim

In medical practice the classification of breast cancer is most commonly based on the molecular subtypes, in order to predict the disease prognosis, avoid over-treatment, and provide individualized cancer management. Tumor size is a major determiner of treatment planning, acting on the decision-making process, whether to perform breast surgery or administer neoadjuvant chemotherapy. Imaging methods play a key role in determining the tumor size in breast cancers at the time of the diagnosis.

We aimed to compare the radiologically determined tumor sizes with the corresponding pathologically determined tumor sizes of breast cancer at the time of the diagnosis, in correlation with the molecular subtypes.

Methods

Ninety-one patients with primary invasive breast cancer were evaluated. The main molecular subtypes were luminal A, luminal B, HER-2 positive, and triple-negative. The Bland-Altman plot was used for presenting the limits of agreement between the radiologically and the pathologically determined tumor sizes by the molecular subtypes.

Results

A significantly proportional underestimation was found for the luminal A subtype, especially for large tumors. The p-values for the magnetic resonance imaging, mammography, and ultrasonography were 0.020, 0.030, and <0.001, respectively. No statistically significant differences were observed among the radiologic modalities in determining the tumor size in the remaining molecular subtypes (p>0.05).

Conclusion

The radiologically determined tumor size was significantly smaller than the pathologically determined tumor size in the luminal A subtype of breast cancers when measured with all three imaging modalities. The differences were more prominent with ultrasonography and mammography. The underestimation rate increases as the tumor gets larger.

Accuracy in tumor size measurements: Comparison of digital mammography, digital breast tomosynthesis and synthetic mammography

PURPOSE

The aim of this study was to assess the accuracy of digital mammography (DM), digital breast tomosynthesis (DBT) and synthetic mammography (SM) in tumor size measurements compared with histological tumor sizes.

MATERIALS AND METHODS

71 breast cancer patients who underwent DM and DBT acquisitions simultaneously were included in this study. One radiologist with 8 years of experience in breast imaging measured tumor sizes independently in three separate sessions which include DM, DBT and SM images, respectively. The correlations between the measured tumor sizes on each imaging technique and histological sizes were analyzed using Spearman correlation test. The patients were categorized into two subgroups according to assigned breast density categories (dense and non-dense), and histological tumor sizes (≤2 cm and > 2 cm). To assess the agreement levels between the measured tumor sizes and histological sizes Bland-Altman analyses were performed for each imaging technique.

RESULTS

The mean of histological size of tumors was 23.85 ± 16.57 mm (median: 20). The means of measured tumor sizes were 21.21 ± 13.59 mm (median: 19), 21.52 ± 13.42 mm (median: 19) and 18.97 ± 11.21 mm (median: 17) in DM, DBT and SM, respectively. The Spearman correlation values with histologic sizes were 0.814 (P < 0.001), 0.887 (P < 0.001), and 0.852 (P < 0.001) for DM, DBT and SM, respectively. In subgroup analyses, the correlation values showed decrement for tumors >2 cm in size compared to tumors ≤2 cm in size.

CONCLUSION

DBT provides the most accurate tumor size measurements among mammographic imaging techniques and if mammography will be used in tumor size measurements, DBT should be preferred.

Breast density does not affect breast cancer tumor size assessment: A comparison of radiologic versus pathologic measurement by different imaging modalities across breast densities

BACKGROUND

Tumor size is an important parameter in breast cancer staging. Definitive tumor size is determined by measurement of the pathologic specimen. However, prior to surgery, size must be assessed by imaging with mammography (MMG), ultrasound (US), or magnetic resonance imaging (MRI). Discrepancies between imaging-assessed and pathologic size are not uncommon. Breast density decreases the sensitivity of MMG, and may affect image-based tumor size assessment.

AIM

To compare tumor size assessed by the different imaging modalities to pathologic size across breast densities.

MATERIAL & METHODS

This was a retrospective analysis of 183 female patients (197 breast cancers) diagnosed and operated for primary breast cancer at a single center. Tumor size measurements were collated for each available imaging modality and compared with measurements from pathologic specimens. Breast density was assessed on MMG using the Breast Imaging Reporting and Data System.

RESULTS

Mean pathologic tumor size was 23.0 ± 19.3 mm. Mean tumor size did not differ significantly with MMG (22.3 ± 16.6 mm; P = 0.165) or MRI (23.4 ± 19.2 mm; P = 0.620). However, US significantly underestimated mean tumor size (15.2 ± 8.6 mm; P = 0.0001 vs pathology). Breast density did not affect the accuracy of tumor size assessment by any imaging modality.

CONCLUSIONS

US may underestimate breast tumor size. Treatment decisions that take into account tumor size can be made equally reliably in patients with high or low breast density.

Influence of different post-contrast time points on dynamic contrast-enhanced (DCE) MRI T staging in breast cancer

PURPOSE

to assess whether MRI T stage of breast cancer lesions (BCLs) is affected by maximum diameter (MD) measured at different post-contrast time points (TPs) on different acquisition planes on dynamic contrast-enhanced (DCE) MRI sequence.

METHODS

53 DCE-MRI examinations of patients with BCLs were retrospectively selected. MD of BCLs was measured on axial, coronal and sagittal planes on DCE images at five different post-contrast TPs. Friedman test followed by Bonferroni-adjusted Wilcoxon-signed rank test for post-hoc analysis was performed to evaluate differences among the five measurements. Reliability of the measurements was evaluated with the intraclass correlation coefficient analysis. Differences between pathological and MRI T stage assessed at each TP on each acquisition plane were assessed using the Wilcoxon-sign rank test; p values <0.05 were considered statistically significant.

RESULTS

on axial, coronal and sagittal planes, MD measured at TP1 was significantly different (p < 0.0001) compared to those obtained at the subsequent TPs. No significant differences were found between MD measured at TPs 3, 4 and 5. Intra and inter-observer reliability resulted as very good, with ICC ranging between 0.915-0.992 and 0.845-0.911, respectively. MRI T stage assessed at TP1 on axial and sagittal plane as well as at all TPs on coronal plane was significantly different from pathological T stage.

CONCLUSION

MRI T stage definition of BCLs is significantly affected by the TP used for lesions' MD measurement. TPs 3, 4 and 5 are the preferred TPs for the assessment of MRI T stage of BCLs on both axial and sagittal planes.

Influence of Tumor Subtype, Radiological Sign and Prognostic Factors on Tumor Size Discrepancies Between Digital Breast Tomosynthesis and Final Histology

Background

Influence of tumor subtype, radiological sign and prognostic factors on tumor size discrepancies between DBT and final histology has not been completely investigated so far.

Purpose

To study the influence of tumor subtype, radiological sign and prognostic factors on tumor size discrepancies between digital breast tomosynthesis and final histology.

Material and methods

This is a retrospective study conducted between January 2015 and December 2016. After IRB approval, 130 consecutive patients with breast cancer diagnosed with digital breast tomosynthesis (DBT) were evaluated. A discrepancy between DBT and final histology was considered present if the difference was above the cut-off of 5 mm. Tumor subtype, radiological sign and prognostic factors were evaluated in patients with discrepancies. Descriptive statistic and non-parametric tests were used.

Results

A total of 105 cases of cancer, in 96 patients, all female, were included. Mean age was 61 years (range: 35-82 yrs). In 19 (18.1%) cases, discrepancies were found: 13 (68.4%) were underestimated by DBT. For tumor subtype, 10 (52.6%) were infiltrating lobular carcinomas (ILC) (p < 0.01). Fourteen (73.7%) discordant cases were architectural distortions (p < 0.01). Prognostic factors did not affect tumor size discrepancies.

Conclusion

ILC or an architectural distortion represents the majority of cases of tumor size discrepancies between DBT and final histology.

Breast lesion size assessment in mastectomy specimens: Correlation of cone-beam breast-CT, digital breast tomosynthesis and full-field digital mammography with histopathology

To compare the accuracy of breast lesion size measurement of cone-beam breast-CT (CBBCT), digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM).Patients scheduled for mastectomy due to at least 1 malignant breast lesion were included. Mastectomy specimens were examined by CBBCT, DBT, FFDM, and histopathology.A total of 94 lesions (40 patients) were included. Histopathological analyses revealed 47 malignant, 6 high-risk, and 41 benign lesions. Mean histopathological lesion size was 20.8 mm (range 2-100). Mean absolute size deviation from histopathology was largest for FFDM (5.3 ± 6.7 mm) and smallest for CBBCT 50 mA, high-resolution mode (4.3 ± 6.7 mm). Differences between imaging modalities did not reach statistical significance (P = .85).All imaging methods tend to overestimate breast lesion size compared to histopathological gold standard. No significant differences were found regarding size measurements, although in tendency CBBCT showed better lesion detection and cT classification over FFDM.

Comparison of MRI and US in Tumor Size Evaluation of Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

Objective

Magnetic resonance imaging (MRI) and ultrasonography (US) are commonly used in the pre-surgery determination of tumor size and the follow-up of breast cancer patients treated with neoadjuvant chemotherapy (NAC). The aim of this study was to compare the efficiency of preoperative MRI and US in tumor size evaluation of patients with breast cancer after NAC to guide clinicians on the appropriate treatment plan.

Materials and Methods

The study included a total of 75 patients who had undergone radiological follow-up, surgical treatment and pathological examination in our hospital between 2013 and 2016. Of these, 28 patients were followed-up with MRI and 47 with US. The dimension evaluations in pathology examination and on both MRI and US were based on the longest dimension of the tumor.

Results

There was no statistically significant difference between the tumor size measured pathologically and the size measured preoperatively on MRI (p=0.379). The tumor size measured on US before surgery was significantly smaller than the size measured in pathology (p=0.004). MRI did not overestimate by more than 10 mm in any patient, whereas US overestimated in 4 patients (8.6%). The correlation coefficient of MRI was higher than that of US (0.927 and 0.687, respectively).

Conclusion

MRI is superior to US in preoperative tumor size evaluation of patients receiving NAC.

Update of the American Society of Breast Surgeons Toolbox to address the lumpectomy reoperation epidemic

In 2015, the American Society of Breast Surgeons (ASBrS) convened a multidisciplinary consensus conference, the Collaborative Attempt to Lower Lumpectomy Reoperation Rates (CALLER). The CALLER conference endorsed a "toolbox" of multiple processes of care for which there was evidence that they were associated with fewer reoperations. We present an update of the toolbox taking into consideration the latest advances in decreasing re excision rates. In this review, we performed a comprehensive review of the literature from 2015-2018 using search terms for each tool. The original ten tools were updated with the latest evidence from the literature and our strength of recommendation. We added an additional section looking at new tools and techniques that may provide more accurate intraoperative assessment of margins. The updates on the CALLER Toolbox for lumpectomy will help guide surgeons to various resources to aid in the removal of breast cancer, while being aware of cosmesis and decreasing re excision rates.

Accuracy of Ultrasound for Preoperative Assessment of Tumor Size in Patients With Newly Diagnosed Breast Cancer: Is It Affected by the Background Parenchymal Echotexture?

OBJECTIVES

To assess the impact of the background parenchymal echotexture on the accuracy of tumor size estimation using breast ultrasound (US).

METHODS

A total of 140 women with newly diagnosed invasive breast cancer from January 2014 to December 2015 were enrolled in this study. Two radiologists retrospectively reviewed US images in consensus for background parenchymal echotexture interpretation. The maximum tumor diameter from static images was recorded. Tumor size measurements were considered as having agreement with histologic results if they were within ±5 mm compared to the pathologic size. The relationship between the accuracy of tumor size measurement by the background parenchymal echotexture and clinicopathologic characteristics was evaluated.

RESULTS

Of these 140 patients, 77 (55.0%) showed a homogeneous background parenchymal echotexture, whereas 63 (45.0%) showed a heterogeneous echotexture. The mean tumor size was 1.9 cm (range, 0.5-4.9 cm). The overall accuracy of tumor size measurement was 76.4% (104 of 140). Tumors of women with a homogeneous background parenchymal echotexture were more accurately measured than those of women with a heterogeneous echotexture (87.0% versus 63.5%; P = .001). Tumors with a small size (<2 cm; P = .018) and ductal carcinoma in situ-negative (P = .031), human epidermal growth factor receptor 2 (HER2)-negative (P = .053), and triple-negative (P = .016) types were also more accurately measured. The independent factors associated with inaccurate tumor size measurement were a heterogeneous background parenchymal echotexture, a large tumor size, and the HER2-enriched type (P < .05).

CONCLUSIONS

The background parenchymal echotexture affected the accuracy of tumor size estimation using breast US. Invasive breast cancers with large (≥2 cm) tumors and the HER2-enriched type showed significantly lower breast US accuracy compared to others.

Feasibility of mapping breast cancer with supine breast MRI in patients scheduled for oncoplastic surgery

OBJECTIVES

To prospectively determine the feasibility of preoperative supine breast MRI in breast cancer patients scheduled for oncoplastic breast-conserving surgery.

METHODS

In addition to a diagnostic prone breast MRI, a supplementary supine MRI was performed with the patient in the surgical position including skin markers. Tumours' locations were ink-marked on the skin according to findings obtained from supine MRI. Changes in tumours' largest diameter and locations between prone and supine MRI were measured and compared to histology. Nipple-to-tumour and tumour-to-chest wall distances were also measured. Tumours and suspicious areas were surgically removed according to skin ink-markings. The differences between MRI measurements with reference to histopathology were evaluated with the paired-sample t test.

RESULTS

Fourteen consecutive patients, 15 breasts and 27 lesions were analysed. Compared to histology, prone MRI overestimated tumour size by 47.1% (p = 0.01) and supine MRI by 14.5% (p = 0.259). In supine MRI, lesions' mean diameters and areas were smaller compared to prone MRI (- 20.9%, p = 0.009 and - 38.3%, p = 0.016, respectively). This difference in diameter was more pronounced in non-mass lesions (- 31.2%, p = 0.031) compared to mass lesions (- 9.2%, p = 0.009). Tumours' mean distance from chest wall diminished by 69.4% (p < 0.001) and from nipple by 18.2% (p < 0.001). Free microscopic margins were achieved in first operation in all patients.

CONCLUSIONS

Supine MRI in the surgical position is feasible and useful in the precise localisation of prone MRI-detected lesions and provides a helpful tool to implement in surgery. Supine MRI more accurately determines tumours' size and location and might have an important role to diminish overestimations.

KEY POINTS

• Breath-hold supine breast MRI is feasible using commercially available coils and sequences. • Size and area of lesions on MRI were consistently smaller when measured from the supine position as compared to the prone position. • Supine breast MRI is useful in the precise preoperative localisation of prone MRI-detected lesions. •.

Agreement between MRI and pathologic analyses for determination of tumor size and correlation with immunohistochemical factors of invasive breast carcinoma

Background There may be discordance between tumor size determined by magnetic resonance imaging (MRI) and that observed during pathologic analyses. Purpose To evaluate MRI-pathology concordance of tumor size in patients with invasive breast carcinoma. Material and Methods Data from 307 invasive breast carcinomas were analyzed retrospectively. Preoperative breast MRI was reviewed for size, lesion type, morphology, and dynamic contrast-enhanced tumor kinetics. MRI tumor size was compared with tumor size measurements from the pathologic analysis. Concordance was defined as a difference in diameter of ≤ 0.5 cm. MRI-pathology concordance was compared according to clinical and histopathologic features. Results The mean tumor size on MRI was 2.48 ± 1.41 cm. Tumor measurements determined by MRI were not significantly different from those recorded in the pathologic reports (2.56 ± 1.61 cm, P = 0.199). MRI-pathology concordance was found in 229/307 (74.6%) cases; the size was overestimated in 36 (11.7%) tumors and underestimated in 42 (13.7%). On univariate analysis, MRI-pathology discordance was associated with larger tumor size ( P < 0.001), estrogen receptor (ER) negativity ( P = 0.006), and lymphovascular invasion ( P = 0.003). Human epidermal growth factor receptor 2 positive molecular subtype showed worse correlation between the tumor size measured by MRI and pathology compared with luminal A and luminal B subtypes ( P = 0.008 and 0.007). On multivariate analysis, tumor size and ER status significantly influenced MRI-pathology concordance ( P < 0.05). Conclusion ER negativity and larger tumor size were strongly associated with MRI-pathology discordance in invasive breast carcinomas. Awareness of these factors might improve surgical planning.

Development of nomograms to predict axillary lymph node status in breast cancer patients

BACKGROUND

Prediction of axillary lymph node (ALN) status preoperatively is critical in the management of breast cancer patients. This study aims to develop a new set of nomograms to accurately predict ALN status.

METHODS

We searched the National Cancer Database to identify eligible female breast cancer patients with profiles containing critical information. Patients diagnosed in 2010-2011 and 2012-2013 were designated the training (n = 99,618) and validation (n = 101,834) cohorts, respectively. We used binary logistic regression to investigate risk factors for ALN status and to develop a new set of nomograms to determine the probability of having any positive ALNs and N2-3 disease. We used ROC analysis and calibration plots to assess the discriminative ability and accuracy of the nomograms, respectively.

RESULTS

In the training cohort, we identified age, quadrant of the tumor, tumor size, histology, ER, PR, HER2, tumor grade and lymphovascular invasion as significant predictors of ALNs status. Nomogram-A was developed to predict the probability of having any positive ALNs (P_any) in the full population with a C-index of 0.788 and 0.786 in the training and validation cohorts, respectively. In patients with positive ALNs, Nomogram-B was developed to predict the conditional probability of having N2-3 disease (P_con) with a C-index of 0.680 and 0.677 in the training and validation cohorts, respectively. The absolute probability of having N2-3 disease can be estimated by P_any*P_con. Both of the nomograms were well-calibrated.

CONCLUSIONS

We developed a set of nomograms to predict the ALN status in breast cancer patients.

Estimation of tumor size in breast cancer comparing clinical examination, mammography, ultrasound and MRI-correlation with the pathological analysis of the surgical specimen

BACKGROUND

To evaluate the best method in our center to measure preoperative tumor size in breast tumors, using as reference the tumor size in the postoperative surgical specimen. We compared physical examination vs. mammography vs. resonance vs. ultrasound. There are different studies in the literature with disparate results.

METHODS

This is a retrospective study. All the included patients have been studied by clinical examination performed by gynecologist or surgeon specialists in senology, and radiological tests (mammography, ultrasound and magnetic resonance imaging). The correlation of mammary examination, ultrasound, mammography and resonance with pathological anatomy was studied using the Pearson index. Subsequently, the results of such imaging tests were compared with the tumor size of the infiltrating component measured by anatomopathological study using a student's t test for related variables. The level of significance was set at 95%. Statistical package R. was used.

RESULTS

A total of 73 cases were collected from October 2015 to July 2016 with diagnosis of infiltrating breast carcinoma. Twelve cases of carcinoma in situ and seven cases of neoadjuvant carcinoma are excluded. Finally, a total of 56 cases were included in the analysis. The mean age of the patients is 57 years. The histology is of infiltrating ductal carcinoma in 46 patients (80.7%), lobular in 8 (14%) and other carcinomas in 3 cases (5.2%). We verified the relationship between preoperative tumor size by physical examination, mammography, ultrasound (US) and magnetic resonance imaging (MRI), and the final size of the surgical specimen by applying a Pearson correlation test. A strong correlation was found between the physical examination results 0.62 (0.43-0.76 at 95% CI), ultrasound 0.68 (0.51-0.8 at 95% CI), mammography 0.57 (0.36-0.72 at 95% CI) and RM 0.51 (0.29-0.68 at 95% CI) with respect to pathological anatomy. The mean tumor size of the surgical specimen was 16.1 mm. Mean of tumor size by physical examination was 12.1 mm (P<0.05), by 14 mm US (P<0.05), by mammography of 14.3 (P<0.05) and by MRI of 22.53 mm (P>0.05).

CONCLUSIONS

Ultrasonography is the best predictor of tumor size in breast cancer, compared with clinical examination, mammography, and resonance. Our work could help the decision-making process such as the type of conservative surgery, the possible need for oncoplastic surgery or the decision to start treatment with neoadjuvant therapy, in patients with unifocal tumors.

Relevance of breast MRI in determining the size and focality of invasive breast cancer treated by mastectomy: a prospective study

Background

The aim of this study was the evaluation of breast MRI in determining the size and focality of invasive non-metastatic breast cancers.

Methods

The prospective, single-centre study conducted in 2015 compared preoperative MRI with histological analysis of mastectomy.

Results

One hundred one mastectomies from 98 patients were extensively analysed. The rates of false-positive and false-negative MRI were 2 and 4% respectively. The sensitivity of breast MRI was 84.7% for the detection of all invasive foci, 69% for single foci and 65.7% for multiple foci. In the evaluation of tumour size, the Spearman rank correlation coefficient r between the sizes obtained by MRI and histology was 0.62. The MRI-based prediction of a complete response to neoadjuvant chemotherapy was 75%.

Discussion

MRI exhibits high sensitivity in the detection of invasive breast cancers. False positives were linked to the inflammatory nature of the tumour bed. False negatives were associated with small or low-grade tumours and their retro-areolar location. The size of T1 tumours was overestimated by an average of 7%, but MRI was the most efficient procedure. The sensitivity of MRI for the diagnosis of unifocal tumours was higher than that for multifocal sites. Our study confirmed the positive contribution of preoperative MRI for invasive lobular carcinomas and complete response predictions after neoadjuvant chemotherapy.

Preoperative prediction of the size of pure ductal carcinoma in situ using three imaging modalities as compared to histopathological size: does magnetic resonance imaging add value?

PURPOSE

The purpose of this study was to evaluate whether magnetic resonance imaging (MRI) and ultrasonography add value to traditional mammography in an Asian population with ductal carcinoma in situ (DCIS).

METHODS

Data of 244 patients with pure DCIS treated at Severance Hospital between 2013 and 2015 were analyzed retrospectively. Data extracted included age, preoperative diagnosis, tumor size on preoperative imaging studies, and final histopathological tumor type and size, including hormone receptor status. The extent of correlation between imaging and histopathological tumor sizes was evaluated using a variety of methods, including Bland-Altman analysis.

RESULTS

The mean patient age was 52.39 years (SD = 10.31). The mean measurements of the tumor on preoperative ultrasonography, mammography, MRI, and histopathology were 1.80 (SD = 1.23) cm, 2.97 (SD = 1.92) cm, 2.53(SD = 1.84) cm, and 1.88 (SD = 1.36) cm, respectively. The mean differences in tumor size between ultrasonography, mammography, and MRI compared with histopathology were -0.09 (SD = 1.39), 1.09 (SD = 1.89), and 0.65 (SD = 1.78), respectively. The correlation between the sizes was significant with r values for ultrasonography, mammography, and MRI of 0.447 (SE = 0.061), 0.375 (SE = 0.042), and 0.409 (SE = 0.043), respectively. Mammography and MRI estimated tumor size significantly better for patients older than 50 years (p = 0.045 and <0.001, respectively). Mammography also provided good estimation for patients with a body mass index under 25 (p = 0.041).

CONCLUSION

MRI is better at estimation of histopathological DCIS size compared with mammography. However, ultrasonography had better estimation compared with MRI and mammography, probably owing to the high breast density in this population.

2-D and 3-D Ultrasound for Tumor Volume Analysis: A Prospective Study

Ultrasound (US) allows real-time tumor assessment. We evaluated the volumetric limits of 2-D and 3-D US, compared with magnetic resonance imaging (MRI), with a prospective institutional review board-approved clinical evaluation of US-to-MRI volumetric correlation. US images of pre- and post-neoadjuvant breast cancers were obtained. Volume discrepancy was evaluated with the non-parametric Wilcoxon signed-rank test. Expected inter-observer variability <14% was evaluated as relative paired difference (RPD); clinical relevance was gauged with the volumetric standard error of the mean (SEM). For 42 patients, 133 of 170 US examinations were evaluable. For tumors ≤20 cm³, both highly correlated to MRI with RPD within inter-observer variability and Pearson's correlation up to 0.86 (0.80 before and 0.86 after neoadjuvant chemotherapy, respectively). Lesions 20-40 cm³ had US-to-MRI discrepancy within inter-observer variability for 2-D (RPD: 13%), but not 3-D (RPD: 27%) US (SEM: 1.47 cm³ for 2-D, SEM: 2.28 cm³ for 3-D), suggesting clinical utility. Tumors >40 cm³ correlated poorly. Tumor volumes ≤20 cm³ exhibited a good correlation to MRI. Studies of clinical applications are warranted.

Detection and volume estimation of artificial hematomas in the subcutaneous fatty tissue: comparison of different MR sequences at 3.0 T

In legal medicine, reliable localization and analysis of hematomas in subcutaneous fatty tissue is required for forensic reconstruction. Due to the absence of ionizing radiation, magnetic resonance imaging (MRI) is particularly suited to examining living persons with forensically relevant injuries. However, there is limited experience regarding MRI signal properties of hemorrhage in soft tissue. The aim of this study was to evaluate MR sequences with respect to their ability to show high contrast between hematomas and subcutaneous fatty tissue as well as to reliably determine the volume of artificial hematomas. Porcine tissue models were prepared by injecting blood into the subcutaneous fatty tissue to create artificial hematomas. MR images were acquired at 3T and four blinded observers conducted manual segmentation of the hematomas. To assess segmentability, the agreement of measured volume with the known volume of injected blood was statistically analyzed. A physically motivated normalization taking into account partial volume effect was applied to the data to ensure comparable results among differently sized hematomas. The inversion recovery sequence exhibited the best segmentability rate, whereas the T1T2w turbo spin echo sequence showed the most accurate results regarding volume estimation. Both sequences led to reproducible volume estimations. This study demonstrates that MRI is a promising forensic tool to assess and visualize even very small amounts of blood in soft tissue. The presented results enable the improvement of protocols for detection and volume determination of hemorrhage in forensically relevant cases and also provide fundamental knowledge for future in-vivo examinations.

Synergy in combining findings from mammography and ultrasonography in detecting malignancy in women with higher density breasts and lesions over 2 cm in Albania

AIM OF THE STUDY

To provide evidence of the synergy of combining findings from mammography (MM) and ultrasonography (US) in detecting malignancy in women with high-density breasts.

MATERIAL AND METHODS

A total of 245 women were screened for breast cancer using both mammography and ultrasonography at the American Hospital in Tirana during 2013-2014. The data was used to identify possible benefits in detecting malignancy, by combining the findings of MM and US and confirming them with those of the biopsy. Data on age, breast density, BI-RADS classification, and biopsy confirmations were collected and analysed.

RESULTS

Out of the 245 women, 36 biopsies were taken (17 for women classified BI-RADS 4 and 5; 19 for women with BI-RADS 3 that had grown in size from the previous examination). The accuracy in detecting malignancy for low-density-breast women was 90% for MM, 70% for US, and 90% for combined. For high-density breasts, the accuracy was 65% for MM, 79% for US, and 82% for combined findings. Multivariate analysis indicates that high-density-breast women who have a malignant finding in at least one of the examinations (MM or US) are 24 times more likely (p = 0.039) to have a positive finding in biopsy for malignancy. The odds increased 32 times for lesions over 2 cm (p = 0.056).

CONCLUSIONS

Our study results indicate additional benefits of combining findings from MM and US for high-density-breast women. Further study is warranted in a larger population and for different kinds of cancer.

Cancer Measurement at Ultrasound: State of the Art

Reliable and reproducible tumor measurement is fundamental in the oncologic decision making. In this article, we first highlight the importance of a precise tumor measurement, reviewing the correct modality of measuring tumor lesions at ultrasound. Then we analyze the measurement discrepancies between ultrasound and pathology as well as the discrepancies reported between ultrasound and other imaging modalities. Thereafter, basing on the existent literature and on our experience, we discuss the factors influencing the tumor size measurements at ultrasound. Finally, we illustrate the current strategies to improve the effectiveness of cancer lesions measurement.