Structured illumination microscopy for cancer identification in diagnostic breast biopsies.

Breast cancer is the second most common cancer diagnosed in women in the US with almost 280,000 new cases anticipated in 2023. Currently, on-site pathology for location guidance is not available during the collection of breast biopsies or during surgical intervention procedures. This shortcoming contributes to repeat biopsy and re-excision procedures, increasing the cost and patient discomfort during the cancer management process. Both procedures could benefit from on-site feedback, but current clinical on-site evaluation techniques are not commonly used on breast tissue because they are destructive and inaccurate. Ex-vivo microscopy is an emerging field aimed at creating histology-analogous images from non- or minimally-processed tissues, and is a promising tool for addressing this pain point in clinical cancer management. We investigated the ability structured illumination microscopy (SIM) to generate images from freshly-obtained breast tissues for structure identification and cancer identification at a speed compatible with potential on-site clinical implementation. We imaged 47 biopsies from patients undergoing a guided breast biopsy procedure using a customized SIM system and a dual-color fluorescent hematoxylin & eosin (H&E) analog. These biopsies had an average size of 0.92 cm2 (minimum 0.1, maximum 4.2) and had an average imaging time of 7:29 (minimum 0:22, maximum 37:44). After imaging, breast biopsies were submitted for standard histopathological processing and review. A board-certified pathologist returned a binary diagnostic accuracy of 96% when compared to diagnoses from gold-standard histology slides, and key tissue features including stroma, vessels, ducts, and lobules were identified from the resulting images.

A meta-analysis of MRI radiomics-based diagnosis for BI-RADS 4 breast lesions.

OBJECTIVE: The aim of this study is to conduct a systematic evaluation of the diagnostic efficacy of Breast Imaging Reporting and Data System (BI-RADS) 4 benign and malignant breast lesions using magnetic resonance imaging (MRI) radiomics. METHODS: A systematic search identified relevant studies. Eligible studies were screened, assessed for quality, and analyzed for diagnostic accuracy. Subgroup and sensitivity analyses explored heterogeneity, while publication bias, clinical relevance and threshold effect were evaluated. RESULTS: This study analyzed a total of 11 studies involving 1,915 lesions in 1,893 patients with BI-RADS 4 classification. The results showed that the combined sensitivity and specificity of MRI radiomics for diagnosing BI-RADS 4 lesions were 0.88 (95% CI 0.83-0.92) and 0.79 (95% CI 0.72-0.84). The positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were 4.2 (95% CI 3.1-5.7), 0.15 (95% CI: 0.10-0.22), and 29.0 (95% CI 15-55). The summary receiver operating characteristic (SROC) analysis yielded an area under the curve (AUC) of 0.90 (95% CI 0.87-0.92), indicating good diagnostic performance. The study found no significant threshold effect or publication bias, and heterogeneity among studies was attributed to various factors like feature selection algorithm, radiomics algorithms, etc. Overall, the results suggest that MRI radiomics has the potential to improve the diagnostic accuracy of BI-RADS 4 lesions and enhance patient outcomes. CONCLUSION: MRI-based radiomics is highly effective in diagnosing BI-RADS 4 benign and malignant breast lesions, enabling improving patients' medical outcomes and quality of life.

Hyperspectral dark-field microscopy of human breast lumpectomy samples for tumor margin detection in breast-conserving surgery.

Significance: Hyperspectral dark-field microscopy (HSDFM) and data cube analysis algorithms demonstrate successful detection and classification of various tissue types, including carcinoma regions in human post-lumpectomy breast tissues excised during breast-conserving surgeries. Aim: We expand the application of HSDFM to the classification of tissue types and tumor subtypes in pre-histopathology human breast lumpectomy samples. Approach: Breast tissues excised during breast-conserving surgeries were imaged by the HSDFM and analyzed. The performance of the HSDFM is evaluated by comparing the backscattering intensity spectra of polystyrene microbead solutions with the Monte Carlo simulation of the experimental data. For classification algorithms, two analysis approaches, a supervised technique based on the spectral angle mapper (SAM) algorithm and an unsupervised technique based on the K-means algorithm are applied to classify various tissue types including carcinoma subtypes. In the supervised technique, the SAM algorithm with manually extracted endmembers guided by H&E annotations is used as reference spectra, allowing for segmentation maps with classified tissue types including carcinoma subtypes. Results: The manually extracted endmembers of known tissue types and their corresponding threshold spectral correlation angles for classification make a good reference library that validates endmembers computed by the unsupervised K-means algorithm. The unsupervised K-means algorithm, with no a priori information, produces abundance maps with dominant endmembers of various tissue types, including carcinoma subtypes of invasive ductal carcinoma and invasive mucinous carcinoma. The two carcinomas' unique endmembers produced by the two methods agree with each other within <2% residual error margin. Conclusions: Our report demonstrates a robust procedure for the validation of an unsupervised algorithm with the essential set of parameters based on the ground truth, histopathological information. We have demonstrated that a trained library of the histopathology-guided endmembers and associated threshold spectral correlation angles computed against well-defined reference data cubes serve such parameters. Two classification algorithms, supervised and unsupervised algorithms, are employed to identify regions with carcinoma subtypes of invasive ductal carcinoma and invasive mucinous carcinoma present in the tissues. The two carcinomas' unique endmembers used by the two methods agree to <2% residual error margin. This library of high quality and collected under an environment with no ambient background may be instrumental to develop or validate more advanced unsupervised data cube analysis algorithms, such as effective neural networks for efficient subtype classification.

No drains in reduction mammaplasty - a systematic review.

Breast reduction mammaplasty is the only effective therapeutic intervention for patients with symptomatic breast hypertrophy. In this procedure, closed suction drains have become a standard of care, while the literature supporting use of drains is lacking. In fact, with emerging data we found out that drains might not be so necessary. This review aimed to systematically compare the number of complications in drained and undrained breasts and to evaluate the safety of omitting drains in reduction mammaplasty in clinical practice. A systematic review of literature was conducted identifying all studies on drainage in reduction mammaplasty. The analysed databases revealed 13 eligible studies to be included in this review. There were 308 drained breasts and 859 undrained breasts in total in patients from 16 to 73 years of age. The resected tissue weight per side fluctuated from 108 to 1,296 grams. In total, there was only 2.4% incidence of haematoma complications in undrained breasts and 3.9% in drained breasts. Closed suction drains are still being routinely used in reduction mammaplasty, although aborting drain use is proven to be not only safe, but advantageous. The clear benefit is increased patient comfort, shortened hospital stay, decreased cost of the procedure and nurse care, and decreased rate of complications.

A novel preclinical model of the normal human breast.

Improved screening and treatment have decreased breast cancer mortality, although incidence continues to rise. Women at increased risk of breast cancer can be offered risk reducing treatments, such as tamoxifen, but this has not been shown to reduce breast cancer mortality. New, more efficacious, risk-reducing agents are needed. The identification of novel candidates for prevention is hampered by a lack of good preclinical models. Current patient derived in vitro and in vivo models cannot fully recapitulate the complexities of the human tissue, lacking human extracellular matrix, stroma, and immune cells, all of which are known to influence therapy response. Here we describe a normal breast explant model utilising a tuneable hydrogel which maintains epithelial proliferation, hormone receptor expression, and residency of T cells and macrophages over 7 days. Unlike other organotypic tissue cultures which are often limited by hyper-proliferation, loss of hormone signalling, and short treatment windows (< 48h), our model shows that tissue remains viable over 7 days with none of these early changes. This offers a powerful and unique opportunity to model the normal breast and study changes in response to various risk factors, such as breast density and hormone exposure. Further validation of the model, using samples from patients undergoing preventive therapies, will hopefully confirm this to be a valuable tool, allowing us to test novel agents for breast cancer risk reduction preclinically.

Integrated Case-Based Learning Session for Breast and Upper Limb Anatomy.

Introduction: Medical students are frequently introduced to medical school curricula through anatomy coursework, which often includes histology and embryology content. As medical education has increasingly emphasized integration of content areas, use of activities such as case-based learning (CBL) sessions has grown. Little published work has demonstrated the effectiveness of CBL sessions in integrating anatomy, embryology, and histology on first-year medical students' ability to improve content mastery and adapt their study techniques. Methods: We developed a CBL session that included anatomy, embryology, and histology content covering the upper extremity and breast pathology that was taught to incoming first-year medical students (N = 51) during a prematriculation program in the summers of 2022 and 2023. The session involved completion of an individual pre- and postsession quiz; group completion of clinical cases involving image interpretation, matching exercises, and construction of diagrams, flowcharts, or tables; and a postsession survey with Likert-style and free-response questions about preparation and session effectiveness. Results: Postsession quiz scores significantly improved (p < .001). On the postsession survey (response rate: 59%), students commented that they enjoyed the real-life application and integration of the cases and that the sessions improved their understanding of the connections between content areas. Other comments demonstrated that students were evaluating and adapting their study approach in preparation for the sessions, often using techniques introduced and practiced in the sessions. Discussion: CBL sessions can provide opportunities to incoming first-year medical students to practice, adapt, and evaluate study techniques while delivering integrated content.

Functional hemodynamic imaging markers for the prediction of pathological outcomes in breast cancer patients treated with neoadjuvant chemotherapy.

Significance: Achieving pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is a significant predictor of increased likelihood of survival in breast cancer patients. Early prediction of pCR is of high clinical value as it could allow personalized adjustment of treatment regimens in non-responding patients for improved outcomes. Aim: We aim to assess the association between hemoglobin-based functional imaging biomarkers derived from diffuse optical tomography (DOT) and the pathological outcome represented by pCR at different timepoints along the course of NACT. Approach: Twenty-two breast cancer patients undergoing NACT were enrolled in a multimodal DOT and X-ray digital breast tomosynthesis (DBT) imaging study in which their breasts were imaged at different compression levels. Logistic regressions were used to study the associations between DOT-derived imaging markers evaluated after the first and second cycles of chemotherapy, respectively, with pCR status determined after the conclusion of NACT at the time of surgery. Receiver operating characteristic curve analysis was also used to explore the predictive performance of selected DOT-derived markers. Results: Normalized tumor HbT under half compression was significantly lower in the pCR group compared to the non-pCR group after two chemotherapy cycles (p=0.042). In addition, the change in normalized tumor StO2 upon reducing compression from full to half mammographic force was identified as another potential indicator of pCR at an earlier time point, i.e., after the first chemo cycle (p=0.038). Exploratory predictive assessments showed that AUCs using DOT-derived functional imaging markers as predictors reach as high as 0.75 and 0.71, respectively, after the first and second chemo cycle, compared to AUCs of 0.50 and 0.53 using changes in tumor size measured on DBT and MRI. Conclusions: These findings suggest that breast DOT could be used to assist response assessment in women undergoing NACT, a critical but unmet clinical need, and potentially enable personalized adjustments of treatment regimens.

Improvement of Phased Antenna Array Applied in Focused Microwave Breast Hyperthermia.

Focused microwave breast hyperthermia (FMBH) employs a phased antenna array to perform beamforming that can focus microwave energy at targeted breast tumors. Selective heating of the tumor endows the hyperthermia treatment with high accuracy and low side effects. The effect of FMBH is highly dependent on the applied phased antenna array. This work investigates the effect of polarizations of antenna elements on the microwave-focusing results by simulations. We explore two kinds of antenna arrays with the same number of elements using different digital realistic human breast phantoms. The first array has all the elements' polarization in the vertical plane of the breast, while the second array has half of the elements' polarization in the vertical plane and the other half in the transverse plane, i.e., cross polarization. In total, 96 sets of different simulations are performed, and the results show that the second array leads to a better focusing effect in dense breasts than the first array. This work is very meaningful for the potential improvement of the antenna array for FMBH, which is of great significance for the future clinical applications of FMBH. The antenna array with cross polarization can also be applied in microwave imaging and sensing for biomedical applications.

Breast arterial calcification is associated with sarcopenia in peri- and post-menopausal women.

PURPOSE: Breast arterial calcification (BAC) refers to medial calcium deposition in breast arteries and is detectable via mammography. Sarcopenia, which is characterised by low skeletal muscle mass and quality, is associated with several serious clinical conditions, increased morbidity, and mortality. Both BAC and sarcopenia share common pathologic pathways, including ageing, diabetes, and chronic kidney disease. Therefore, this study evaluated the relationship between BAC and sarcopenia as a potential indicator of sarcopenia. METHODS: This study involved women aged >40. BAC was evaluated using digital mammography and was defined as vascular calcification. Sarcopenia was assessed using abdominal computed tomography. The cross-sectional skeletal mass area was measured at the third lumbar vertebra level. The skeletal mass index was obtained by dividing the skeletal mass area by height in square meters(m2). Sarcopenia was defined as a skeletal mass index of ≤38.5 cm2/m2. A multivariable model was used to evaluate the relationship between BAC and sarcopenia. RESULTS: The study involved 240 participants. Of these, 36 (15 %) were patients with BAC and 204 (85 %) were without BAC. Sarcopenia was significantly higher among the patients with BAC than in those without BAC (72.2 % vs 17.2 %, P < 0.001). The multivariable model revealed that BAC and age were independently associated with sarcopenia (odds ratio[OR]: 7.719, 95 % confidence interval[CI]: 3.201-18.614, and P < 0.001 for BAC and OR: 1.039, 95 % CI: 1.007-1.073, P = 0.01 for age). CONCLUSION: BAC is independently associated with sarcopenia. BAC might be used as an indicator of sarcopenia on screening mammography.

PFDN4 as a Prognostic Marker Was Associated with Chemotherapy Resistance through CREBP1/AURKA Pathway in Triple-Negative Breast Cancer.

Breast cancer is the most common malignancy and its incidence is increasing. It is currently mainly treated by clinical chemotherapy, but chemoresistance remains poorly understood. Prefolded proteins 4 (PFDN4) are molecular chaperone complexes that bind to newly synthesized polypeptides and allow them to fold correctly to stabilize protein formation. This study aimed to investigate the role of PFDN4 in chemotherapy resistance in breast cancer. Our study found that PFDN4 was highly expressed in breast cancer compared to normal tissues and was statistically significantly associated with stage, nodal status, subclasses (luminal, HER2 positive and triple negative), triple-negative subtype and disease-specific survival by TCGA database analysis. CRISPR knockout of PFDN4 inhibited the growth of 89% of breast cancer cell lines, and the triple-negative cell line exhibited a stronger inhibitory effect than the non-triple-negative cell line. High PFDN4 expression was associated with poor overall survival in chemotherapy and resistance to doxorubicin and paclitaxel through the CREBP1/AURKA pathway in the triple-negative MDAMB231 cell line. This study provides insightful evidence for the value of PFDN4 in poor prognosis and chemotherapy resistance in breast cancer patients.

B7-H3 Expression in Breast Cancer and Brain Metastasis.

Brain metastasis is a significant challenge for some breast cancer patients, marked by its aggressive nature, limited treatment options, and poor clinical outcomes. Immunotherapies have emerged as a promising avenue for brain metastasis treatment. B7-H3 (CD276) is an immune checkpoint molecule involved in T cell suppression, which is associated with poor survival in cancer patients. Given the increasing number of clinical trials using B7-H3 targeting CAR T cell therapies, we examined B7-H3 expression across breast cancer subtypes and in breast cancer brain metastases to assess its potential as an interventional target. B7-H3 expression was investigated using immunohistochemistry on tissue microarrays of three clinical cohorts: (i) unselected primary breast cancers (n = 347); (ii) brain metastatic breast cancers (n = 61) and breast cancer brain metastases (n = 80, including a subset of 53 patient-matched breast and brain metastasis cases); and (iii) mixed brain metastases from a range of primary tumours (n = 137). In primary breast cancers, B7-H3 expression significantly correlated with higher tumour grades and aggressive breast cancer subtypes, as well as poorer 5-year survival outcomes. Subcellular localisation of B7-H3 impacted breast cancer-specific survival, with cytoplasmic staining also correlating with a poorer outcome. Its expression was frequently detected in brain metastases from breast cancers, with up to 90% expressing B7-H3. However, not all brain metastases showed high levels of expression, with those from colorectal and renal tumours showing a low frequency of B7-H3 expression (0/14 and 2/16, respectively). The prevalence of B7-H3 expression in breast cancers and breast cancer brain metastases indicates potential opportunities for B7-H3 targeted therapies in breast cancer management.

Breast density quantification in dual-energy mammography using virtual anthropomorphic phantoms.

PURPOSE: Breast density is a significant risk factor for breast cancer and can impact the sensitivity of screening mammography. Area-based breast density measurements may not provide an accurate representation of the tissue distribution, therefore volumetric breast density (VBD) measurements are preferred. Dual-energy mammography enables volumetric measurements without additional assumptions about breast shape. In this work we evaluated the performance of a dual-energy decomposition technique for determining VBD by applying it to virtual anthropomorphic phantoms. METHODS: The dual-energy decomposition formalism was used to quantify VBD on simulated dual-energy images of anthropomorphic virtual phantoms with known tissue distributions. We simulated 150 phantoms with volumes ranging from 50 to 709 mL and VBD ranging from 15% to 60%. Using these results, we validated a correction for the presence of skin and assessed the method's intrinsic bias and variability. As a proof of concept, the method was applied to 14 sets of clinical dual-energy images, and the resulting breast densities were compared to magnetic resonance imaging (MRI) measurements. RESULTS: Virtual phantom VBD measurements exhibited a strong correlation (Pearson's r > 0.95 $r > 0.95$ ) with nominal values. The proposed skin correction eliminated the variability due to breast size and reduced the bias in VBD to a constant value of -2%. Disagreement between clinical VBD measurements using MRI and dual-energy mammography was under 10%, and the difference in the distributions was statistically non-significant. VBD measurements in both modalities had a moderate correlation (Spearman's ρ $\rho \ $ = 0.68). CONCLUSIONS: Our results in virtual phantoms indicate that the material decomposition method can produce accurate VBD measurements if the presence of a third material (skin) is considered. The results from our proof of concept showed agreement between MRI and dual-energy mammography VBD. Assessment of VBD using dual-energy images could provide complementary information in dual-energy mammography and tomosynthesis examinations.

The influence of a previous implant-based breast reconstruction on postoperative sensation of the deep inferior epigastric artery perforator flap.

BACKGROUND: Implants and DIEP flaps have different outcomes regarding postoperative breast sensation. When compared to the preoperative healthy breast, implant-based breast reconstruction (IBBR) negatively influences postoperative breast sensation. However, it is currently unknown whether a prior IBBR also influences postoperative sensation of a replacing DIEP flap. The goal of this cohort study is to evaluate the influence of an IBBR on the postoperative sensation of a replacing DIEP flap. METHODS: Women were included if they received a DIEP flap reconstruction after mastectomy, with or without prior tissue expander (TE) and/or definitive breast implant. Sensation was measured at four intervals in 9 areas of the breast with Semmes-Weinstein monofilaments: T0 (preoperative, implant/no reconstruction), T1 (2-7 months postoperative, DIEP), T2 (± 12 months postoperative, DIEP), Tmax (maximum follow-up, DIEP). Linear mixed-effects models were used to investigate the relationship between an implant/TE prior to the DIEP flap and recovery of breast sensation. RESULTS: 142 women comprising 206 breasts were included. 48 (23.3%) breasts did, and 158 (76.7%) breasts did not have a TE/IBBR prior to their DIEP. No statistically significant or clinically relevant relationships were found between a prior implant/TE and recovery of DIEP flap breast sensation for the flap skin, native skin, or total breast skin at T1, T2, or Tmax. There were also no relationships found after adjustment for the confounders radiation therapy, BMI, diabetes, age, flap weight, follow-up, and nerve coaptation. CONCLUSIONS: An implant/TE prior to a DIEP flap does not influence the recovery of postoperative breast sensation of the DIEP flap.

Technical note: Characterization, validation, and spectral optimization of a dedicated breast CT system for contrast-enhanced imaging.

BACKGROUND: The development of a new imaging modality, such as 4D dynamic contrast-enhanced dedicated breast CT (4D DCE-bCT), requires optimization of the acquisition technique, particularly within the 2D contrast-enhanced imaging modality. Given the extensive parameter space, cascade-systems analysis is commonly used for such optimization. PURPOSE: To implement and validate a parallel-cascaded model for bCT, focusing on optimizing and characterizing system performance in the projection domain to enhance the quality of input data for image reconstruction. METHODS: A parallel-cascaded system model of a state-of-the-art bCT system was developed and model predictions of the presampled modulation transfer function (MTF) and the normalized noise power spectrum (NNPS) were compared with empirical data collected in the projection domain. Validation was performed using the default settings of 49 kV with 1.5 mm aluminum filter and at 65 kV and 0.257 mm copper filter. A 10 mm aluminum plate was added to replicate the breast attenuation. Air kerma at the isocenter was measured at different tube current levels. Discrepancies between the measured projection domain metrics and model-predicted values were quantified using percentage error and coefficient of variation (CoV) for MTF and NNPS, respectively. The optimal filtration was for a 5 mm iodine disk detection task at 49, 55, 60, and 65 kV. The detectability index was calculated for the default aluminum filtration and for copper thicknesses ranging from 0.05 to 0.4 mm. RESULTS: At 49 kV, MTF errors were +5.1% and -5.1% at 1 and 2 cycles/mm, respectively; NNPS CoV was 5.3% (min = 3.7%; max = 8.5%). At 65 kV, MTF errors were -0.8% and -3.2%; NNPS CoV was 13.1% (min = 11.4%; max = 16.9%). Air kerma output was linear, with 11.67 µGy/mA (R2 = 0.993) and 19.14 µGy/mA (R2 = 0.996) at 49 and 65 kV, respectively. For iodine detection, a 0.25 mm-thick copper filter at 65 kV was found optimal, outperforming the default technique by 90%. CONCLUSION: The model accurately predicts bCT system performance, specifically in the projection domain, under varied imaging conditions, potentially contributing to the enhancement of 2D contrast-enhanced imaging in 4D DCE-bCT.

Savi Scout Localization for Extrapelvic Endometriosis Resection.

BACKGROUND Endometriosis is a common cause of chronic pelvic pain among women globally. Pharmacological therapy for endometriosis includes non-steroidal anti-inflammatory drugs (NSAIDs) and hormonal contraceptives, while surgical therapy often involves either laparoscopic excision and ablation of endometriosis implants or open surgery. Surgical therapy is one of the mainstays of treatment especially for extrapelvic endometriomas. However, little guidance exists for the treatment of non-palpable or intermittently palpable lesions of this nature. CASE REPORT A 33-year-old woman with a previous cesarean section presented with complaints of intermittent discomfort in the area between her umbilicus and the surgical incision, for the previous 7 years, that worsened during her menstrual cycle. A 3×3-cm area of fullness was only intermittently palpable during various clinic visits, but was visualizable on computed tomography and magnetic resonance imaging. Given the lesion's varying palpability, a Savi Scout radar localization device was placed into the lesion pre-operatively to aid with surgical resection. The mass was excised, pathologic examination revealed endometrial tissue, and the patient had an uncomplicated postoperative course with resolution of her symptoms. CONCLUSIONS Surgical removal of extrapelvic endometrioma lesions can be made difficult by varying levels of palpability or localizability due to a patient's menstrual cycle. The Savi Scout, most commonly used in breast mass localization, is a useful tool in guiding surgical excision of non-palpable or intermittently palpable extrapelvic endometrioma lesions.

Predictive modeling for breast cancer classification in the context of Bangladeshi patients by use of machine learning approach with explainable AI.

Breast cancer has rapidly increased in prevalence in recent years, making it one of the leading causes of mortality worldwide. Among all cancers, it is by far the most common. Diagnosing this illness manually requires significant time and expertise. Since detecting breast cancer is a time-consuming process, preventing its further spread can be aided by creating machine-based forecasts. Machine learning and Explainable AI are crucial in classification as they not only provide accurate predictions but also offer insights into how the model arrives at its decisions, aiding in the understanding and trustworthiness of the classification results. In this study, we evaluate and compare the classification accuracy, precision, recall, and F1 scores of five different machine learning methods using a primary dataset (500 patients from Dhaka Medical College Hospital). Five different supervised machine learning techniques, including decision tree, random forest, logistic regression, naive bayes, and XGBoost, have been used to achieve optimal results on our dataset. Additionally, this study applied SHAP analysis to the XGBoost model to interpret the model's predictions and understand the impact of each feature on the model's output. We compared the accuracy with which several algorithms classified the data, as well as contrasted with other literature in this field. After final evaluation, this study found that XGBoost achieved the best model accuracy, which is 97%.

Paget's disease of the breast: Presentation, treatment, and outcomes in a modern cohort.

BACKGROUND: Surgical management for Paget's disease (PD) of the breast is controversial. This study aims to assess outcomes of PD patients based on procedure type and determine the reliability of imaging in estimating disease extent. METHODS: A retrospective review analyzed clinicopathologic data of PD patients between 2009 and 2022. Pre-operative imaging size (PIS) was compared to post-operative pathology size (PPS) looking at concordance. RESULTS: Thirty patients had PD, 21 underwent total mastectomy (TM) and 9 breast conserving surgery (BCS). Seventeen patients (56.7 â€‹%) had a final diagnosis of invasive cancer (14 â€‹TM, 3 BCS), with no local recurrences. Only 6/19 (31.6 â€‹%) patients with positive findings on ultrasound/mammogram had concordance between PIS and PPS. There were no breast/chest wall recurrences with a median follow up of 35.9 months. CONCLUSION: Ultrasound and mammogram had poor concordance with pathological size. BCS is feasible in select patients. MRI may help guide management.

Margin assessment during breast conserving surgery using diffuse reflectance spectroscopy.

Significance: During breast-conserving surgeries, it is essential to evaluate the resection margins (edges of breast specimen) to determine whether the tumor has been removed completely. In current surgical practice, there are no methods available to aid in accurate real-time margin evaluation. Aim: In this study, we investigated the diagnostic accuracy of diffuse reflectance spectroscopy (DRS) combined with tissue classification models in discriminating tumorous tissue from healthy tissue up to 2 mm in depth on the actual resection margin of in vivo breast tissue. Approach: We collected an extensive dataset of DRS measurements on ex vivo breast tissue and in vivo breast tissue, which we used to develop different classification models for tissue classification. Next, these models were used in vivo to evaluate the performance of DRS for tissue discrimination during breast conserving surgery. We investigated which training strategy yielded optimum results for the classification model with the highest performance. Results: We achieved a Matthews correlation coefficient of 0.76, a sensitivity of 96.7% (95% CI 95.6% to 98.2%), a specificity of 90.6% (95% CI 86.3% to 97.9%) and an area under the curve of 0.98 by training the optimum model on a combination of ex vivo and in vivo DRS data. Conclusions: DRS allows real-time margin assessment with a high sensitivity and specificity during breast-conserving surgeries.

Assessment of average glandular dose in mammography practice of a teaching hospital in Ghana.

Introduction: above the age of 40, women are advised to begin breast examinations and screenings for early detection of breast cancer. The average glandular dose (AGD) provides dosimetric information about the quantity of radiation received by the mammary glands during mammographic exposures. There is, therefore, the need to analyse the radiation dose received by patients presenting for mammography examinations. Methods: a retrospective cross-sectional design was carried out on the data of 663 participants, conveniently sampled between the months of July 2021 and June 2022. Paired T-test was used to compare imaging parameters for cranio-caudal (CC), medio-lateral (ML), automatic exposure control (AEC), manual exposure control (MEC), and left and right breast. Pearson´s correlation was used to test for relationship between imaging parameters and AGD. Results: the mean AGD per exposure was 1.9 ± 0.7 mGy for CC projections and 2.3 ± 1.2 mGy for ML projections. The mean AGD per examination for the study was 4.1 ± 1.4 mGy. A positive correlation was found between AGD per examination and exposure factors (tube loading and tube voltage), compressed breast thickness, and compression force. Patient age had no statistically significant relationship with the AGD per examination. Conclusion: average glandular dose (AGD) was consistent with other findings in literature studies. It was also observed that MEC yielded lower AGD per exposure values than AEC. There was no significant difference in the mean AGD per exposure for left and right breasts.

Decorin (DCN) Downregulation Activates Breast Stromal Fibroblasts and Promotes Their Pro-Carcinogenic Effects through the IL-6/STAT3/AUF1 Signaling.

Decorin (DCN), a member of the small leucine-rich proteoglycan gene family, is secreted from stromal fibroblasts with non-cell-autonomous anti-breast-cancer effects. Therefore, in the present study, we sought to elucidate the function of decorin in breast stromal fibroblasts (BSFs). We first showed DCN downregulation in active cancer-associated fibroblasts (CAFs) compared to their adjacent tumor counterpart fibroblasts at both the mRNA and protein levels. Interestingly, breast cancer cells and the recombinant IL-6 protein, both known to activate fibroblasts in vitro, downregulated DCN in BSFs. Moreover, specific DCN knockdown in breast fibroblasts modulated the expression/secretion of several CAF biomarkers and cancer-promoting proteins (α-SMA, FAP- α, SDF-1 and IL-6) and enhanced the invasion/proliferation abilities of these cells through activation of the STAT3/AUF1 signaling. Furthermore, DCN-deficient fibroblasts promoted the epithelial-to-mesenchymal transition and stemness processes in BC cells in a paracrine manner, which increased their resistance to cisplatin. These DCN-deficient fibroblasts also enhanced angiogenesis and orthotopic tumor growth in mice in a paracrine manner. On the other hand, ectopic expression of DCN in CAFs suppressed their active features and their paracrine pro-carcinogenic effects. Together, the present findings indicate that endogenous DCN suppresses the pro-carcinogenic and pro-metastatic effects of breast stromal fibroblasts.