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

Integrating machine learning models with cross-validation and bootstrapping for evaluating groundwater quality in Kanchanaburi province, Thailand

Exploring the potential of new models for mapping groundwater quality presents a major challenge in water resource management, particularly in Kanchanaburi Province, Thailand, where groundwater faces contamination risks. This study aimed to explore the applicability of random forest (RF) and artificial neural networks (ANN) models to predict groundwater quality. Particularly, these two models were integrated into cross-validation (CV) and bootstrapping (B) techniques to build predictive models, including RF-CV, RF-B, ANN-CV, and ANN-B. Entropy groundwater quality index (EWQI) was converted to normalized EWQI which was then classified into five levels from very poor to very good. A total of twelve physicochemical parameters from 180 groundwater wells, including potassium, sodium, calcium, magnesium, chloride, sulfate, bicarbonate, nitrate, pH, electrical conductivity, total dissolved solids, and total hardness, were investigated to decipher groundwater quality in the eastern part of Kanchanaburi Province, Thailand. Our results indicated that groundwater quality in the study area was primarily polluted by calcium, magnesium, and bicarbonate and that the RF-CV model (RMSE = 0.06, R2 = 0.87, MAE = 0.04) outperformed the RF-B (RMSE = 0.07, R2 = 0.80, MAE = 0.04), ANN-CV (RMSE = 0.09, R2 = 0.70, MAE = 0.06), and ANN-B (RMSE = 0.10, R2 = 0.67, MAE = 0.06). Our findings highlight the superiority of the RF models over the ANN models based on the CV and B techniques. In addition, the role of groundwater parameters to the normalized EWQI in various machine learning models was found. The groundwater quality map created by the RF-CV model can be applied to orient groundwater use.

ACR Appropriateness Criteria® Imaging of Invasive Breast Cancer

As the proportion of women diagnosed with invasive breast cancer increases, the role of imaging for staging and surveillance purposes should be determined based on evidence-based guidelines. It is important to understand the indications for extent of disease evaluation and staging, as unnecessary imaging can delay care and even result in adverse outcomes. In asymptomatic patients that received treatment for curative intent, there is no role for imaging to screen for distant recurrence. Routine surveillance with an annual 2-D mammogram and/or tomosynthesis is recommended to detect an in-breast recurrence or a new primary breast cancer in women with a history of breast cancer, and MRI is increasingly used as an additional screening tool in this population, especially in women with dense breasts. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Discrepancy between Tumor Size Assessed by Full-Field Digital Mammography or Ultrasonography (cT) and Pathology (pT) in a Multicenter Series of Breast Metaplastic Carcinoma Patients

Metaplastic breast cancer (BC-Mp) presents diagnostic and therapeutic complexities, with scant literature available. Correct assessment of tumor size by ultrasound (US) and full-field digital mammography (FFDM) is crucial for treatment planning.

METHODS

A retrospective cohort study was conducted on databases encompassing records of BC patients (2012-2022) at the National Research Institutes of Oncology (Warsaw, Gliwice and Krakow Branches). Inclusion criteria comprised confirmed diagnosis in postsurgical pathology reports with tumor size details (pT) and availability of tumor size from preoperative US and/or FFDM. Patients subjected to neoadjuvant systemic treatment were excluded. Demographics and clinicopathological data were gathered.

RESULTS

Forty-five females were included. A total of 86.7% were triple-negative. The median age was 66 years (range: 33-89). The median pT was 41.63 mm (6-130), and eight patients were N-positive. Median tumor size assessed by US and FFDM was 31.81 mm (9-100) and 34.14 mm (0-120), respectively. Neither technique demonstrated superiority (p > 0.05), but they both underestimated the tumor size (p = 0.002 for US and p = 0.018 for FFDM). Smaller tumors (pT1-2) were statistically more accurately assessed by any technique (p < 0.001). Only pT correlated with overall survival.

CONCLUSION

The risk of underestimation in tumor size assessment with US and FFDM has to be taken into consideration while planning surgical procedures for BC-Mp.

An Optical Sensory System for Assessment of Residual Cancer Burden in Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy

Breast cancer patients undergoing neoadjuvant chemotherapy (NAC) require precise and accurate evaluation of treatment response. Residual cancer burden (RCB) is a prognostic tool widely used to estimate survival outcomes in breast cancer. In this study, we introduced a machine-learning-based optical biosensor called the Opti-scan probe to assess residual cancer burden in breast cancer patients undergoing NAC. The Opti-scan probe data were acquired from 15 patients (mean age: 61.8 years) before and after each cycle of NAC. Using regression analysis with k-fold cross-validation, we calculated the optical properties of healthy and unhealthy breast tissues. The ML predictive model was trained on the optical parameter values and breast cancer imaging features obtained from the Opti-scan probe data to calculate RCB values. The results show that the ML model achieved a high accuracy of 0.98 in predicting RCB number/class based on the changes in optical properties measured by the Opti-scan probe. These findings suggest that our ML-based Opti-scan probe has considerable potential as a valuable tool for the assessment of breast cancer response after NAC and to guide treatment decisions. Therefore, it could be a promising, non-invasive, and accurate method for monitoring breast cancer patient's response to NAC.

Pathologic Tumor Size versus Mammography, Sonography, and MRI in Breast Cancer Based on Pathologic Subtypes

INTRODUCTION

The standard of care for imaging of breast pathology has historically been mammography and sonography. MRI is a modern adjunct in the surgeon's toolkit. We looked to examine the differences in imaging modalities and their ability to predict the size in relation to the pathologic size after excision with focus on pathologic subtypes.

METHODS

We analyzed patient records across a 4-year period from 2017 to 2021 who were treated surgically for breast cancer at our facility. We used a retrospective chart review to collect measurements that were recorded of the tumors by the radiologist for available mammography, ultrasound, and MRI which were compared to pathology report measurements of the final specimens. We subdivided the results by pathologic subtypes including invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), and ductal carcinoma in situ (DCIS).

RESULTS

658 total patients met criteria for analysis. Mammography overestimated specimens with DCIS by 1.93 mm (P = .15), US underestimated by .56 (.55), and MRI overestimated by 5.77 mm (P < .01). There was no statistically significant difference in any modalities with IDC. With specimens of ILC, all 3 imaging modalities underestimated tumor size, with only US being significant.

DISCUSSION

Mammography and MRI consistently overestimated tumor size with the exception of ILC while US underestimated tumor size on all pathologic subtypes. MRI significantly overestimated tumor size in DCIS by 5.77 mm. Mammography was the most accurate imaging modality for all pathologic subtypes and never had a statistically significant difference from actual tumor size.

Applying Explainable Machine Learning Models for Detection of Breast Cancer Lymph Node Metastasis in Patients Eligible for Neoadjuvant Treatment

BACKGROUND

Due to recent changes in breast cancer treatment strategy, significantly more patients are treated with neoadjuvant systemic therapy (NST). Radiological methods do not precisely determine axillary lymph node status, with up to 30% of patients being misdiagnosed. Hence, supplementary methods for lymph node status assessment are needed. This study aimed to apply and evaluate machine learning models on clinicopathological data, with a focus on patients meeting NST criteria, for lymph node metastasis prediction.

METHODS

From the total breast cancer patient data (n = 8381), 719 patients were identified as eligible for NST. Machine learning models were applied for the NST-criteria group and the total study population. Model explainability was obtained by calculating Shapley values.

RESULTS

In the NST-criteria group, random forest achieved the highest performance (AUC: 0.793 [0.713, 0.865]), while in the total study population, XGBoost performed the best (AUC: 0.762 [0.726, 0.795]). Shapley values identified tumor size, Ki-67, and patient age as the most important predictors.

CONCLUSION

Tree-based models achieve a good performance in assessing lymph node status. Such models can lead to more accurate disease stage prediction and consecutively better treatment selection, especially for NST patients where radiological and clinical findings are often the only way of lymph node assessment.

Role of breast ultrasonography in predicting accurate tumor dimensions in correlation with histopathology and its impact on staging of breast carcinoma

BACKGROUND AND OBJECTIVES

Estimation of the preoperative size of a breast tumor is of primary importance in deciding the treatment modality. Hence, clinical examination of the lump aided by the imaging is necessary. Our study is instrumental in correlating the size of breast tumor by high-resolution ultrasonography (USG) with the morphological size and also in comparing clinical staging of breast carcinoma against the gold standard pathological staging.

METHODS

It is a cross-sectional study of correlating the size of tumor on USG with the morphological size of biopsy proven invasive ductal carcinoma when received after excision. The size of the tumor was measured grossly and was compared with the USG measurements and palpatory findings.

RESULTS

Seventy percent of cases had good correlation between the USG and morphological size. In 50% of cases, the size on physical examination corroborated with the USG findings and only in 40% of the cases size on physical examination matched with morphological findings. In 65% of cases, the clinical staging of the breast carcinoma matched with the pathological staging. Our study reflected that USG promised to be the most useful radiological tool in predicting the accurate preoperative size of the tumor.

INTERPRETATION AND CONCLUSION

We observed that USG has proved to be a very useful conjunct to clinical examination as only palpation was not found to be very accurate in predicting the actual tumor size. It proved to be safer and cheaper and effectively instrumental in meting out an effective management at pre- and postoperative level to the patient.

The Effect of Black Cohosh on Ki67 expression and Tumor Volume: A Pilot Study of Ductal Carcinoma in Situ Patients

BACKGROUND

Black cohosh (BC) (Cimicifuga racemosa) may prevent and treat breast cancer through anti-proliferative, pro-apoptotic, anti-estrogenic, and anti-inflammatory effects. This study sought to evaluate the effect of BC on tumor cellular proliferation, measured by Ki67 expression, in a pre-operative window trial of ductal carcinoma in situ (DCIS) patients.

METHODS

Patients were treated pre-operatively for 2 to 6 weeks with BC extract. Eligible subjects were those who had DCIS on core biopsy. Ki67 was measured using automated quantitative immunofluorescence (AQUA) pre/post-operatively. Ki67, tumor volume, and hormone changes were assessed with 2-sided Wilcoxon signed-rank tests, α = .05.

RESULTS

Thirty-one patients were treated for an average of 24.5 days (median 25; range 15-36). Ki67 decreased non-significantly (n = 26; P = .20; median pre-treatment 1280, post-treatment 859; range pre-treatment 175-7438, post-treatment 162-3370). Tumor volume, estradiol, and FSH did not change significantly. No grade 3 or 4 adverse events were reported.

CONCLUSIONS

BC use showed no significant impact on cellular proliferation, tumor volume, or invasive disease upgrade rates in DCIS patients. It was well-tolerated, with no observed significant toxicities. Further study is needed to elucidate BC's role in breast cancer treatment and prevention.ClinicalTrials.gov Identifier: NCT01628536https://clinicaltrials.gov/ct2/show/NCT01628536.

Multimodality imaging in lobular breast cancer: Differences in mammography, ultrasound, and MRI in the assessment of local tumor extent and correlation with molecular characteristics

Introduction

Invasive lobular breast cancer (ILC) is a diagnostic challenge due to the diversity of morphological features. The objective of the study was to investigate the presentation and local extent of ILC using various imaging techniques and to assess the correlation between imaging and molecular profile.

Materials and methods

We reviewed 162 consecutive patients with ILC found on vacuum-assisted biopsy, who underwent evaluation of the lesion morphology and extent using ultrasound (US), mammography (MMG), and magnetic resonance imaging (MRI). Radiographic features were compared with ILC intrinsic subtype based on the expression of Ki-67 and estrogen, progesterone, and HER2 receptors.

Results

A total of 113 mass lesions and 49 non-mass enhancements (NMEs) were found in MRI. Masses were typically irregular and spiculated, showing heterogeneous contrast enhancement, diffusion restriction, and type III enhancement curve. NMEs presented mainly as the area of focal or multiregional distribution with heterogeneous or clumped contrast enhancement, diffusion restriction, and type III enhancement curve. Lesion extent significantly varied between MRI and MMG/ultrasonography (USG) (P < 0.001) but did not differ between MGF and ultrasonography (USG). The larger the ILC, the higher the disproportion when lesion extent in MRI was compared with MMG (P < 0.001) and ultrasonography (USG) (P < 0.001). In the study group, there were 97 cases of luminal A subtype (59.9%), 54 cases of luminal B HER2− (33.3%), nine cases of luminal B HER2+ (5.5%), and two cases of triple negative (1.2%). The HER2 type was not found in the study group. We did not observe any significant correlation between molecular profile and imaging.

Conclusion

MRI is the most effective technique for the assessment of ILC local extent, which is important for optimal treatment planning. Further studies are needed to investigate if the intrinsic subtype of ILC can be predicted by imaging features on MRI.

Interactive exploration of a global clinical network from a large breast cancer cohort

Despite unprecedented amount of information now available in medical records, health data remain underexploited due to their heterogeneity and complexity. Simple charts and hypothesis-driven statistics can no longer apprehend the content of information-rich clinical data. There is, therefore, a clear need for powerful interactive visualization tools enabling medical practitioners to perceive the patterns and insights gained by state-of-the-art machine learning algorithms. Here, we report an interactive graphical interface for use as the front end of a machine learning causal inference server (MIIC), to facilitate the visualization and comprehension by clinicians of relationships between clinically relevant variables. The widespread use of such tools, facilitating the interactive exploration of datasets, is crucial both for data visualization and for the generation of research hypotheses. We demonstrate the utility of the MIIC interactive interface, by exploring the clinical network of a large cohort of breast cancer patients treated with neoadjuvant chemotherapy (NAC). This example highlights, in particular, the direct and indirect links between post-NAC clinical responses and patient survival. The MIIC interactive graphical interface has the potential to help clinicians identify actionable nodes and edges in clinical networks, thereby ultimately improving the patient care pathway.

A comprehensive comparison of circulating tumor cells and breast imaging modalities as screening tools for breast cancer in Chinese women

Background

Circulating tumor cells (CTCs) have been recognized as a sensitive biomarker for breast cancer (BC). This study aimed to comprehensively compare CTC with imaging modalities, including ultrasonography, mammography, and contrast-enhanced magnetic resonance imaging (MRI) in screening for BC in Chinese women.

Methods

Three hundred forty-three participants were enrolled in this study, including 102 treatment-naive BC patients, 177 with breast benign diseases (BBD) and 64 healthy female patients. All participants underwent CTC testing and at least one of the following examinations, ultrasonography, mammography, and MRI at the Second Affiliated Hospital of Zhejiang University between December 2017 and November 2020. CTCs were quantitatively assessed using cell counting (CTC detection rate/counts) and categorically examined using a cutoff value (CTC classification). The diagnostic power of CTC tests and imaging modalities, including accuracy and capability to predict clinicopathological characteristics of BC, were evaluated and compared.

Results

CTC classification with a cutoff value of 2 showed a “good” diagnostic accuracy of 0.889 for early- to mid-stage BC comparable to breast imaging modalities using Breast Imaging-Reporting and Data System (BI-RADS). MRI demonstrated the highest sensitivity of 0.872 for BC, and CTC classification had the highest specificity of 0.938. A relatively low sensitivity was found for mammography in this cohort of patients. Successful detection of BC by CTC detection rate/counts, but not CTC classification, correlated with two important clinicopathological features, American Joint Committee on Cancer (AJCC) stage and tumor-node-metastasis (TNM) stage. The detection power of certain imaging modalities was also associated with AJCC stage (ultrasonography, p = 0.0438 and MRI, p = 0.0422) and lymph node metastasis (ultrasonography, 0.0157). There were clear correlations between CTC tests (counts or classification) and imaging BI-RADS scoring system in detecting positive BC cases (p < 0.05). Further correlation analysis suggested that CTC quantity, but not CTC classification, had the capability to predict clinicopathological traits of BC that were identified by ultrasonography.

Conclusions

CTC tests have a diagnostic potency comparable to breast imaging modalities, and may be used as an alternative screening tool for BC.

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.

Consistency Analysis of CTLM Imaging and Mammography in the Diagnosis of Breast Tumor Lesions

Objective. To analyze the consistency of preoperative CTLM imaging in the diagnosis of breast cancer lesions and postoperative pathological examination. Methods. The clinical data of 225 patients with breast tumor in our breast surgery department were collected. All patients underwent mammography, CTLM, and pathological examination. To analyze the image characteristics of breast CTLM imaging, calculate the diagnostic efficacy of CTLM imaging for breast tumors, and compare the image characteristics of CTLM imaging for benign and malignant tumors. Results. (1) Postoperative pathological examination showed that 136 cases (60.44%) of lesions were benign tumors, and 89 cases (39.56%) were malignant tumors. (2) The “spokes distribution” of normal breast CTLM images was interrupted. In the 3D reconstructed images, the morphology of the abnormal angiogenesis area is mostly irregular nonbanded structure, which is manifested as slab structure, spindle structure, spherical structure, diverticulum structure, inverted conical structure, rings structure, branched structure, and dumbbell structure. (3) The detection rate of breast tumor by CTLM imaging was 84.44%. The specificity and coincidence rate of CTLM imaging were higher than that of mammography (P < 0.05). (4) The features of CTLM imaging images of breast malignant tumors are mostly bright white locally, with irregular edges and obvious attenuation of laser signal, and the reconstructed shape of 3D images is mostly like a slab structure. Conclusion. CTLM imaging can provide related information of neovascularization in breast cancer lesions, which is basically consistent with pathologically confirmed lesions.

Adequate Assessment Can Affect the Management of Breast Cancer in Geriatric Population

Breast cancer (BC) risk increases with age; about a third of patients are diagnosed in age older than 65. Treatment of this age group remains controversial, leading to inferior outcomes with lower survival rates than younger patients. We aimed to evaluate performance status tools as well as the outcome of management of breast cancer in the geriatric population. We have conducted a retrospective database analysis looking into the management of breast cancer patients older than 65 years old presenting to our unit during the period between June 2015 and June 2019. All patients had triple assessment as well as multimodality performance status assessment with their treatment modalities, and outcomes are recorded and assessed. We have included 578 patients, 0.8% male and 99.2% female, and our patients' mean age was 71 years. Most of our patients scored one or two on the WHO/ECOG performance status score and Clinical Frailty Score, as well as ASA-PS score. 3.2% had no treatment, 4.3% had endocrine therapy only, 0.5% had primary endocrine therapy followed by surgery, and 92.3% underwent surgery with 4.1% complication rate. Patients who underwent breast-conserving surgery had adjuvant breast radiotherapy, and 23.7% had adjuvant chest wall radiotherapy, 78.8% had adjuvant endocrine treatment, and 4.8% had adjuvant chemotherapy out of which 30.7% had adjuvant chemotherapy and Herceptin. Objective assessment tools should be used for patients older than 65 years diagnosed with primary breast cancer to be able to scarify patients' individualised treatment options to reach the optimum outcome.

Clinical correlates of circulating cell-free DNA tumor fraction

BACKGROUND

Oncology applications of cell-free DNA analysis are often limited by the amount of circulating tumor DNA and the fraction of cell-free DNA derived from tumor cells in a blood sample. This circulating tumor fraction varies widely between individuals and cancer types. Clinical factors that influence tumor fraction have not been completely elucidated.

METHODS AND FINDINGS

Circulating tumor fraction was determined for breast, lung, and colorectal cancer participant samples in the first substudy of the Circulating Cell-free Genome Atlas study (CCGA; NCT02889978; multi-cancer early detection test development) and was related to tumor and patient characteristics. Linear models were created to determine the influence of tumor size combined with mitotic or metabolic activity (as tumor mitotic volume or excessive lesion glycolysis, respectively), histologic type, histologic grade, and lymph node status on tumor fraction. For breast and lung cancer, tumor mitotic volume and excessive lesion glycolysis (primary lesion volume scaled by percentage positive for Ki-67 or PET standardized uptake value minus 1.0, respectively) were the only statistically significant covariates. For colorectal cancer, the surface area of tumors invading beyond the subserosa was the only significant covariate. The models were validated with cases from the second CCGA substudy and show that these clinical correlates of circulating tumor fraction can predict and explain the performance of a multi-cancer early detection test.

CONCLUSIONS

Prognostic clinical variables, including mitotic or metabolic activity and depth of invasion, were identified as correlates of circulating tumor DNA by linear models that relate clinical covariates to tumor fraction. The identified correlates indicate that faster growing tumors have higher tumor fractions. Early cancer detection from assays that analyze cell-free DNA is determined by circulating tumor fraction. Results support that early detection is particularly sensitive for faster growing, aggressive tumors with high mortality, many of which have no available screening today.

Quality of Anatomic Staging of Breast Carcinoma in Hospitals in the United States, With Focus on Measurement of Tumor Dimension

OBJECTIVES

We investigated the accuracy of clinical breast carcinoma anatomic staging and the greatest tumor dimension measurements.

METHODS

We compared clinical stage and greatest dimension values with the pathologic reference standard values using 57,747 cases from the 2016 US National Cancer Institute Surveillance, Epidemiology, and End Results program who were treated by surgical resection without prior neoadjuvant therapy.

RESULTS

Agreement for clinical vs pathologic anatomic TNM group stage, overall, is 74.3% ± 0.4%. Lymph node N staging overall agrees very well (85.1% ± 0.4%). Based on tumor dimension and location, T staging has an agreement of only 64.2% ± 0.4%, worsening to 55% without carcinoma in situ (Tis) cases. In approximately 25% of cases, pathologic T stage is higher than clinical T stage. The mean difference in the greatest dimension is 1.36 ± 9.59 mm with pathologic values being generally larger than clinical values; pathologic and clinical measurements correlate well. T-stage disagreement is associated with histology, tumor grade, tumor size, N stage, patient age, periodic biases in tumor size measurements, and overuse of family T-stage categories. Pathologic measurement biases include rounding and specimen-slicing intervals.

CONCLUSIONS

Clinical and pathologic T-staging values agree only moderately. Pathologists face challenges in increasing the precision of gross tumor measurements, with the goal of improving the accuracy of clinical T staging and measurement.

Modeling viscous damping in actuated breast tissue to provide diagnostic insight for breast cancer: A proof-of-concept analysis

PURPOSE

This study develops a viscous damping model (VDM) based on Rayleigh Damping (RD) with potential use in low cost, non-invasive breast cancer diagnostics using Digital Image Elasto Tomography (DIET).

METHODS

A clinical trial involving 13 subjects, each with a tumor in one breast, resulted in 13 cancerous and 13 healthy breasts. Displacement data following actuator induced steady state vibration in the breast tissue were captured using the DIET system. Over 14 000 reference points on the breast surface were split into four segments and viscous damping constant calculated for each reference point. The VDM was fit to median-filtered data for each breast segment and VDM coefficients compared within each breast. One model coefficient, relating to stiffness, was hypothesized to differ in breast segments containing a tumor. Comparison of " b " coefficients in different breast segments using percentage tolerances provided an unbiased, generalizable diagnostic method. Bootstrapping with replacement was used to upsample the data and create smooth receiver operator characteristic (ROC) curves. A total of 12 breast segmentation configurations were used to demonstrate the robustness of the method.

RESULTS

Fitting the VDM to median-filtered data gave consistent results for one VDM coefficient (" a ") across all breasts. The second VDM coefficient (" b ") showed diagnostic potential with breast segments having consistent coefficients in healthy breasts. In cancerous breasts " b " coefficients were found to be statistically different in segments containing and adjacent to the tumor compared with the segment furthest from the tumor with p < 0.02 using the Student t-Test. Large discrepancies in " b " coefficients were found to be indicative of a tumor with a 14.5% tolerance resulting in sensitivity and specificity of 76.9%. The optimal breast configuration resulted in an area under the ROC curve (AUC) of 0.81 with sensitivity and specificity at 77% and 72%, respectively.

CONCLUSION

This VDM method enables a computationally simple diagnostic technique using DIET for comfortable breast screening for women of all ages. Regular screening potential allows for tolerance alteration based on age, prior subject-specific results, and other risk factors to manage false positives, reducing psychological harm while optimizing early detection for successful treatment and decreased mortality.

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.

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.

Induced volatolomics of pathologies

Volatolomics allows us to elucidate cell metabolic processes in real time. In particular, a volatile organic compound (VOC) excreted from our bodies may be specific for a certain disease, such that measuring this VOC may afford a simple, fast, accessible and safe diagnostic approach. Yet, finding the optimal endogenous volatile marker specific to a pathology is non-trivial because of interlaboratory disparities in sample preparation and analysis, as well as high interindividual variability. These limit the sensitivity and specificity of volatolomics and its applications in biological and clinical fields but have motivated the development of induced volatolomics. This approach aims to overcome issues by measuring VOCs that result not from an endogenous metabolite but, rather, from the pathogen-specific or metabolic-specific enzymatic metabolism of an exogenous biological or chemical probe. In this Review, we introduce volatile-compound-based probes and discuss how they can be exploited to detect and discriminate pathogenic infections, to assess organ function and to diagnose and monitor cancers in real time. We focus on cases in which labelled probes have informed us about metabolic processes and consider the potential and drawbacks of the probes for clinical trials. Beyond diagnostics, VOC-based probes may also be effective tools to explore biological processes more generally.

Routine cavity shaves following breast conserving surgery; friend or foe?

BACKGROUND

Radial margin status is considered one of the most important prognostic predictor for patients undergoing breast-conserving surgery (BCT), not only related to regional recurrence but also to 5y survival, especially in patients with invasive disease.

AIM

While our primary aim was to evaluate whether doing routine radial cavity shaves following at the time of primary conservative breast surgery will decrease the need for a second operation or not, our secondary aim was to assess time added to the operation to resect and mark the radial shaves, as well as patients' satisfaction with the results.

MATERIAL AND METHODS

We have conducted a case series prospective analysis, including158 patients who underwent breast-conserving surgery looking into the histological status of resection margins and radial shaves, added time taken to take and mark the shaves as well as patients' satisfaction.

RESULTS

158 female breast cancer patients have been included in our analysis, the mean age was 56 years; total number of lesions was 160. While 89.3% of lesions were palpable, 10.6% were not requiring wire-guided localisation. Mean tumour size was 24 mm SD 7, final histology revealed that 86.8% lesion was invasive ductal carcinoma, 5.6% invasive lobular carcinoma, 1.2% medullary carcinoma. 12.4% had invasive disease as well as DCIS, and 1.8% had DCIS only with no invasive disease. Mean preoperative breast volume was 723 ml, Mean wide local excision specimen weight was 73 g, and mean shave weight was 1.6 g. Total number of radial margins was 640, 81.8% was clear, 14.6% was close, and 3.4% was involved. Total number of shaves was 640 out of which 98.7% was clear 0.7% was close and 0.4% was involved. Out of the 160 lesions, 3.7% required a second procedure to clear margins, out of which 2.5% had re-excision for close or involved single shaves each while 1.2% had mastectomy due to close or involved two shaves each. Average time utilised in resection of radial shaves and marking was 7 min 0.6% of patients developed a haematoma, 1.8% had a Seroma, and 1.2% had wound infection. Mean hospital stay was 1day SD 1.

CONCLUSION

Routine radial cavity shaves not only ensure microscopic clearance, reduce the need for re-excision with no significant added operating time but also has no impact on patients' satisfaction.

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.

Comparison of Mammography and Ultrasonography for Tumor Size of DCIS of Breast Cancer

OBJECTIVE

Accurate assessment of breast tumor size preoperatively is important for the initial decision-making in surgical approach. Therefore, we aimed to compare efficacy of mammography and ultrasonography in ductal carcinoma in situ (DCIS) of breast cancer.

METHODS

Preoperative mammography and ultrasonography were performed on 104 women with DCIS of breast cancer. We compared the accuracy of each of the imaging modalities with pathological size by Pearson correlation. For each modality, it was considered concordant if the difference between imaging assessment and pathological measurement is less than 0.5cm.

RESULTS

At pathological examination tumor size ranged from 0.4cm to 7.2cm in largest diameter. For mammographically determined size versus pathological size, correlation coefficient of r was 0.786 and for ultrasonography it was 0.651. Grouped by breast composition, in almost entirely fatty and scattered areas of fibroglandular dense breast, correlation coefficient of r was 0.790 for mammography and 0.678 for ultrasonography; in heterogeneously dense and extremely dense breast, correlation coefficient of r was 0.770 for mammography and 0.548 for ultrasonography. In microcalcification positive group, coeffient of r was 0.772 for mammography and 0.570 for ultrasonography. In microcalcification negative group, coeffient of r was 0.806 for mammography and 0.783 for ultrasonography.

CONCLUSION

Mammography was more accurate than ultrasonography in measuring the largest cancer diameter in DCIS of breast cancer. The correlation coefficient improved in the group of almost entirely fatty/ scattered areas of fibroglandular dense breast or in microcalcification negative group.

A Mathematical Model to Predict Diagnostic Periods for Secondary Distant Metastases in Patients with ER/PR/HER2/Ki-67 Subtypes of Breast Cancer

Previously, a consolidated mathematical model of primary tumor (PT) growth and secondary distant metastasis (sdMTS) growth in breast cancer (BC) (CoMPaS) was presented. The aim was to detect the diagnostic periods for visible sdMTS via CoMPaS in patients with different subtypes ER/PR/HER2/Ki-67 (Estrogen Receptor/Progesterone Receptor/Human Epidermal growth factor Receptor 2/Ki-67 marker) of breast cancer. CoMPaS is based on an exponential growth model and complementing formulas, and the model corresponds to the tumor-node-metastasis (TNM) staging system and BC subtypes (ER/PR/HER2/Ki-67). The CoMPaS model reflects (1) the subtypes of BC, such as ER/PR/HER2/Ki-67, and (2) the growth processes of the PT and sdMTSs in BC patients without or with lymph node metastases (MTSs) in accordance with the eighth edition American Joint Committee on Cancer prognostic staging system for breast cancer. CoMPaS correctly describes the growth of the PT in the ER/PR/HER2/Ki-67 subtypes of BC patients and helps to calculate the different diagnostic periods, depending on the tumor volume doubling time of sdMTS, when sdMTSs might appear. CoMPaS and the corresponding software tool can help (1) to start the early treatment of small sdMTSs in BC patients with different tumor subtypes (ER/PR/HER2/Ki-67), and (2) to consider the patient almost healthy if sdMTSs do not appear during the different diagnostic periods.

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.

Defining clinicopathological and radiological features of breast cancer in women under the age of 35: an epidemiological study

INTRODUCTION

Breast cancer is the most commonly diagnosed female cancer. Diagnosis in younger women (under 35 years) is different to their older counterparts, and mammography is not considered as sensitive in this cohort. Consequentially, younger patients may present later with more advanced disease.

METHODS

This is a retrospective analysis of a prospectively updated database containing consecutive patients who presented to the symptomatic breast unit of Galway University Hospital between 2009 and 2015. Patient clinicopathologic factors, clinical examination features, diagnostic radiological modalities and Bi-RADS score were all assessed. Data was analysed using Statistical Package for the Social Sciences version 25.

RESULTS

One thousand eight hundred thirty-six patients were diagnosed with breast cancer, and of these, 51 (2.8%) patients were < 35 years. Invasive ductal carcinoma made up 90% of diagnosis, and 42% had an associated ductal carcinoma in situ. Fifty-four percent were high-grade tumours and 52% presented with stage III disease or greater. The main radiological tool used was ultrasound, which had a sensitivity of 87.50% (95% confidence interval [CI] 74.75 to 95.27%). Mammogram sensitivity was 86.84% (95% CI 71.91 to 95.59%). Magnetic resonance imaging was used in 29% of cases, with a sensitivity of 100.00% (95% CI 78.20 to 100.00%).

CONCLUSION

Females under 35 tend to be diagnosed with aggressive, advanced stage tumours. Ultrasound remains the radiological test of choice, although diagnosis using mammography demonstrated a relatively high sensitivity compared with previous reports. This study emphasises the varying epidemiology of breast cancer in younger patients and the potential role of mammography in making radiological diagnosis in those who are symptomatic.

Technical Factors Affecting Ultrasound Breast Tumor Size as Correlated with Pathological Type

Background and Objectives: Accurate breast tumor sizing is very important in treatment planning; as a result, ultrasound (US) plays an important role in diagnosing breast masses, due to its non-magnified image and its availability. The continuous change in the disease pathogenesis of breast cancer and tremendous advances in US imaging technology require the continuous evaluation of this imaging modality. In this study, our aim was to determine the accuracy of US in measuring the size of breast mass, and if there is an influence of the different pathological types on this accuracy. Materials and Methods: This study contained 66 specimens of breast masses that underwent surgical excision and pathological examination of the resected masses; the mean difference between the size taken by US and the size taken by pathology was calculated to the patients as a whole and for each tumor type in this study. Results: The result was that US underestimates the size of the tumor by 0.5 cm for all pathological types, and the US size is in agreement with the pathology size. Conclusions: US is an accurate method in measuring breast lesions with a degree of underestimation that may be related to many factors such as the tumor type, size, and margins. Complementary MRI is recommended in case of ILC and architectural distortion.

Invasive lobular breast cancer: A review of pathogenesis, diagnosis, management, and future directions of early stage disease

Invasive lobular carcinoma (ILC) is the second most common type of invasive breast cancer after invasive ductal carcinoma (IDC). Invasive lobular carcinoma has unique clinical, pathologic, and radiographic features which suggest that it is a distinct clinical entity; however, it is treated with the same treatment paradigms as IDC. Information regarding the specific treatment of ILC, including response to standard therapy, is sparse. Neoadjuvant treatment considerations are of great importance in this space as ILC is often found at a locally advanced stage. In this review, we summarize the classic features of ILC and the available data regarding efficacy of both endocrine therapy and chemotherapy in curative treatment of breast cancer.

Breast cancer research and treatment reconstruction of unilateral breast structure using three-dimensional ultrasound imaging to assess breast neoplasm

Purpose

To develop and evaluate the accuracy of a three-dimensional (3D) US method for assessing unilateral breast reconstruction and discuss the feasibility of breast ultrasound 3D reconstruction of the unilateral breast compared with 3D MRI.

Methods

Sixty-four breast lesions were collected for surgical resection. (1) MRI and US imaging were used to reconstruct the 3D models of the breast neoplasm. The diameters for maximum length, width, and depth of the negative tumor margins were used as the primary standards for comparison. (2) The measurement direction was determined by the largest gravity change between the two body positions. (3) The vertical distance from the midpoint of breast neoplasm to the ipsilateral nipple was calculated via MRI and US reconstruction.

Results

(1) Comparison of the measured size and histopathology of the breast neoplasm showed that US, MRI, and histopathology were highly correlated (p < 0.001). (2) When compared with the other two vertical directions, the direction with the largest gravity change had the greatest difference between MRI and US measurements. (3) The vertical distance from the breast neoplasm to the ipsilateral nipple and skin junction was significantly different (p > 0.05).

Conclusions

We have presented a novel US 3D reconstruction method for evaluating tumor size, which can provide a basis for investigated advanced visualization techniques for assessing breast tissue such as holographic presentation of 3D image data. These methods can provide physicians with a novel approach for making accurate surgical plans, for better communication with patients, and for more effective navigating throughout the operation.

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.

Pentameric last-digit preference and stage border avoidance in pathology measurement

AIMS

Cancer treatment relies on accurate staging, an essential aspect of which is determination of the size of a tumour. Measuring the size of a tumour in daily practice often proves problematic and results in rounding of values to approximate values. It has been shown that size values are most frequently reported with end digits of 0 or 5.

METHODS AND RESULTS

We sought to determine whether this observation holds true in our national cancer registry of breast and lung tumours. Data from patients with breast and lung cancer were retrieved from the Netherlands National Cancer Registry and analysed for tumour size. Whereas a preference for terminal digits of 0 or 5 (pentameric preference) was clearly present for lung cancer, critical pentameric values at stage boundaries were avoided in breast cancer.

CONCLUSIONS

In conclusion, pathologists adopt a practical approach to tumour size measurement by rounding values and avoiding stage border boundary values, thus circumventing potential difficulties in treatment decisions.