Radiation enhancement using focussed ultrasound-stimulated microbubbles for breast cancer: A Phase 1 clinical trial.

BACKGROUND: Preclinical studies have demonstrated that tumour cell death can be enhanced 10- to 40-fold when radiotherapy is combined with focussed ultrasound-stimulated microbubble (FUS-MB) treatment. The acoustic exposure of microbubbles (intravascular gas microspheres) within the target volume causes bubble cavitation, which induces perturbation of tumour vasculature and activates endothelial cell apoptotic pathways responsible for the ablative effect of stereotactic body radiotherapy. Subsequent irradiation of a microbubble-sensitised tumour causes rapid increased tumour death. The study here presents the mature safety and efficacy outcomes of magnetic resonance (MR)-guided FUS-MB (MRgFUS-MB) treatment, a radioenhancement therapy for breast cancer. METHODS AND FINDINGS: This prospective, single-center, single-arm Phase 1 clinical trial included patients with stages I-IV breast cancer with in situ tumours for whom breast or chest wall radiotherapy was deemed adequate by a multidisciplinary team (clinicaltrials.gov identifier: NCT04431674). Patients were excluded if they had contraindications for contrast-enhanced MR or microbubble administration. Patients underwent 2 to 3 MRgFUS-MB treatments throughout radiotherapy. An MR-coupled focussed ultrasound device operating at 800 kHz and 570 kPa peak negative pressure was used to sonicate intravenously administrated microbubbles within the MR-guided target volume. The primary outcome was acute toxicity per Common Terminology Criteria for Adverse Events (CTCAE) v5.0. Secondary outcomes were tumour response at 3 months and local control (LC). A total of 21 female patients presenting with 23 primary breast tumours were enrolled and allocated to intervention between August/2020 and November/2022. Three patients subsequently withdrew consent and, therefore, 18 patients with 20 tumours were included in the safety and LC analyses. Two patients died due to progressive metastatic disease before 3 months following treatment completion and were excluded from the tumour response analysis. The prescribed radiation doses were 20 Gy/5 fractions (40%, n = 8/20), 30 to 35 Gy/5 fractions (35%, n = 7/20), 30 to 40 Gy/10 fractions (15%, n = 3/20), and 66 Gy/33 fractions (10%, n = 2/20). The median follow-up was 9 months (range, 0.3 to 29). Radiation dermatitis was the most common acute toxicity (Grade 1 in 16/20, Grade 2 in 1/20, and Grade 3 in 2/20). One patient developed grade 1 allergic reaction possibly related to microbubbles administration. At 3 months, 18 tumours were evaluated for response: 9 exhibited complete response (50%, n = 9/18), 6 partial response (33%, n = 6/18), 2 stable disease (11%, n = 2/18), and 1 progressive disease (6%, n = 1/18). Further follow-up of responses indicated that the 6-, 12-, and 24-month LC rates were 94% (95% confidence interval [CI] [84%, 100%]), 88% (95% CI [75%, 100%]), and 76% (95% CI [54%, 100%]), respectively. The study's limitations include variable tumour sizes and dose fractionation regimens and the anticipated small sample size typical for a Phase 1 clinical trial. CONCLUSIONS: MRgFUS-MB is an innovative radioenhancement therapy associated with a safe profile, potentially promising responses, and durable LC. These results warrant validation in Phase 2 clinical trials. TRIAL REGISTRATION: clinicaltrials.gov, identifier NCT04431674.

Neoadjuvant chemotherapy for triple-negative and Her2 +ve breast cancer: striving for the standard of care.

PURPOSE: Neoadjuvant chemotherapy (NAC) for triple-negative (TN) and Her2-positive (HER2) breast cancers is supported by international guidelines as it can decrease extent of surgery, provide prognostic information, and allow response-driven adjuvant therapies. Our goal was to describe practice patterns for patients with TN and HER2-positive breast cancer and identify the factors associated with the receipt of NAC versus surgery as initial treatment. METHODS: A retrospective population-based cohort study of adult women diagnosed with stage I-III TN or HER2-positive breast cancer (2012-2020) in Ontario was completed using linked administrative datasets. The primary outcome was NAC as first treatment. The association between NAC and patient, tumor, and practice-related factors was examined using multivariable logistic regression models. RESULTS: Of 14,653 patients included, 23.9% (n = 3500) underwent NAC as first treatment. Patients who underwent NAC were more likely to be younger and have larger tumors, node-positive disease, and stage 3 disease. Of patients who underwent surgery first, 8.8% were seen by a medical oncologist prior to surgery. On multivariable analysis, increasing tumor size (T2 vs T1/T0: 2.75 (2.31-3.28)) and node-positive (N1 vs N0: OR 3.54 (2.92-4.30)) disease were both associated increased odds of receiving NAC. CONCLUSION: A considerable proportion of patients with TN and HER2-positive breast cancer do not receive NAC as first treatment. Of those, most were not assessed by both a surgeon and medical oncologist prior to initiating therapy. This points toward potential gaps in multidisciplinary assessment and disparities in receipt of guideline-concordant care.

Identification of pancreatic cancer risk factors from clinical notes using natural language processing.

OBJECTIVES: Screening for pancreatic ductal adenocarcinoma (PDAC) is considered in high-risk individuals (HRIs) with established PDAC risk factors, such as family history and germline mutations in PDAC susceptibility genes. Accurate assessment of risk factor status is provider knowledge-dependent and requires extensive manual chart review by experts. Natural Language Processing (NLP) has shown promise in automated data extraction from the electronic health record (EHR). We aimed to use NLP for automated extraction of PDAC risk factors from unstructured clinical notes in the EHR. METHODS: We first developed rule-based NLP algorithms to extract PDAC risk factors at the document-level, using an annotated corpus of 2091 clinical notes. Next, we further improved the NLP algorithms using a cohort of 1138 patients through patient-level training, validation, and testing, with comparison against a pre-specified reference standard. To minimize false-negative results we prioritized algorithm recall. RESULTS: In the test set (n = 807), the NLP algorithms achieved a recall of 0.933, precision of 0.790, and F1-score of 0.856 for family history of PDAC. For germline genetic mutations, the algorithm had a high recall of 0.851, while precision and F1-score were lower at 0.350 and 0.496 respectively. Most false positives for germline mutations resulted from erroneous recognition of tissue mutations. CONCLUSIONS: Rule-based NLP algorithms applied to unstructured clinical notes are highly sensitive for automated identification of PDAC risk factors. Further validation in a large primary-care patient population is warranted to assess real-world utility in identifying HRIs for pancreatic cancer screening.

Adherence to NCCN Genetic Testing Guidelines in Pancreatic Cancer and Impact on Treatment.

INTRODUCTION: National Comprehensive Cancer Network (NCCN) 2019 Guidelines recommend universal germline (GL) testing for patients (pts) with pancreatic cancer (PC), given germline mutations (gMut) can occur at a similar rate irrespective of an individual's family history of cancer. Molecular analysis of tumors in those with metastatic disease is also recommended. We aimed to determine rates of genetic testing at our institution, factors associated with testing, and outcomes of those tested. METHODS: Frequency of GL and somatic testing was examined in pts diagnosed with non-endocrine PC, with >2 visits between June 2019 and June 2021 at the Mount Sinai Health System. The clinicopathological variables and treatment outcomes were also recorded. RESULTS: A total of 149 pts met the inclusion criteria. Sixty-six pts (44%) underwent GL testing: 42 (28%) at time of diagnosis with the remainder later in treatment. The rate of GL testing increased every year: 33% (2019), 44% (2020), and 61% (2021). A family history of cancer was the only variable associated with the decision to perform GL testing. Eight pts (12% of pts tested) had pathological gMut: BRCA1 (1), BRCA2 (1), ATM (2), PALB2 (2), NTHL1 (1), both CHEK2 and APC (1). Neither gBRCA pt received a PARP inhibitor, all except one received first-line platinum. Ninety-eight pts (65.7%) had molecular tumor testing (66.7% of patients with metastases). Two pts with BRCA2 somatic mut did not have GL testing. Three pts received targeted therapies. CONCLUSION: Genetic testing based on provider discretion results in low rates of GL testing. Early results of genetic testing can have an impact on treatment decisions and trajectory of disease. Initiatives to increase testing are needed but must be feasible in real-world clinic settings.

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.

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.

Healthcare Worker Mental Health After the Initial Peak of the COVID-19 Pandemic: a US Medical Center Cross-Sectional Survey.

BACKGROUND: There is a paucity of data on the mental health impact of the Coronavirus disease 2019 (COVID-19) pandemic on United States (US) healthcare workers (HCWs) after the first surge in the spring of 2020. OBJECTIVE: To determine the impact of the pandemic on HCWs, and the relationship between HCW mental health and demographics, occupational factors, and COVID-19 concerns. DESIGN: Cross-sectional survey in an urban medical center (September-November 2020) in Baltimore, MD, in the United States. PARTICIPANTS: A total of 605 HCWs (physicians, nurse practitioners, nurses, physician assistants, patient care technicians, respiratory therapists, social workers, mental health therapists, and case managers). MAIN MEASURES: Measures of mental health (Patient Health Questionnaire-2, Generalized Anxiety Disorder-7, PROMIS Sleep Disturbance 4a, Impact of Event Scale-Revised, Maslach Burnout Inventory-2 item, Connor-Davidson Resilience Scale-2 item), demographics, occupational factors, and COVID-19 related concerns. KEY RESULTS: Fifty-two percent of 1198 HCWs responded to the survey and 14.2% reported depression, 43.1% mild or higher anxiety, 31.6% sleep disturbance, 22.3% posttraumatic stress symptoms, 21.6% depersonalization, 46.0% emotional exhaustion, and 23.1% lower resilience. Relative to HCWs providing in-person care to COVID-19 infected patients none of their working days, those doing so all or most days were more likely to experience worse depression (adjusted odds ratio, 3.9; 95% CI, 1.3-11.7), anxiety (aOR, 3.0; 95% CI, 1.4-6.3), possible PTSD symptoms (aOR, 2.6; 95% CI, 1.1-5.8), and higher burnout (aOR, 2.6; 95% CI, 1.1-6.0). Worse mental health in several domains was associated with higher health fear (aORs ranged from 2.2 to 5.0), job stressors (aORs ranged from 1.9 to 4.0), perceived social stigma/avoidance (aORs ranged from 1.8 to 2.9), and workplace safety concerns (aORs ranged from 1.8 to 2.8). CONCLUSIONS: US HCWs experienced significant mental health symptoms eight months into the pandemic. More time spent providing in-person care to COVID-19-infected patients and greater COVID-19-related concerns were consistently associated with worse mental health.

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.

Takotsubo Cardiomyopathy During Anti-HER2 Therapy for Metastatic Breast Cancer.

Human epidermal growth factor receptor 2 (HER2)-targeted antibodies, including pertuzumab and trastuzumab, improve overall survival and progression-free survival among women with HER2-positive metastatic breast cancer, but grade ≥3 cardiotoxicity occurs in approximately 8% of cases. Here we report a case of Takotsubo cardiomyopathy associated with the use of dual anti-HER2 therapy in a 63-year-old woman who presented to the emergency department with an 8- to 10-hour history of progressive dyspnea after completing her third cycle of pertuzumab plus trastuzumab in addition to nab-paclitaxel chemotherapy. To our knowledge, this patient represents the first reported case of Takotsubo cardiomyopathy associated with pertuzumab plus trastuzumab combination therapy in the literature.

User-Centered Design of a Web-Based Tool to Support Management of Chemotherapy-Related Toxicities in Cancer Patients.

BACKGROUND: Cancer patients receiving chemotherapy have high symptom needs that can negatively impact quality of life and result in high rates of unplanned acute care visits. Remote monitoring tools may improve symptom management in this patient population. OBJECTIVE: This study aimed to design a prototype tool to facilitate remote management of chemotherapy-related toxicities. METHODS: User needs were assessed using a participatory, user-centered design methodology that included field observation, interviews, and focus groups, and then analyzed using affinity diagramming. Participants included oncology patients, caregivers, and health care providers (HCPs) including medical oncologists, oncology nurses, primary care physicians, and pharmacists in Ontario, Canada. Overarching themes informed development of a Web-based prototype, which was further refined over 2 rounds of usability testing with end users. RESULTS: Overarching themes were derived from needs assessments, which included 14 patients, 1 caregiver, and 12 HCPs. Themes common to both patients and HCPs included gaps and barriers in current systems, need for decision aids, improved communication and options in care delivery, secure access to credible and timely information, and integration into existing systems. In addition, patients identified missed opportunities, care not meeting their needs, feeling overwhelmed and anxious, and wanting to be more empowered. HCPs identified accountability for patient management as an issue. These themes informed development of a Web-based prototype (bridges), which included toxicity tracking, self-management advice, and HCP communication functionalities. Usability testing with 11 patients and 11 HCPs was generally positive; however, identified challenges included tool integration into existing workflows, need for standardized toxicity self-management advice, issues of privacy and consent, and patient-tailored information. CONCLUSIONS: Web-based tools integrating just-in-time self-management advice and HCP support into routine care may address gaps in systems for managing chemotherapy-related toxicities. Attention to the integration of new electronic tools into self-care by patients and practice was a strong theme for both patients and HCP participants and is a key issue that needs to be addressed for wide-scale adoption.

Prospective Evaluation of the Impact of the 21-Gene Recurrence Score Assay on Adjuvant Treatment Decisions for Women with Node-Positive Breast Cancer in Ontario, Canada.

BACKGROUND: The 21-gene Recurrence Score (RS) assay is only reimbursed in Ontario for node-negative and micrometastatic node-positive (N+) early-stage breast cancer (EBC). We carried out a prospective study to evaluate the impact of the assay on treatment decisions for women with N+ EBC. SUBJECTS, MATERIALS, AND METHODS: Women with estrogen receptor-positive, human epidermal growth receptor 2-negative EBC and one to three positive axillary lymph nodes, who were candidates for adjuvant chemotherapy in addition to hormonal treatment, but in whom the benefit of chemotherapy was uncertain, were eligible. The primary objective was to characterize how the results of the RS assay affected physicians' recommendations for adjuvant chemotherapy. Secondary objectives were to characterize changes in the physicians' and patients' level of confidence in treatment recommendations, to determine whether the results of the RS assay affected patients' treatment preferences, and to determine the final treatment administered. RESULTS: Seventy-two patients were recruited; the mean age was 61. RS was <18 in 55%, between 18 and 30 in 36%, and ≥31 in 9% of patients. Treatment recommendations changed in 36% of all evaluable patients. The most significant change was in the group with a low RS. Physicians' and patients' confidence in treatment recommendations increased in 49% and 54% of cases, respectively. Upfront chemotherapy was recommended to 79% of patients before the assay; 42% ultimately received chemotherapy. CONCLUSION: The RS assay resulted in a substantial decrease in the number of patients who received chemotherapy and in an increase in physicians' and patients' confidence in the adjuvant treatment recommendations. IMPLICATIONS FOR PRACTICE: This is the first decision impact study to include exclusively women with ER-positive, HER2-negative, early-stage breast cancer with 1-3 positive lymph nodes, a population typically treated with adjuvant chemotherapy. This study provides evidence that, in these patients, the Oncotype Dx Recurrence Score assay influences systemic treatment decisions. Most of the changes in treatment recommendation resulted in withdrawal of chemotherapy or change in recommendation from a chemotherapy regimen with anthracyclines to a taxane-only regimen. If prospective studies confirm that these decisions result in good outcomes, a reduction in the use of chemotherapy might result in pharmacoeconomic savings.

Perceived Barriers to Goals of Care Discussions With Patients With Advanced Cancer and Their Families in the Ambulatory Setting: A Multicenter Survey of Oncologists.

BACKGROUND: Earlier goals of care (GOC) discussions in patients with advanced cancer are associated with less aggressive end-of-life care including decreased use of medical technologies. Unfortunately, conversations often occur late in the disease trajectory when patients are acutely unwell. Here, we evaluate practitioner perspectives of patient, family, physician, and external barriers to early GOC discussions in the ambulatory oncology setting. METHODS: A previously published survey to assess barriers to GOC discussions among clinicians on inpatient medical wards was modified for the ambulatory oncology setting and distributed to oncologists from 12 centers in Ontario, Canada. Physicians were asked to rank the importance of various barriers to having GOC discussions (1 = extremely unimportant to 7 = extremely important). RESULTS: Questionnaires were completed by 30 (24%) of 127 physicians. Respondents perceived patient- and family-related factors as the most important barriers to GOC discussions. Of these, patient difficulty accepting prognosis or desire for aggressive treatment were perceived as most important. Patients' inflated expectation of treatment benefit was also considered an important barrier to discontinuing active cancer-directed therapy. While physician barriers were ranked lower than patient-related factors, clinicians' self-identified difficulty estimating prognosis and uncertainty regarding treatment benefits were also considered important. Patient's refusal for referral was the most highly rated barrier to early palliative care referral. Most respondents were nonetheless very or extremely willing to initiate (90%) or lead (87%) GOC discussions. CONCLUSION: Oncologists ranked patient- and family-related factors as the most important barriers to GOC discussions, while clinicians' self-identified difficulty estimating prognosis and uncertainty regarding treatment benefits were also considered important. Further work is required to assess patient preferences and perceptions and develop targeted interventions.

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.

A single-institution experience of salvage therapy for patients with early and locally advanced breast cancer who progress during neoadjuvant chemotherapy.

PURPOSE: Progression during neoadjuvant chemotherapy (NAT) for early and locally advanced breast cancer is generally uncommon. However, these patients tend to do poorly, and salvage therapy (ST) use is variable and often not well defined. We aimed to establish the characteristics and outcomes of breast cancer (BC) patients progressing on NAT, report the patterns of institutional ST usage, and identify predictors of ST failure. METHODS: A retrospective review was conducted using the "Biomatrix" institutional database. Fisher's exact test was used to study the association between baseline characteristics and progression after ST. Survival outcomes were estimated using Kaplan-Meier. Disease-Free Survival 1 (DFS1) and DFS2 represent the time between diagnosis and first progression, and the first and second progression, respectively. The log-rank test was used to compare survival outcomes between different ST types. RESULTS: Thirty patients out of 413 (7.2%) progressed on primary NAT, with a median follow-up of 28.52 months (13.77-46.97) and a mean age of 57 years (standard deviation: 12). The two most frequently used ST modalities were surgery (43%) and radiation with concurrent cisplatin chemotherapy (CT/RT) (40%). Eighty percent of the patients made it to subsequent surgery and among those, 11 (69%) were initially not operable and their tumors were rendered surgically removable after ST. The initial tumor stage and grade, and the presence of lymphovascular invasion predicted progression after ST (p = 0.02, p = 0.03 and p = 0.01, respectively). Median DFS1, DFS2, and overall survival were 4.4 months (95% CI 3.6-5.7), 14.8 months (95% CI 2.37-NR), and 39.5 months (95% CI 22.73-NR), respectively. No difference in survival outcomes based on ST type was seen. CONCLUSION: In this evaluated cohort and despite potential poorer outcomes, patients progressing on NAT responded well to ST, became operable, and had promising survival outcomes. Appropriate selection of ST is crucial, and can help improve outcomes in such patients.

The role of quantitative estrogen receptor status in predicting tumor response at surgery in breast cancer patients treated with neoadjuvant chemotherapy.

PURPOSE: Estrogen receptor (ER) negative (-) breast cancer (BC) patients have better tumor response rates than ER-positive (+) patients after neoadjuvant chemotherapy (NCT). We conducted a retrospective review using the institutional database "Biomatrix" to assess the value of quantitative ER status in predicting tumor response at surgery and to identify potential predictors of survival outcomes. METHODS: Univariate followed by multivariable regression analyses were conducted to assess the association between quantitative ER and tumor response assessed as tumor size reduction and pathologic complete response (pCR). Predictors of recurrence-free survival (RFS) were identified using a cox proportional hazards model (CPH). A log-rank test was used to compare RFS between groups if a significant predictor was identified. RESULTS: 304 patients were included with a median follow-up of 43.3 months (Q1-Q3 28.7-61.1) and a mean age of 49.7 years (SD 10.9). Quantitative ER was inversely associated with tumor size reduction and pCR (OR 0.99, 95% CI 0.99-1.00, p = 0.027 and 0.98 95% CI 0.97-0.99, p < 0.0001, respectively). A cut-off of 60 and 80% predicted best the association with tumor size reduction and pCR, respectively. pCR was shown to be an independent predictor of RFS (HR 0.17, 95% CI 0.07-0.43, p = 0.0002) in all patients. At 5 years, 93% of patients with pCR and 72% of patients with residual tumor were recurrence-free, respectively (p = 0.0012). CONCLUSIONS: Quantitative ER status is inversely associated with tumor response in BC patients treated with NCT. A cut-off of 60 and 80% predicts best the association with tumor size reduction and pCR, respectively. Therefore, patients with an ER status higher than the cut-off might benefit from a neoadjuvant endocrine therapy approach. Patients with pCR had better survival outcomes independently of their tumor phenotype. Further prospective studies are needed to validate the clinical utility of quantitative ER as a predictive marker of tumor response.

Apriori prediction of chemotherapy response in locally advanced breast cancer patients using CT imaging and deep learning: transformer versus transfer learning.

Objective: Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response to NAC for patients with Locally Advanced Breast Cancer (LABC) before treatment initiation could be beneficial to optimize therapy, ensuring the administration of effective treatments. The objective of the work here was to develop a predictive model to predict tumor response to NAC for LABC using deep learning networks and computed tomography (CT). Materials and methods: Several deep learning approaches were investigated including ViT transformer and VGG16, VGG19, ResNet-50, Res-Net-101, Res-Net-152, InceptionV3 and Xception transfer learning networks. These deep learning networks were applied on CT images to assess the response to NAC. Performance was evaluated based on balanced_accuracy, accuracy, sensitivity and specificity classification metrics. A ViT transformer was applied to utilize the attention mechanism in order to increase the weight of important part image which leads to better discrimination between classes. Results: Amongst the 117 LABC patients studied, 82 (70%) had clinical-pathological response and 35 (30%) had no response to NAC. The ViT transformer obtained the best performance range (accuracy = 71 ± 3% to accuracy = 77 ± 4%, specificity = 86 ± 6% to specificity = 76 ± 3%, sensitivity = 56 ± 4% to sensitivity = 52 ± 4%, and balanced_accuracy=69 ± 3% to balanced_accuracy=69 ± 3%) depending on the split ratio of train-data and test-data. Xception network obtained the second best results (accuracy = 72 ± 4% to accuracy = 65 ± 4, specificity = 81 ± 6% to specificity = 73 ± 3%, sensitivity = 55 ± 4% to sensitivity = 52 ± 5%, and balanced_accuracy = 66 ± 5% to balanced_accuracy = 60 ± 4%). The worst results were obtained using VGG-16 transfer learning network. Conclusion: Deep learning networks in conjunction with CT imaging are able to predict the tumor response to NAC for patients with LABC prior to start. A ViT transformer could obtain the best performance, which demonstrated the importance of attention mechanism.

3D CT Radiomic Analysis Improves Detection of Axillary Lymph Node Metastases Compared to Conventional Features in Patients With Locally Advanced Breast Cancer.

OBJECTIVE: Preoperative detection of axillary lymph node metastases (ALNMs) from breast cancer is suboptimal; however, recent work suggests radiomics may improve detection of ALNMs. This study aims to develop a 3D CT radiomics model to improve detection of ALNMs compared to conventional imaging features in patients with locally advanced breast cancer. METHODS: Retrospective chart review was performed on patients referred to a specialty breast cancer center between 2015 and 2020 with US-guided biopsy-proven ALNMs and pretreatment chest CT. One hundred and twelve patients (224 lymph nodes) met inclusion and exclusion criteria and were assigned to discovery (n = 150 nodes) and testing (n = 74 nodes) cohorts. US-biopsy images were referenced in identifying ALNMs on CT, with contralateral nodes taken as negative controls. Positive and negative nodes were assessed for conventional features of lymphadenopathy as well as for 107 radiomic features extracted following 3D segmentation. Diagnostic performance of individual and combined radiomic features was evaluated. RESULTS: The strongest conventional imaging feature of ALNMs was short axis diameter ≥10 mm with a sensitivity of 64%, specificity of 95%, and area under the curve (AUC) of 0.89 (95% CI, 0.84-0.94). Several radiomic features outperformed conventional features, most notably energy, a measure of voxel density magnitude. This feature demonstrated a sensitivity, specificity, and AUC of 91%, 79%, and 0.94 (95% CI, 0.91-0.98) for the discovery cohort. On the testing cohort, energy scored 92%, 81%, and 0.94 (95% CI, 0.89-0.99) for sensitivity, specificity, and AUC, respectively. Combining radiomic features did not improve AUC compared to energy alone (P = .08). CONCLUSION: 3D radiomic analysis represents a promising approach for noninvasive and accurate detection of ALNMs.

Quantitative ultrasound radiomics guided adaptive neoadjuvant chemotherapy in breast cancer: early results from a randomized feasibility study.

Background: In patients with locally advanced breast cancer (LABC) receiving neoadjuvant chemotherapy (NAC), quantitative ultrasound (QUS) radiomics can predict final responses early within 4 of 16-18 weeks of treatment. The current study was planned to study the feasibility of a QUS-radiomics model-guided adaptive chemotherapy. Methods: The phase 2 open-label randomized controlled trial included patients with LABC planned for NAC. Patients were randomly allocated in 1:1 ratio to a standard arm or experimental arm stratified by hormonal receptor status. All patients were planned for standard anthracycline and taxane-based NAC as decided by their medical oncologist. Patients underwent QUS imaging using a clinical ultrasound device before the initiation of NAC and after the 1st and 4th weeks of treatment. A support vector machine-based radiomics model developed from an earlier cohort of patients was used to predict treatment response at the 4th week of NAC. In the standard arm, patients continued to receive planned chemotherapy with the treating oncologists blinded to results. In the experimental arm, the QUS-based prediction was conveyed to the responsible oncologist, and any changes to the planned chemotherapy for predicted non-responders were made by the responsible oncologist. All patients underwent surgery following NAC, and the final response was evaluated based on histopathological examination. Results: Between June 2018 and July 2021, 60 patients were accrued in the study arm, with 28 patients in each arm available for final analysis. In patients without a change in chemotherapy regimen (53 of 56 patients total), the QUS-radiomics model at week 4 of NAC that was used demonstrated an accuracy of 97%, respectively, in predicting the final treatment response. Seven patients were predicted to be non-responders (observational arm (n=2), experimental arm (n=5)). Three of 5 non-responders in the experimental arm had chemotherapy regimens adapted with an early initiation of taxane therapy or chemotherapy intensification, or early surgery and ended up as responders on final evaluation. Conclusion: The study demonstrates the feasibility of QUS-radiomics adapted guided NAC for patients with breast cancer. The ability of a QUS-based model in the early prediction of treatment response was prospectively validated in the current study. Clinical trial registration: clinicaltrials.gov, ID NCT04050228.