Surface dose measurement and comparison between TLD and OSLD during modified re constructive mastectomy irradiation.

Radiotherapy (RT) is one of the major treatment modalities among surgery and chemotherapy for carcinoma breast. The surface dose study of modified reconstructive constructive Mastectomy (MRM) breast is important due to the heterogeneity in the body contour and the conventional treatment angle to save the lungs and heart from the radiation. These angular entries of radiation beam cause an unpredictable dose deposition on the body surface, which has to be monitored. Thermoluminescent dosimeter (TLD) or optically stimulated luminescent dosimeter (nano OSLD) are commonly preferable dosimeters for this purpose. The surface dose response of TLD and nano OSLD during MRM irradiation has been compared with the predicted dose from the treatment planning system (TPS). The study monitored 100 MRM patients by employing a total 500 dosimeters consisting of TLD (n = 250) and nano OSLD (n = 250), during irradiation from an Elekta Versa HD 6 MV Linear accelerator. The study observed a variance of 3.9% in the dose measurements for TLD and 3.2% for nano OSLD from the planned surface dose, with a median percentage dose of 44.02 for nano OSLD and 40.30 for TLD (p value 0.01). There was no discernible evidence of variation in dose measurements attributable to differences in field size or from patient to patient. Additionally, no variation was observed in dose measurements when comparing the placement of the dosimeter from central to off-centre positions. In comparison, a minor difference in dose measurements were noted between TLD and nano OSLD, The study's outcomes support the applicability of both TLD and nano OSLD as effective dosimeters during MRM breast irradiation for surface dose evaluation.

A prediction model based on digital breast pathology image information.

BACKGROUND: The workload of breast cancer pathological diagnosis is very heavy. The purpose of this study is to establish a nomogram model based on pathological images to predict the benign and malignant nature of breast diseases and to validate its predictive performance. METHODS: In retrospect, a total of 2,723 H&E-stained pathological images were collected from 1,474 patients at Qingdao Central Hospital between 2019 and 2022. The dataset consisted of 509 benign tumor images (adenosis and fibroadenoma) and 2,214 malignant tumor images (infiltrating ductal carcinoma). The images were divided into a training set (1,907) and a validation set (816). Python3.7 was used to extract the values of the R channel, G channel, B channel, and one-dimensional information entropy from all images. Multivariable logistic regression was used to select variables and establish the breast tissue pathological image prediction model. RESULTS: The R channel value, B channel value, and one-dimensional information entropy of the images were identified as independent predictive factors for the classification of benign and malignant pathological images (P < 0.05). The area under the curve (AUC) of the nomogram model in the training set was 0.889 (95% CI: 0.869, 0.909), and the AUC in the validation set was 0.838 (95% CI: 0.7980.877). The calibration curve results showed that the calibration curve of this nomogram model was close to the ideal curve. The decision curve results indicated that the predictive model curve had a high value for auxiliary diagnosis. CONCLUSION: The nomogram model for the prediction of benign and malignant breast diseases based on pathological images demonstrates good predictive performance. This model can assist in the diagnosis of breast tissue pathological images.

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.

Cylindroma of the Breast: A Rare Differential for Breast Cancer on Core Biopsies, Case Report and Review of Literature.

Breast cancers of either ductal or lobular pathology make up the vast majority of breast malignancies. Other cancers occur rarely in the breast. Benign pathology can at times mimic breast cancers on imaging and initial needle biopsies. We report a rare breast pathology of cylindroma. Cylindromas are usually benign, rare dermatologic lesions most commonly associated with head or neck locations. They more commonly occur as sporadic and solitary masses. Less commonly is an autosomal-dominant multi-centric form of this disease. Malignant cylindromas are very rare. We present a patient with findings of a cylindroma of the breast after excision. This was initially felt to be concerning for breast cancer on imaging and core biopsy. Treatment of cylindromas of the breast is excision. Sentinel lymph node dissection is not indicated, nor are adjuvant therapies when identified in the breast. This lesion needs to be included in the differential diagnosis for breast cancer. If cylindromas can be accurately diagnosed preoperatively, this would negate the need for consideration of axillary nodal surgery and adjuvant therapies.

Prophylactic central lymph node dissection in cN0 papillary thyroid cancer: a comparative study of via breast and transoral approach versus via breast approach alone.

Background: Papillary thyroid cancer (PTC) progresses slowly and has a good prognosis, while the prognosis is worse if combined with central neck lymph node metastasis at an early stage. The different endoscope approaches may affect the thoroughness of lymph node dissection. This study aimed to compare the clinical efficacy and safety of prophylactic central lymph node dissection(CLND) for cN0 PTC performed via breast and transoral approach versus via breast approach alone. Materials and methods: A retrospective analysis of the surgical data of 136 patients with stage cN0 PTC was performed from August 2020 to December 2022. Among them, 64 underwent the breast and transoral approach (combined approach group), and 72 underwent the breast approach alone (breast approach group). The relevant indexes of surgery, the number of lymph nodes dissected, the occurrence of postoperative complications, and the cosmetic satisfaction of incision were statistically compared between the two groups. Results: The operation time of the combined approach group was 156.4 ± 29.8 min, significantly longer than that of the breast approach group, 119.6 ± 55.9 min, and the difference was statistically significant (P<0.05). The two groups of patients were compared in terms of intraoperative bleeding, postoperative drainage, hospitalization time, incision cosmetic satisfaction, and the occurrence of postoperative complications, and the differences were not statistically significant (P>0.05). The total number of lymph nodes retrieved in the central area (10.6 ± 7.1) and the number of positive lymph nodes (4.6 ± 4.9) in the combined approach group were significantly more than those in the breast approach group (7.4 ± 4.8, 1.6 ± 2.7), and the difference was statistically significant (P<0.05). The difference between the two groups in terms of the number of negative lymph nodes was not statistically significant (P>0.05). Conclusions: The study demonstrated that choosing the breast combined transoral approach for prophylactic CLND of cN0 PTC could more thoroughly clear the central area lymph nodes, especially the positive lymph nodes, which could help in the evaluation of the disease and the guidance of the treatment, while not increasing the postoperative complications. It provides a reference for clinicians to choose the appropriate surgical approach and also provides new ideas and methods for prophylactic CLND in patients with cN0 PTC.

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.

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.

Breast density prediction from low and standard dose mammograms using deep learning: effect of image resolution and model training approach on prediction quality.

Purpose. To improve breast cancer risk prediction for young women, we have developed deep learning methods to estimate mammographic density from low dose mammograms taken at approximately 1/10th of the usual dose. We investigate the quality and reliability of the density scores produced on low dose mammograms focussing on how image resolution and levels of training affect the low dose predictions.Methods. Deep learning models are developed and tested, with two feature extraction methods and an end-to-end trained method, on five different resolutions of 15,290 standard dose and simulated low dose mammograms with known labels. The models are further tested on a dataset with 296 matching standard and real low dose images allowing performance on the low dose images to be ascertained.Results. Prediction quality on standard and simulated low dose images compared to labels is similar for all equivalent model training and image resolution versions. Increasing resolution results in improved performance of both feature extraction methods for standard and simulated low dose images, while the trained models show high performance across the resolutions. For the trained models the Spearman rank correlation coefficient between predictions of standard and low dose images at low resolution is 0.951 (0.937 to 0.960) and at the highest resolution 0.956 (0.942 to 0.965). If pairs of model predictions are averaged, similarity increases.Conclusions. Deep learning mammographic density predictions on low dose mammograms are highly correlated with standard dose equivalents for feature extraction and end-to-end approaches across multiple image resolutions. Deep learning models can reliably make high quality mammographic density predictions on low dose mammograms.

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.

[Feasibility analysis of the application of programmed process endoscopic lateral neck dissection via chest-breast approach in papillary thyroid carcinoma surgery].

Objective: To explore the feasibility of endoscopic lymph node dissection(LND) with programmed breast approach for the treatment of papillary thyroid cancer. Methods: A case series study. The clinical data of 39 patients with papillary thyroid cancer who underwent endoscopic LND treatment with programmed breast approach in Shenzhen People's Hospital from January to November 2022 were retrospectively analyzed. There were 10 males and 29 females, aged (35.95±10.17) years. LND time, total surgical time, intraoperative bleeding volume, postoperative drainage volume, postoperative hospital stay and postoperative complications were analyzed. Results: Among 39 patients, there were 18 cases of unilateral thyroid cancer, 21 cases of bilateral thyroid cancer, 35 cases of unilateral LND, and 4 cases of bilateral LND. The maximum diameter of thyroid cancer lesions was (1.48±0.69) cm, and the maximum diameter of lymph node metastases was (1.63±0.58)cm. The operative time of unilateral neck dissection was (124.11±19.92) min (102-170 min), and the total operative time was (226.42±55.68) min (110-390 min). The number of lymph nodes cleaned was (32.40±10.44)(12-54), the number of metastasis and detection was 207/1 393. The postoperative drainage volume was (174.64±82.33) ml(41-350 ml). There were no neck hematomas, no skin burns or no shrugging disorders in the postoperative period. There were 7 cases of numbness and discomfort in neck skin sensation, which gradually relieved after half a year. Postoperative discharge time (4.77±1.94) d(3-15 d). Conclusion: It is safe and feasible to treat papillary thyroid cancer with endoscopic LND with programmed breast approach, which can improve surgical efficiency and clinical application value.

Sonographic Evaluation of Nigerian Women with Mammographic Focal Asymmetric Density.

BACKGROUND AND OBJECTIVE: Focal asymmetric breast densities (FABD) present a diagnostic challenge concerning the need for a further histologic workup to rule out malignancy. We therefore aim to correlate ultrasonography and mammographic findings in women with FABD and evaluate the use of ultrasonography as a workup tool. METHODOLOGY: This is a retrospective study of women who underwent targeted breast sonography due to FABD with a mammogram in a private diagnostic centre in Abuja over three years (2016-2018). Demographic details, clinical indication, mammographic and ultrasonography features were documented and statistical analysis was done using SAS software version 9.3 with the statistical level of significance set at 0.05. RESULT: The age range of 44 patients was 32-69 years with a majority (79.5%) presenting for screening mammography. The predominant breast density pattern in those <60 years was heterogeneous (ACR C). FABD in mammography was noted mostly in the upper outer quadrant and retro-areolar regions (34.1 and 38.6%). Ultrasonography findings were normal breast tissue (56.8%), 4 simple cysts, 1 abscess, 4 solid masses, 2 focal fibrocystic changes, and 4 cases of duct ectasia. Twenty-nine (65.9%) of the abnormal cases were on the same side as the mammogram, while all the incongruent cases were recorded in heterogeneously dense breasts (ACR C). Final BIRADS Scores on USS showed that 41(93.2%) of mammographic FABD had normal and benign findings while only 2(4.6%) had sonographic features of malignancy. CONCLUSION: Breast ultrasonography allows for optimal lesion characterization and is a veritable tool in the workup of patients with focal asymmetric breast densities with the majority presenting as normal breast tissue and benign pathologies.

CONTEXTE ET OBJECTIF: Les densités asymétriques mammographiques focales mammographiques, FABD présentent un défi diagnostique en ce qui concerne la nécessité d'un examen histologique supplémentaire pour exclure une tumeur maligne. Nous visons donc à corréler les résultats échographiques et mammographiques chez les femmes ayant une densité mammaire focale asymétrique et à établir la nécessité d'un bilan plus approfondi. METHODOLOGIE: Une étude rétrospective de 44 femmes ayant subi une échographie ciblée du sein en raison de FABD à la mammographie dans un centre de diagnostic privé à Abuja sur trois ans (2016-2018) Les détails démographiques, les présentations cliniques, les caractéristiques mammographiques et échographiques ont été documentés et analysés statistiquement fait à l'aide du logiciel SAS version 9.3 avec un niveau de signification statistique fixé à 0,05. RESULTAT: La tranche d'âge des patients était de 32 à 69 ans (SD 1), la majorité (79,5%) se présentant pour une mammographie de dépistage. Le schéma de densité mammaire prédominant chez les moins de 60 ans était hétérogène (ACR C). FABD en mammographie a presque la même distribution dans le quadrant externe supérieur et les régions rétroaréolaires (38,4 vs 36,8%). Les résultats échographiques étaient: tissu mammaire normal (65,9%), 4 kystes simples, 1 kyste complexe, 4 masses solides, 2 fibrokystiques focales et 4 cas d'ectasie canalaire.29 (65,9%) des cas anormaux étaient du même côté que la mammographie, alors que tous les cas incongruents ont été enregistrés dans des seins denses de manière hétérogène (ACR C). Les scores finaux BIRADS sur USS ont montré que 41 (93,2%) des FABD mammographiques avaient des résultats normaux et bénins, tandis que seulement 2 (4,6%) avaient des caractéristiques échographiques de malignité. CONCLUSION: L'échographie mammaire permet une caractérisation optimale des lésions et constitue un véritable outil dans le bilan des patientes présentant des densités mammaires asymétriques focales dont la majorité se présente comme un tissu mammaire normal et des pathologies bénignes. MOTS CLES: Sein, Asymétrie focale, Échographie, Mammographie.

Patient Characteristics Impact Performance of AI Algorithm in Interpreting Negative Screening Digital Breast Tomosynthesis Studies.

Background Artificial intelligence (AI) is increasingly used to manage radiologists' workloads. The impact of patient characteristics on AI performance has not been well studied. Purpose To understand the impact of patient characteristics (race and ethnicity, age, and breast density) on the performance of an AI algorithm interpreting negative screening digital breast tomosynthesis (DBT) examinations. Materials and Methods This retrospective cohort study identified negative screening DBT examinations from an academic institution from January 1, 2016, to December 31, 2019. All examinations had 2 years of follow-up without a diagnosis of atypia or breast malignancy and were therefore considered true negatives. A subset of unique patients was randomly selected to provide a broad distribution of race and ethnicity. DBT studies in this final cohort were interpreted by a U.S. Food and Drug Administration-approved AI algorithm, which generated case scores (malignancy certainty) and risk scores (1-year subsequent malignancy risk) for each mammogram. Positive examinations were classified based on vendor-provided thresholds for both scores. Multivariable logistic regression was used to understand relationships between the scores and patient characteristics. Results A total of 4855 patients (median age, 54 years [IQR, 46-63 years]) were included: 27% (1316 of 4855) White, 26% (1261 of 4855) Black, 28% (1351 of 4855) Asian, and 19% (927 of 4855) Hispanic patients. False-positive case scores were significantly more likely in Black patients (odds ratio [OR] = 1.5 [95% CI: 1.2, 1.8]) and less likely in Asian patients (OR = 0.7 [95% CI: 0.5, 0.9]) compared with White patients, and more likely in older patients (71-80 years; OR = 1.9 [95% CI: 1.5, 2.5]) and less likely in younger patients (41-50 years; OR = 0.6 [95% CI: 0.5, 0.7]) compared with patients aged 51-60 years. False-positive risk scores were more likely in Black patients (OR = 1.5 [95% CI: 1.0, 2.0]), patients aged 61-70 years (OR = 3.5 [95% CI: 2.4, 5.1]), and patients with extremely dense breasts (OR = 2.8 [95% CI: 1.3, 5.8]) compared with White patients, patients aged 51-60 years, and patients with fatty density breasts, respectively. Conclusion Patient characteristics influenced the case and risk scores of a Food and Drug Administration-approved AI algorithm analyzing negative screening DBT examinations. © RSNA, 2024.

Performance of Diffusion-weighted Imaging-based Noncontrast MRI Protocols for Diagnosis of Breast Cancer: A Systematic Review and Meta-Analysis.

Background Diffusion-weighted imaging (DWI) is increasingly recognized as a powerful diagnostic tool and tested alternative to contrast-enhanced (CE) breast MRI. Purpose To perform a systematic review and meta-analysis that assesses the diagnostic performance of DWI-based noncontrast MRI protocols (ncDWI) for the diagnosis of breast cancer. Materials and Methods A systematic literature search in PubMed for articles published from January 1985 to September 2023 was performed. Studies were excluded if they investigated malignant lesions or selected patients and/or lesions only, used DWI as an adjunct technique to CE MRI, or were technical studies. Statistical analysis included pooling of diagnostic accuracy and investigating between-study heterogeneity. Additional subgroup comparisons of ncDWI to CE MRI and standard mammography were performed. Results A total of 28 studies were included, with 4406 lesions (1676 malignant, 2730 benign) in 3787 patients. The pooled sensitivity and specificity of ncDWI were 86.5% (95% CI: 81.4, 90.4) and 83.5% (95% CI: 76.9, 88.6), and both measures presented with high between-study heterogeneity (I 2 = 81.6% and 91.6%, respectively; P < .001). CE MRI (18 studies) had higher sensitivity than ncDWI (95.1% [95% CI: 92.9, 96.7] vs 88.9% [95% CI: 82.4, 93.1], P = .004) at similar specificity (82.2% [95% CI: 75.0, 87.7] vs 82.0% [95% CI: 74.8, 87.5], P = .97). Compared with ncDWI, mammography (five studies) showed no evidence of a statistical difference for sensitivity (80.3% [95% CI: 56.3, 93.3] vs 56.7%; [95% CI: 41.9, 70.4], respectively; P = .09) or specificity (89.9% [95% CI: 85.5, 93.1] vs 90% [95% CI: 61.3, 98.1], respectively; P = .62), but ncDWI had a higher area under the summary receiver operating characteristic curve (0.93 [95% CI: 0.91, 0.95] vs 0.78 [95% CI: 0.74, 0.81], P < .001). Conclusion A direct comparison with CE MRI showed a modestly lower sensitivity at similar specificity for ncDWI, and higher diagnostic performance indexes for ncDWI than standard mammography. Heterogeneity was high, thus these results must be interpreted with caution. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kataoka and Iima in this issue.

Breast Tuberculosis in Iran: A Comprehensive Review.

ABSTRACT: Tuberculosis (TB) remains a significant global health concern and kills millions of people every year. While TB can affect any organ in the body, breast TB is relatively uncommon. This study presents a comprehensive review of literature spanning 23 years, with a focus on cases of breast TB in Iran. Among the 96 cases found, the majority (89.6%) fell within the age range of 20-60, with a striking prevalence among women (98.9%). Common symptoms included pain and palpable mass, each presenting in approximately 60.4% of cases. Notably, only a quarter of patients had a confirmed history of exposure to a known TB case. Left breast involvement was more prevalent (58.3%), with ipsilateral lymph node enlargement observed in 40.6% of cases. Given the clinical presentation of breast TB, which often leads to misdiagnosis, a significant proportion of cases (68.7%) were diagnosed through excisional biopsy. Following a standard 6-month regimen of anti-TB drugs, relapse occurred in only 4.2% of cases. This study highlights the need for heightened awareness and vigilance in diagnosing breast TB, especially in regions with a high burden. Although breast TB poses diagnostic challenges, with prompt identification and treatment, the prognosis is generally favorable, with a low incidence of relapse.

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.

Tumor Doubling Time and Screening Interval.

The goal of screening is to detect breast cancers when still curable to decrease breast cancer-specific mortality. Breast cancer screening in the United States is routinely performed with digital mammography and digital breast tomosynthesis. This article reviews breast cancer doubling time by tumor subtype and examines the impact of doubling time on breast cancer screening intervals. By the article's end, the reader will be better equipped to have informed discussions with patients and medical professionals regarding the benefits and disadvantages of the currently recommended screening mammography intervals.

Artificial Intelligence for Breast Cancer Risk Assessment.

Breast cancer risk prediction models based on common clinical risk factors are used to identify women eligible for high-risk screening and prevention. Unfortunately, these models have only modest discriminatory accuracy with disparities in performance in underrepresented race and ethnicity groups. The field of artificial intelligence (AI) and deep learning are rapidly advancing the field of breast cancer risk prediction with the development of mammography-based AI breast cancer risk models. Early studies suggest mammography-based AI risk models may perform better than traditional risk factor-based models with more equitable performance.

Non-contrast Breast MR Imaging.

Considering the high cost of dynamic contrast-enhanced MR imaging and various contraindications and health concerns related to administration of intravenous gadolinium-based contrast agents, there is emerging interest in non-contrast-enhanced breast MR imaging. Diffusion-weighted MR imaging (DWI) is a fast, unenhanced technique that has wide clinical applications in breast cancer detection, characterization, prognosis, and predicting treatment response. It also has the potential to serve as a non-contrast MR imaging screening method. Standardized protocols and interpretation strategies can help to enhance the clinical utility of breast DWI. A variety of other promising non-contrast MR imaging techniques are in development, but currently, DWI is closest to clinical integration, while others are still mostly used in the research setting.