Ergonomic wellness for the trainee in gastrointestinal endoscopy.

PURPOSE OF REVIEW: Endoscopy-related injuries (ERIs) are prevalent in gastrointestinal endoscopy. The aim of this review is to address the growing concern of ERIs by evaluating the ergonomic risk factors and the efficacy of interventions and educational strategies aimed at mitigating these risks, including novel approaches. RECENT FINDINGS: ERIs are highly prevalent, exacerbated by factors such as repetitive strain, nonneutral postures, suboptimal equipment design, and the procedural learning curve. Female sex and smaller hand sizes have been identified as specific risk factors. Recent guidelines underscore the importance of ergonomic education and the integration of ergonomic principles into the foundational training of gastroenterology fellows. Advances in equipment design focus on adaptability to different hand sizes and ergonomic positions. Furthermore, the incorporation of microbreaks and macrobreaks, along with neutral monitor and bed positioning, has shown promise in reducing the incidence of ERIs. Wearable sensors may be helpful in monitoring and promoting ergonomic practices among trainees. SUMMARY: Ergonomic wellness is paramount for gastroenterology trainees to prevent ERIs and ensure a sustainable career. Effective strategies include ergonomic education integrated into curricula, equipment design improvements, and procedural adaptations such as scheduled breaks and optimal positioning. Sensor-based and camera-based systems may allow for education and feedback to be provided regarding ergonomics to trainees in the future.

Patient-reported experience with the use of Mepitel Film for prevention of acute radiation dermatitis in breast cancer.

BACKGROUND AND PURPOSE: Mepitel Film (MF) has been demonstrated to reduce the severity of radiation dermatitis (RD) in patients receiving breast cancer radiotherapy (RT). The objective of this study was to characterize patient-reported experience with MF use, including its impact on daily activities and wellbeing. MATERIALS AND METHODS: This single-institution study analyzed anonymized responses to a questionnaire completed by patients who used MF for the prevention of RD during breast cancer RT. RESULTS: Of the 254 patients contacted, 192 patients completed the survey. Most patients disagreed or strongly disagreed that MF limited their ability to perform their daily activities, including household chores (88%, n = 169/191), their ability to work (83%, n = 157/189), or their ability to sleep (85%, n = 163/191). Furthermore, patients agreed or strongly agreed MF was comfortable on their skin (67%, n = 126/189) and protected their skin from rubbing against clothing (86%, n = 161/188). Some patients agreed or strongly agreed that MF affected their ability to shower (31%, n = 50/162), wear bras (28%, n = 51/185), and impacted their level of pruritus (35%, n = 67/189). However, most patients agreed or strongly agreed that their overall experience with MF was positive (92%, n = 173/189) and would recommend MF to a friend undergoing breast cancer RT (88%, n = 166/188). CONCLUSION: MF use is associated with positive patient-reported experience during breast RT with minimal impact on daily activities.

Drivers of Emergency Department Use Among Oncology Patients in the Era of Novel Cancer Therapeutics: A Systematic Review.

BACKGROUND: Patients diagnosed with cancer are frequent users of the emergency department (ED). While many visits are unavoidable, a significant portion may be potentially preventable ED visits (PPEDs). Cancer treatments have greatly advanced, whereby patients may present with unique toxicities from targeted therapies and are often living longer with advanced disease. Prior work focused on patients undergoing cytotoxic chemotherapy, and often excluded those on supportive care alone. Other contributors to ED visits in oncology, such as patient-level variables, are less well-established. Finally, prior studies focused on ED diagnoses to describe trends and did not evaluate PPEDs. An updated systematic review was completed to focus on PPEDs, novel cancer therapies, and patient-level variables, including those on supportive care alone. METHODS: Three online databases were used. Included publications were in English, from 2012-2022, with sample sizes of ≥50, and reported predictors of ED presentation or ED diagnoses in oncology. RESULTS: 45 studies were included. Six studies highlighted PPEDs with variable definitions. Common reasons for ED visits included pain (66%) or chemotherapy toxicities (69.1%). PPEDs were most frequent amongst breast cancer patients (13.4%) or patients receiving cytotoxic chemotherapy (20%). Three manuscripts included immunotherapy agents, and only one focused on end-of-life patients. CONCLUSION: This updated systematic review highlights variability in oncology ED visits during the last decade. There is limited work on the concept of PPEDs, patient-level variables and patients on supportive care alone. Overall, pain and chemotherapy toxicities remain key drivers of ED visits in cancer patients. Further work is needed in this realm.

Perceptions of healthcare professionals on the use of Mepitel Film for the prevention of acute radiation dermatitis in breast cancer.

INTRODUCTION: Randomized clinical trials support Mepitel Film (MF) as a prophylactic treatment for radiation dermatitis (RD) in patients undergoing breast radiotherapy. Although several studies have canvassed the opinion of patients on using MF, no such studies have been done to investigate the perception of healthcare professionals (HCPs). The objective of this study was therefore to investigate the perceptions of HCPs on MF as a treatment option for RD. METHODS: Anonymized responses to a web-based survey sent to HCPs at a single institution managing patients using MF during breast radiotherapy were analyzed. RESULTS: Of the 28 HCPs contacted, 22 completed the survey, including 6 radiation oncologists (ROs), 11 radiation therapists (RTTs), and 5 nurses. Most HCPs reported MF was better at preventing severe RD than the standard of care and improved radiation-induced skin reactions (n = 20/22, 91%, and n = 19/22, 86%, respectively). MF was recommended for mastectomy patients without reconstruction (n = 15/21, 71%). The majority of HCPs believed that patients' families could be trained to apply and remove MF (n = 19/22, 86%). Many HCPs perceived that implementation of MF would be difficult in terms of maintaining patient flow and wide-scale implementation within their institution (n = 11/22, 50%, and n = 10/22, 46%, respectively). Most HCPs perceived that fewer than 50% of their patients could afford MF if priced at $100 CAD (n = 15/20, 75%). CONCLUSION: These findings provide insights into the possibility of MF to be incorporated into standard practice of care for RD. Although most HCPs were satisfied with MF as a prophylactic treatment for RD, there are concerns about its resource-intensive operationalization and financial accessibility to patients. Future research should focus on ways to improve HCP experience with MF and to improve its implementation into clinical settings as standard of care.

A Canadian national guideline on the neoadjuvant treatment of invasive breast cancer, including patient assessment, systemic therapy, and local management principles.

PURPOSE: The neoadjuvant treatment of breast cancer (NABC) is a rapidly changing area that benefits from guidelines integrating evidence with expert consensus to help direct practice. This can optimize patient outcomes by ensuring the appropriate use of evolving neoadjuvant principles. METHODS: An expert panel formulated evidence-based practice recommendations spanning the entire neoadjuvant breast cancer treatment journey. These were sent for practice-based consensus across Canada using the modified Delphi methodology, through a secure online survey. Final recommendations were graded using the GRADE criteria for guidelines. The evidence was reviewed over the course of guideline development to ensure recommendations remained aligned with current relevant data. RESULTS: Response rate to the online survey was almost 30%; representation was achieved from various medical specialties from both community and academic centres in various Canadian provinces. Two rounds of consensus were required to achieve 80% or higher consensus on 59 final statements. Five additional statements were added to reflect updated evidence but not sent for consensus. CONCLUSIONS: Key highlights of this comprehensive Canadian guideline on NABC include the use of neoadjuvant therapy for early stage triple negative and HER2 positive breast cancer, with subsequent adjuvant treatments for patients with residual disease. The use of molecular signatures, other targeted adjuvant therapies, and optimal response-based local regional management remain actively evolving areas. Many statements had evolving or limited data but still achieved high consensus, demonstrating the utility of such a guideline in helping to unify practice while further evidence evolves in this important area of breast cancer management.

Treatment Patterns and Outcomes of Women with Symptomatic and Asymptomatic Breast Cancer Brain Metastases: A Single-Center Retrospective Study.

BACKGROUND: Breast cancer is the most common cancer among women worldwide and the second leading cause of brain metastases (BrM). We assessed the treatment patterns and outcomes of women treated for breast cancer BrM at our institution in the modern era of stereotactic radiosurgery (SRS). MATERIALS AND METHODS: We conducted a retrospective analysis of women (≥18 years of age) with metastatic breast cancer who were treated with surgery, whole brain radiotherapy (WBRT), or SRS to the brain at the Sunnybrook Odette Cancer Centre, Toronto, Canada, between 2008 and 2018. Patients with a history of other malignancies and those with an uncertain date of diagnosis of BrM were excluded. Descriptive statistics were generated and survival analyses were performed with subgroup analyses by breast cancer subtype. RESULTS: Among 683 eligible patients, 153 (22.4%) had triple-negative breast cancer, 188 (27.5%) had HER2+, 246 (36.0%) had hormone receptor (HR)+/HER2-, and 61 (13.3%) had breast cancer of an unknown subtype. The majority of patients received first-line WBRT (n = 459, 67.2%) or SRS (n = 126, 18.4%). The median brain-specific progression-free survival and median overall survival (OS) were 4.1 months (interquartile range [IQR] 1.0-9.6 months) and 5.1 months (IQR 2.0-11.7 months) in the overall patent population, respectively. Age >60 years, presence of neurological symptoms at BrM diagnosis, first-line WBRT, and HER2- subtype were independently prognostic for shorter OS. CONCLUSION: Despite the use of SRS, outcomes among patients with breast cancer BrM remain poor. Strategies for early detection of BrM and central nervous system-active systemic therapies warrant further investigation. IMPLICATIONS FOR PRACTICE: Although triple-negative breast cancer and HER2+ breast cancer have a predilection for metastasis to the central nervous system (CNS), patients with hormone receptor-positive/HER2- breast cancer represent a high proportion of patients with breast cancer brain metastases (BrM). Hence, clinical trials should include patients with BrM and evaluate CNS-specific activity of novel systemic therapies when feasible, irrespective of breast cancer subtype. In addition, given that symptomatic BrM are associated with shorter survival, this study suggests that screening programs for the early detection and treatment of breast cancer BrM warrant further investigation in an era of minimally toxic stereotactic radiosurgery.

Analysis of tumor nuclear features using artificial intelligence to predict response to neoadjuvant chemotherapy in high-risk breast cancer patients.

PURPOSE: Neoadjuvant chemotherapy (NAC) is used to treat patients with high-risk breast cancer. The tumor response to NAC can be classified as either a pathological partial response (pPR) or pathological complete response (pCR), defined as complete eradication of invasive tumor cells, with a pCR conferring a significantly lower risk of recurrence. Predicting the response to NAC, however, remains a significant clinical challenge. The objective of this study was to determine if analysis of nuclear features on core biopsies using artificial intelligence (AI) can predict response to NAC. METHODS: Fifty-eight HER2-positive or triple-negative breast cancer patients were included in this study (pCR n = 37, pPR n = 21). Multiple deep convolutional neural networks were developed to automate tumor detection and nuclear segmentation. Nuclear count, area, and circularity, as well as image-based first- and second-order features including mean pixel intensity and correlation of the gray-level co-occurrence matrix (GLCM-COR) were determined. RESULTS: In univariate analysis, the pCR group had fewer multifocal/multicentric tumors, higher nuclear intensity, and lower GLCM-COR compared to the pPR group. In multivariate binary logistic regression, tumor multifocality/multicentricity (OR = 0.14, p = 0.012), nuclear intensity (OR = 1.23, p = 0.018), and GLCM-COR (OR = 0.96, p = 0.043) were each independently associated with likelihood of achieving a pCR, and the model was able to successful classify 79% of cases (62% for pPR and 89% for pCR). CONCLUSION: Analysis of tumor nuclear features using digital pathology/AI can significantly improve models to predict pathological response to NAC.

Budget Impact Analysis of Preoperative Radioactive Seed Localization.

BACKGROUND: This study models costs in implementing a radioactive seed localization (RSL) program for nonpalpable breast lesions at a large Canadian tertiary hospital to replace existing wire-guided localization (WGL). METHODS: All direct and indirect operating costs of localization per lesion from the hospital's perspective were determined by retrospectively reviewing patient data and costs from January 2014 to December 2016. A budget impact analysis and sensitivity analysis were performed to calculate the mean cost per lesion, the minimum and maximum cost per lesion, operational costs, and initial costs. RESULTS: There were 265 WGL lesions in 2014 and 170 RSL lesions in 2016 included in cost calculation. The mean cost per localization was $185 CAD for WGL ($148-$311) and $283 CAD ($245-$517) for RSL using preloaded seeds, adjusted to 2016 Canadian dollars. The annual operational expenditure including all localizations and overhead costs was $49,835 for WGL and $80,803 for RSL. Initial costs for RSL were $22,000, including external training and new equipment purchases. CONCLUSIONS: Our budget impact analysis shows that RSL using preloaded radioactive seeds was more expensive than WGL when considering per-lesion localization costs and specific costs related to radiation safety. Manually loading radioactive seed could be a cost-saving alternative to purchasing preloaded seeds. Our breakdown of costs can provide a framework for other centres to determine which localization method best suit their departments.

Computational Radiology in Breast Cancer Screening and Diagnosis Using Artificial Intelligence.

Breast cancer screening has been shown to significantly reduce mortality in women. The increased utilization of screening examinations has led to growing demands for rapid and accurate diagnostic reporting. In modern breast imaging centers, full-field digital mammography (FFDM) has replaced traditional analog mammography, and this has opened new opportunities for developing computational frameworks to automate detection and diagnosis. Artificial intelligence (AI), and its subdomain of deep learning, is showing promising results and improvements on diagnostic accuracy, compared to previous computer-based methods, known as computer-aided detection and diagnosis.In this commentary, we review the current status of computational radiology, with a focus on deep neural networks used in breast cancer screening and diagnosis. Recent studies are developing a new generation of computer-aided detection and diagnosis systems, as well as leveraging AI-driven tools to efficiently interpret digital mammograms, and breast tomosynthesis imaging. The use of AI in computational radiology necessitates transparency and rigorous testing. However, the overall impact of AI to radiology workflows will potentially yield more efficient and standardized processes as well as improve the level of care to patients with high diagnostic accuracy.

Effect of Treatment Sequencing on the Tumor Response to Combined Treatment With Ultrasound-Stimulated Microbubbles and Radiotherapy.

OBJECTIVES: To investigate whether timing and sequencing of ultrasound-stimulated microbubbles (USMBs) and external beam radiotherapy (XRT) affect the treatment response in a preclinical prostate cancer model. METHODS: Prostate cancer xenografts were treated with ultrasound-stimulated lipid microspheres before and after 8-Gy XRT. Treatments were separated by 0, 3, 6, 12, and 24 hours, with 5 tumors per group. Tumor effects were evaluated by microvessel density (measured by CD31 staining), cell death (terminal deoxynucleotidyl transferase deoxyuridine triphosphate nick end-labeling and hematoxylin-eosin staining), and hypoxia (carbonic anhydrase 9 staining). RESULTS: Administering USMBs 6 hours before XRT showed the maximum treatment effect using all 3 assays. At this time, the mean cell death index ± SD was 36% ± 10%, compared with 19% ± 4% for no separation between USMB treatment and XRT; the microvessel density was 9 ± 3 counts per field (19 ± 5 without separation); and the percentage of hypoxic cells was 10% ± 5% (21% ± 4%). The observed treatment effect was greater with USMBs before XRT than when administering XRT first, but these differences were not statistically significant. CONCLUSIONS: The maximum tumor effect was observed with USMBs delivered 6 hours before XRT. The sequencing of treatment did not have a significant effect on the tumor response.

Locally advanced breast cancer treated with neoadjuvant chemotherapy and adjuvant radiotherapy: a retrospective cohort analysis.

BACKGROUND: Neoadjuvant chemotherapy (NAC) is increasingly used to treat locally advanced breast cancer (LABC). Improved response to NAC correlates with better survival outcomes. The dual purpose of this study is to report recurrence and survival outcomes for LABC patients treated with NAC, surgery and adjuvant radiotherapy and to correlate these outcomes with tumour response after NAC using multiple response assessment methods. METHODS: All LABC patients treated for curative intent with NAC, surgery, and adjuvant radiotherapy at our institute between January 2009 and December 2014 were included for analysis. NAC was mostly anthracycline and taxane-based; radiotherapy consisted of 50 Gy to the breast/chest wall and regional lymph nodes. Response to NAC was categorized using synoptic pathology reports, modified-RECIST and Chevallier scores. Survival curves were generated by the Kaplan-Meier method and compared using the log-rank test. RESULTS: The cohort included 103 patients nearly equally divided between Stage II (n = 53) and Stage III (n = 50). Rates of locoregional control (LRC), recurrence-free survival (RFS), and overall survival (OS) were 99, 98, and 100% at 1 year and 89, 69 and 77% at 5 years, respectively. Responses to NAC did not correlate with LRC (p > 0.05) but did correlate with RFS and OS (p < 0.05), except that the Chevallier score did not predict RFS (p = 0.06). Using bivariate Cox modeling tumour size before (p = 0.003) and after (p < 0.001) NAC, stage group (p = 0.05), and response assessed by synoptic pathology (p = 0.05), modified-RECIST (p = 0.001), and Chevallier score (p = 0.015) all predicted for RFS. No factors predicted for LRC. CONCLUSION: Pathologic response by all tested methods correlated with improved survival but were not associated with decreased LRC.

Predicting breast cancer response to neoadjuvant chemotherapy using pretreatment diffuse optical spectroscopic texture analysis.

BACKGROUND: Diffuse optical spectroscopy (DOS) has been demonstrated capable of monitoring response to neoadjuvant chemotherapy (NAC) in locally advanced breast cancer (LABC) patients. In this study, we evaluate texture features of pretreatment DOS functional maps for predicting LABC response to NAC. METHODS: Locally advanced breast cancer patients (n=37) underwent DOS breast imaging before starting NAC. Breast tissue parametric maps were constructed and texture analyses were performed based on grey-level co-occurrence matrices for feature extraction. Ground truth labels as responders (R) or non-responders (NR) were assigned to patients based on Miller-Payne pathological response criteria. The capability of DOS textural features computed on volumetric tumour data before the start of treatment (i.e., 'pretreatment') to predict patient responses to NAC was evaluated using a leave-one-out validation scheme at subject level. Data were analysed using a logistic regression, naive Bayes, and k-nearest neighbour classifiers. RESULTS: Data indicated that textural characteristics of pretreatment DOS parametric maps can differentiate between treatment response outcomes. The HbO2 homogeneity resulted in the highest accuracy among univariate parameters in predicting response to chemotherapy: sensitivity (%Sn) and specificity (%Sp) were 86.5% and 89.0%, respectively, and accuracy was 87.8%. The highest predictors using multivariate (binary) combination features were the Hb-contrast+HbO2-homogeneity, which resulted in a %Sn/%Sp=78.0/81.0% and an accuracy of 79.5%. CONCLUSIONS: This study demonstrated that the pretreatment DOS texture features can predict breast cancer response to NAC and potentially guide treatments.

Tumor radiation response enhancement by acoustical stimulation of the vasculature.

We have discovered that ultrasound-mediated microbubble vascular disruption can enhance tumor responses to radiation in vivo. We demonstrate this effect using a human PC3 prostate cancer xenograft model. Results indicate a synergistic effect in vivo with combined single treatments of ultrasound-stimulated microbubble vascular perturbation and radiation inducing an over 10-fold greater cell kill with combined treatments. We further demonstrate with experiments in vivo that induction of ceramide-related endothelial cell apoptosis, leading to vascular disruption, is a causative mechanism. In vivo experiments with ultrasound and bubbles permit radiation doses to be decreased significantly for comparable effect. We envisage this unique combined ultrasound-based vascular perturbation and radiation treatment method being used to enhance the effects of radiation in a tumor, leading to greater tumor eradication.

Sunitinib effects on the radiation response of endothelial and breast tumor cells.

BACKGROUND: Endothelial cells are suggested regulators of tumor response to radiation. Anti-vascular targeting agents can enhance tumor response by targeting endothelial cells. Here, we have conducted experiments in vitro to discern the effects of radiation combined with the anti-angiogenic Sunitinib on endothelial (HUVEC) and tumor (MDA-MB-231) cells, and further compared findings to results obtained in vivo. METHODS: In vitro and in vivo treatments consisted of single dose radiation therapy of 2, 4, 8 or 16 Gy administered alone or in combination with bFGF or Sunitinib. In vitro, in situ end labeling (ISEL) was used to assess 24-hour apoptotic cell death, and clonogenic assays were used to assess long-term response. In vivo MDA-MB-231 tumors were grown in CB-17 SCID mice. The vascular marker CD31 was used to assess 24-hour acute response while tumor clonogenic assays were used to assess long-term tumor cell viability following treatments. RESULTS: Using in vitro studies, we observed an enhanced endothelial cell response to radiation doses of 8 and 16 Gy when compared to tumor cells. Administering Sunitinib alone significantly increased HUVEC cell death, while having modest additive effects when combined with radiation. Sunitinib also increased tumor cell death when combined with 8 and 16 Gy radiation doses. In comparison, we found that the clonogenic response of in vivo treated tumor cells more closely resembled that of in vitro treated endothelial cells than in vitro treated tumor cells. CONCLUSION: Our results indicate that the endothelium is an important regulator of tumor response to radiotherapy, and that Sunitinib can enhance tumor radiosensitivity. To the best of our knowledge, this is the first time that Sunitinib is investigated in combination with radiotherapy on the MDA-MB-231 breast cancer cell line.

Quantitative US Delta Radiomics to Predict Radiation Response in Individuals with Head and Neck Squamous Cell Carcinoma.

Purpose To investigate the role of quantitative US (QUS) radiomics data obtained after the 1st week of radiation therapy (RT) in predicting treatment response in individuals with head and neck squamous cell carcinoma (HNSCC). Materials and Methods This prospective study included 55 participants (21 with complete response [median age, 65 years {IQR: 47-80 years}, 20 male, one female; and 34 with incomplete response [median age, 59 years {IQR: 39-79 years}, 33 male, one female) with bulky node-positive HNSCC treated with curative-intent RT from January 2015 to October 2019. All participants received 70 Gy of radiation in 33-35 fractions over 6-7 weeks. US radiofrequency data from metastatic lymph nodes were acquired prior to and after 1 week of RT. QUS analysis resulted in five spectral maps from which mean values were extracted. We applied a gray-level co-occurrence matrix technique for textural analysis, leading to 20 QUS texture and 80 texture-derivative parameters. The response 3 months after RT was used as the end point. Model building and evaluation utilized nested leave-one-out cross-validation. Results Five delta (Δ) parameters had statistically significant differences (P < .05). The support vector machines classifier achieved a sensitivity of 71% (15 of 21), a specificity of 76% (26 of 34), a balanced accuracy of 74%, and an area under the receiver operating characteristic curve of 0.77 on the test set. For all the classifiers, the performance improved after the 1st week of treatment. Conclusion A QUS Δ-radiomics model using data obtained after the 1st week of RT from individuals with HNSCC predicted response 3 months after treatment completion with reasonable accuracy. Keywords: Computer-Aided Diagnosis (CAD), Ultrasound, Radiation Therapy/Oncology, Head/Neck, Radiomics, Quantitative US, Radiotherapy, Head and Neck Squamous Cell Carcinoma, Machine Learning Clinicaltrials.gov registration no. NCT03908684 Supplemental material is available for this article. © RSNA, 2024.

Glass microspargers as effective frit spargers in single use bioreactors.

For multiple-use bench scale and larger bioreactors, sintered stainless steel frit spargers are commonly used as microspargers. For bench-scale single-use bioreactors (SUBs), existing microspargers are sintered plastics, such as polyethylene. However, though plastics are readily sterilized by irradiation making them convenient for single use, these designs overlook surface energy properties of the materials of construction. For these sintered plastic spargers, forces at the water-air-surface interface cause bubble coalescence, leading to lower effective mass transfer, higher gas flow rates, and differing pCO2 profiles in cell culture. Alternative materials of construction were evaluated based on contact angle information and bubble formation observations. Sintered glass was chosen over thermoplastic polymers for higher surface wettability as described in the glass/water contact angle, its history as a commonly sintered material, and availability at costs suitable for single use applications. Glass sintered spargers and traditional stainless steel frit spargers were compared by porosity, bubble size, and kL a studies. Mass transfer (kL a) and cell culture performance equal or greater than a standard 20 µm stainless steel microsparger mass transfer efficiency was achieved by a glass frit sparger, of international porosity standard "P40" according to ISO 4793-80, which corresponds to a range of 16-40 µm.

A hierarchical self-attention-guided deep learning framework to predict breast cancer response to chemotherapy using pre-treatment tumor biopsies.

BACKGROUND: Pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) has demonstrated a strong correlation to improved survival in breast cancer (BC) patients. However, pCR rates to NAC are less than 30%, depending on the BC subtype. Early prediction of NAC response would facilitate therapeutic modifications for individual patients, potentially improving overall treatment outcomes and patient survival. PURPOSE: This study, for the first time, proposes a hierarchical self-attention-guided deep learning framework to predict NAC response in breast cancer patients using digital histopathological images of pre-treatment biopsy specimens. METHODS: Digitized hematoxylin and eosin-stained slides of BC core needle biopsies were obtained from 207 patients treated with NAC, followed by surgery. The response to NAC for each patient was determined using the standard clinical and pathological criteria after surgery. The digital pathology images were processed through the proposed hierarchical framework consisting of patch-level and tumor-level processing modules followed by a patient-level response prediction component. A combination of convolutional layers and transformer self-attention blocks were utilized in the patch-level processing architecture to generate optimized feature maps. The feature maps were analyzed through two vision transformer architectures adapted for the tumor-level processing and the patient-level response prediction components. The feature map sequences for these transformer architectures were defined based on the patch positions within the tumor beds and the bed positions within the biopsy slide, respectively. A five-fold cross-validation at the patient level was applied on the training set (144 patients with 9430 annotated tumor beds and 1,559,784 patches) to train the models and optimize the hyperparameters. An unseen independent test set (63 patients with 3574 annotated tumor beds and 173,637 patches) was used to evaluate the framework. RESULTS: The obtained results on the test set showed an AUC of 0.89 and an F1-score of 90% for predicting pCR to NAC a priori by the proposed hierarchical framework. Similar frameworks with the patch-level, patch-level + tumor-level, and patch-level + patient-level processing components resulted in AUCs of 0.79, 0.81, and 0.84 and F1-scores of 86%, 87%, and 89%, respectively. CONCLUSIONS: The results demonstrate a high potential of the proposed hierarchical deep-learning methodology for analyzing digital pathology images of pre-treatment tumor biopsies to predict the pathological response of breast cancer to NAC.

Individualising radiation therapy decisions in breast cancer patients based on tumour infiltrating lymphocytes and genomic biomarkers.

Radiation therapy (RT) has long been fundamental for the curative treatment of breast cancer. While substantial progress has been made in the anatomical and technological precision of RT delivery, and some approaches to de-escalate or omit RT based on clinicopathologic features have been successful, there remain substantial opportunities to refine individualised RT based on tumour biology. A major area of clinical and research interest is to ascertain the individualised risk of loco-regional recurrence to direct treatment decisions regarding escalation and de-escalation of RT. Patient-tailored treatment with RT is considerably lagging behind compared with the massive progress made in the field of personalised medicine that currently mainly applies to decisions on the use of systemic therapy or targeted agents. Herein we review select literature surrounding the use of tumour genomic biomarkers and biomarkers of the immune system, including tumour infiltrating lymphocytes (TILs), within the management of breast cancer, specifically as they relate to progress in moving toward analytically validated and clinically tested biomarkers utilized in RT.

Machine learning analysis of breast ultrasound to classify triple negative and HER2+ breast cancer subtypes.

OBJECTIVES: Early diagnosis of triple-negative (TN) and human epidermal growth factor receptor 2 positive (HER2+) breast cancer is important due to its increased risk of micrometastatic spread necessitating early treatment and for guiding targeted therapies. This study aimed to evaluate the diagnostic performance of machine learning (ML) classification of newly diagnosed breast masses into TN versus non-TN (NTN) and HER2+ versus HER2 negative (HER2-) breast cancer, using radiomic features extracted from grayscale ultrasound (US) b-mode images. MATERIALS AND METHODS: A retrospective chart review identified 88 female patients who underwent diagnostic breast US imaging, had confirmation of invasive malignancy on pathology and receptor status determined on immunohistochemistry available. The patients were classified as TN, NTN, HER2+ or HER2- for ground-truth labelling. For image analysis, breast masses were manually segmented by a breast radiologist. Radiomic features were extracted per image and used for predictive modelling. Supervised ML classifiers included: logistic regression, k-nearest neighbour, and Naïve Bayes. Classification performance measures were calculated on an independent (unseen) test set. The area under the receiver operating characteristic curve (AUC), sensitivity (%), and specificity (%) were reported for each classifier. RESULTS: The logistic regression classifier demonstrated the highest AUC: 0.824 (sensitivity: 81.8%, specificity: 74.2%) for the TN sub-group and 0.778 (sensitivity: 71.4%, specificity: 71.6%) for the HER2 sub-group. CONCLUSION: ML classifiers demonstrate high diagnostic accuracy in classifying TN versus NTN and HER2+ versus HER2- breast cancers using US images. Identification of more aggressive breast cancer subtypes early in the diagnostic process could help achieve better prognoses by prioritizing clinical referral and prompting adequate early treatment.

Novel MRI-guided focussed ultrasound stimulated microbubble radiation enhancement treatment for breast cancer.

Preclinical studies have demonstrated focused ultrasound (FUS) stimulated microbubble (MB) rupture leads to the activation of acid sphingomyelinase-ceramide pathway in the endothelial cells. When radiotherapy (RT) is delivered concurrently with FUS-MB, apoptotic pathway leads to increased cell death resulting in potent radiosensitization. Here we report the first human trial of using magnetic resonance imaging (MRI) guided FUS-MB treatment in the treatment of breast malignancies. In the phase 1 prospective interventional study, patients with breast cancer were treated with fractionated RT (5 or 10 fractions) to the disease involving breast or chest wall. FUS-MB treatment was delivered before 1st and 5th fractions of RT (within 1 h). Eight patients with 9 tumours were treated. All 7 evaluable patients with at least 3 months follow-up treated for 8 tumours had a complete response in the treated site. The maximum acute toxicity observed was grade 2 dermatitis in 1 site, and grade 1 in 8 treated sites, at one month post RT, which recovered at 3 months. No RT-related late effect or FUS-MB related toxicity was noted. This study demonstrated safety of combined FUS-MB and RT treatment. Promising response rates suggest potential strong radiosensitization effects of the investigational modality.Trial registration: clinicaltrials.gov, identifier NCT04431674.