This study assessed the level of agreement between quantitative ultrasound (QUS) feature estimates derived from ultrasound images of breast tumors in women with locally advanced breast cancer (LABC) produced using a cart-based and a handheld ultrasound system. Thirty LABC patients receiving neoadjuvant chemotherapy were imaged at two separate times: a pre-treatment ‘baseline’ time point, and four weeks after the start of chemotherapy. Three sets of QUS features were produced using the reference phantom technique, one for each imaging time and a third set calculated by taking the differences in feature estimates between times. Cross-system statistical testing using the Wilcoxon signed-rank test was performed for each feature set to assess the level of feature estimate agreement between ultrasound systems. The Bland–Altman method was employed to graphically assess feature sets for systematic skew. The range of p-values was 4.50 × 10−11 to 0.277 for the baseline features, 2.77 × 10−5 to 0.865 for the week 4 features, and 2.03 × 10−9 to 1 for the feature differences. For the feature differences, all five of the primary QUS features (MBF, SS, SI, ASD, AAC) were found to be in agreement between the two scanner types at the 5% confidence level. For the baseline feature set and week 4 feature set, 0 out of 5 and 3 out of 5 of the primary features were found to be in agreement, respectively. Of the 20 QUS texture features examined, the number and proportion of the total for each feature set which were found to have statistically significant similarity in their sample medians at the 5% confidence level were as follows: 2 out of 20 (10%) for the baseline features; 17 out of 20 (85%) for the week 4 features; and 12 out of 20 (60%) for the feature differences. The specific texture features found to be in agreement varied between QUS-specific feature sets. Overall, a moderate level of agreement between sets of feature differences produced using the two systems was demonstrated.

ImportanceHead and neck cancers (HNC) impose a significant economic burden on healthcare systems. Understanding the direct medical costs across different phases of care is crucial for resource allocation and cost-effectiveness evaluations, particularly in universal healthcare settings.ObjectiveTo quantify the direct medical costs of HNC over 60 months postdiagnosis and examine cost variations by cancer subsite, stage, and treatment modality.DesignPopulation-based, matched case-control study using administrative healthcare data.SettingOntario, Canada, a province with a publicly funded universal healthcare system.ParticipantsWe included 19,832 adults diagnosed with HNC between 2007 and 2020. Each case was matched with 5 noncancer controls based on age, sex, and comorbidity.ExposuresHNC diagnosis, categorized by cancer subsite, stage, and treatment modality.Main Outcome MeasuresMean per-person direct medical costs attributable to HNC over a 63-month period, analyzed by phase of care, cancer subsite, stage, and treatment modality.ResultsThe mean per-person cost attributable to HNC over 63 months was $53,812.9 ± $762.2. Costs peaked in the first 3 months postdiagnosis ($9709.7 ± $36.1 per month) and declined over time. Larynx/hypopharynx cancers incurred the highest costs across most phases. Advanced-stage cancers were associated with increased costs, with stage IV cancers nearly doubling the costs of stage I. Multimodal treatments, particularly surgery combined with chemoradiation, resulted in the highest costs across all phases (P < .01).ConclusionsHNC results in substantial healthcare costs, with significant variations by subsite, stage, and treatment modality. The highest costs occur in the early treatment phase and remain elevated for patients requiring multimodal therapies.RelevanceThese findings provide critical data for policymakers and health system authorities to optimize resource allocation and assess cost-effectiveness. Future research should explore indirect costs and the impact of early detection strategies to reduce the economic burden of HNC.Level of evidence3.

Surgical system decision-makers are confronted with the challenge of justifying investment in new surgical facilities against expanding the capacity of existing ones, and if worthwhile, where to place such new facilities. Geospatial analysis can provide findings to inform this decision. This scoping review examines how geospatial analysis has been used to identify geographically defined populations experiencing an inequitable access to surgical care to inform the care structures and processes. A comprehensive literature search was performed in November 2024 using the MEDLINE, EMBASE, Scopus, and PubMed databases for English-language peer-reviewed journal articles that carried out geospatial analysis of surgical care and identified geographic locations in need of resource allocations. Two reviewers independently screened studies for inclusion and extracted the data. Studies were summarized based on their findings and analytical methods. Of the nineteen studies included, three types of findings were presented: 1) two studies determined optimal locations for a new surgical facility; 2) six studies recommended strengthening the capacity of existing facilities after ruling out the need to build new ones, and 3) eleven studies identified locations that should be prioritized for resource allocation (e.g., more surgeons) without examining the need for new facilities or the possibility of strengthening existing ones. Gaps in the literature were identified to include a lack of explicit justification and identification of optimal sites for ambulatory surgical centers, use of dated registry data and potentially unreliable self-report data, and a lack of using the most appropriate geospatial techniques to answer surgical care planning questions according to the local context. Practical recommendations on geospatial analysis in surgical research are provided.

Rationale: Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response of NAC for patients with LABC before initiating treatment would be valuable to customize therapies and ensure the delivery of effective care. Objective: Our objective was to develop predictive measures of tumor response to NAC prior to starting for LABC using machine learning and textural computed tomography (CT) features in different level of frequencies. Materials and Methods: A total of 851 textural biomarkers were determined from CT images and their wavelet coefficients for 117 patients with LABC to evaluate the response to NAC. A machine learning pipeline was designed to classify response to NAC treatment for patients with LABC. For training predictive models, three models including all features (wavelet and original image features), only wavelet and only original-image features were considered. We determined features from CT images in different level of frequencies using wavelet transform. Additionally, we conducted a comparison of feature selection methods including mRMR, Relief, Rref QR decomposition, nonnegative matrix factorization and perturbation theory feature selection techniques. Results: Of the 117 patients with LABC evaluated, 82 (70%) had clinical–pathological response to chemotherapy and 35 (30%) had no response to chemotherapy. The best performance for hold-out data splitting was obtained using the KNN classifier using the Top-5 features, which were obtained by mRMR, for all features (accuracy = 77%, specificity = 80%, sensitivity = 56%, and balanced-accuracy = 68%). Likewise, the best performance for leave-one-out data splitting could be obtained by the KNN classifier using the Top-5 features, which was obtained by mRMR, for all features (accuracy = 75%, specificity = 76%, sensitivity = 62%, and balanced-accuracy = 72%). Conclusions: The combination of original textural features and wavelet features results in a greater predictive accuracy of NAC response for LABC patients. This predictive model can be utilized to predict treatment outcomes prior to starting, and clinicians can use it as a recommender system to modify treatment.

Sentinel lymph node biopsy (SLNB) after neoadjuvant chemotherapy (NAC) is recommended for patients initially presenting with cN1 disease and evidence of clinical/imaging response after NAC. We aimed to describe real-world population changes in management. We completed a population-based cohort study including adult women undergoing NAC followed by surgery for cT1-3N1 breast cancer between 1 April 2012 and 31 January 2020 in Ontario, Canada. Axillary surgeries (SLNB, axillary lymph node dissection [ALND], or SLNB followed by ALND) were studied over time using the Cochran–Armitage test, while multivariable logistic regression evaluated factors associated with surgery type. Overall, 2563 patients were analyzed (37.9

BACKGROUND:Despite numerous randomized controlled trials finding that albumin is not associated with improved patient outcomes, transfusion practice is highly variable. We examined the variability and impact of albumin transfusion on outcomes in cancer surgery. METHODS:We included consecutive adults undergoing cancer surgery between 2018 and 2021 in Ontario, Canada. The primary exposure was the proportion of patients who received perioperative albumin. The secondary outcomes were hospital length of stay and the incidence of infection, anemia, venous thromboembolism, and mortality in albumin-treated versus non-albumin-treated patients in a case-control analysis. RESULTS:Of 155 166 cancer surgeries (66.8% female patients, median age 62.9 yr), 2.5% received perioperative albumin. The cancer surgery types with the highest proportion of patients receiving albumin were hepato-pancreato-biliary (24.8%) and colorectal (18.6%). Of 104 facilities, 12.5% had nonrandom outliers for albumin use in at least 1 cancer type (p = 0.0004). Patient outcomes were different in case-control matched cohorts for colorectal and hepato-pancreato-biliary surgeries, including a higher rate of infection, venous thromboembolism, and mortality in patients treated with albumin (cases) than those who were not (controls). CONCLUSION:Albumin transfusion rates were highly variable among hospitals for the same cancer type. Quality improvement initiatives are warranted to curtail unnecessary albumin transfusions in the perioperative period.

Importance:Head and neck cancer (HNC) and its associated treatments are associated with substantial functional, psychological, and financial consequences. Patient-reported outcome measures (PROMs) play a crucial role in capturing the full impact of disease. Understanding how PROMs are associated with health care costs is critical for cancer care planning; however, the association of health care expenditure and PROMs is yet to be clarified. Objective:To assess the association between Edmonton Symptom Assessment System (ESAS) scores and direct health care costs incurred in 30 days for adult patients with HNC. Design, Setting, and Participants:This cohort study used linked administrative datasets from Ontario, Canada, of adult patients who received a diagnosis of HNC between January 1, 2007, and December 31, 2022. Included patients had at least 1 ESAS assessment completed from the date of diagnosis to the date of death or January 31, 2023. Coprimary exposures were the highest individual symptom score (h-ESAS, from 0 to 10) and the sum total of the individual scores of the 9 symptoms (t-ESAS, from 0-90). Multivariable negative binomial regression models using a generalized estimating equation approach under an exchangeable correlation structure were used to assess the association between each primary exposure and 30-day costs, accounting for patient age, sex, immigration status, socioeconomic status, cancer type, and recent cancer-directed treatment modality, updated to each ESAS assessment date. Data analysis was performed from September 2024 to February 2025. Main Outcomes and Measures:A 30-day cost-capturing window was defined around each ESAS assessment date to comprise a 7-day interval before this date and a 22-day interval after this date. Direct health care costs incurred during this 30-day window were estimated using a patient-level case-costing algorithm adjusted to 2023 Canadian dollars. Results:The total sample population was 16 544 adult patients with HNC (mean [SD] age at diagnosis, 63.7 [11.5] y; 12 526 [75.7%] male individuals ) and their 90 025 ESAS assessments completed since the date of diagnosis. Each 1-point increase in h-ESAS was associated with a 22% increase in 30-day costs (rate ratio [RR], 1.22; 95% CI, 1.21-1.22). Likewise, relative costs increased progressively with higher t-ESAS scores, peaking among patients with scores of 71 to 80 (RR, 4.82; 95% CI, 4.32-5.39). Conclusions and Relevance:This cohort study found that both h-ESAS and t-ESAS were significantly associated with 30-day costs. These findings highlight the potential role of PROMs in cost-mitigation strategies for HNC care.

Objectives We explored how to improve communication about low-risk lesions including labels, language and other strategies.Design Qualitative description and thematic analysis to examine the transcripts of telephone interviews with patients who had low-risk lesions and physicians; and mapping to Communication Accommodation Theory to interpret themes.Setting CanadaParticipants 15 patients: 6 (40%) bladder, 5 (33%) prostate and 4 (27%) cervix lesions; and 13 physicians: 7 (54%) cervix, 3 (23%) bladder and 3 (23%) prostate lesions.Main outcome measures Patient and physician views of labels, language and other strategies to improve communication about low-risk lesions.Results Patients and clinicians held discordant views about low-risk lesion label impact, preferences and rationale. All labels prompted confusion and anxiety among patients. In contrast, physicians perceived that patients understood that labels they used across all label categories (abnormal, precursor-to-cancer and cancer) implied low risk for cancer progression. Patients preferred abnormal cells, particularly when first learning of their diagnosis, and desired additional information to distinguish their diagnosis from cancer and justify treatment. In contrast, physicians favoured precursor-to-cancer and cancer labels out of habit, to match labels that patients saw elsewhere (online, charts) and to convince patients to attend follow-up and treatment visits. However, patients and physicians largely agreed on the need for 16 strategies that could improve communication about low-risk lesions including language (eg, plain language, situate low-risk lesions on cancer spectrum) and complementary communication strategies (eg, longer appointments, visual aids, connect patients with support services or groups).Conclusions The findings build on prior research by revealing that modifying labels is not the only or best strategy needed to improve communication about low-risk lesions. Ongoing research should examine how best to implement the strategies recommended by patients and physicians.

BACKGROUND:Speech-language pathologists serve a critical role within multidisciplinary head and neck cancer care teams. Provision of speech-language pathology services for head and neck cancer patients varies by region and is not well characterized. METHODS:A mixed methods scoping assessment was conducted with a purposive sample of speech-language pathologists from designated comprehensive head and neck cancer centers. Each speech-language pathologist completed a 31-item survey and 60-min semi-structured interview. RESULTS:Analysis of survey responses and qualitative interviews identified three major themes: unsuitable infrastructure; multilevel barriers; and the need to champion speech-language pathology services. Speech-language pathologists consistently reported inadequate resources, inequitable services, and increasing job responsibilities associated with growing patient complexity and caseloads. CONCLUSIONS:Significant systemic barriers impede the effective delivery of speech-language pathology services in head and neck cancer care. Our findings and recommendations create an important foundation for healthcare agency decisions on the allocation and funding of speech-language pathology services.

Importance:The care for a small subset of patients is responsible for a disproportionately large share of health care expenditures. Head and neck cancer is associated with significant health care costs due to complex treatment regimens and long-term sequelae. Given this high baseline cost, identifying patients with high care costs within a population with cancer might help inform interventions to optimize resource allocation. Objective:To characterize patients with head and neck cancer with the highest health care costs during the first year after diagnosis. Design, Setting, and Participants:A population-based, retrospective cohort study was conducted using administrative data from the Institute for Clinical and Evaluative Sciences in Ontario, Canada, and included adults diagnosed with head and neck cancer between January 2007 and October 2020 (identified from the provincial cancer registry) with a full 1.5-year follow-up from the date of diagnosis to the date of death or October 31, 2021. The total 1-year health care costs were estimated using a patient-level algorithm and were collected in 2020 Canadian dollar values. The main analyses were performed in April 2023 and a sensitivity analysis was performed in April 2025. Main Outcomes and Measures:High health care costs (>75th percentile) during the first year after a head and neck cancer diagnosis. Predictors of high health care costs were identified using a multivariable logistic regression model. Results:The cohort included 13 795 patients (mean age, 63.2 [SD, 11.7] years and 3452 [25.0%] were female), 3448 (25%) of whom had high health care costs. Cancer stage was the strongest predictor of high health care costs. Compared with patients with stage I cancer, those with stage II cancer had 2-fold greater odds for high health care costs (odds ratio [OR], 3.14 [95% CI, 2.56-3.84]), those with stage III cancer had 5-fold greater odds for high health care costs (OR, 6.08 [95% CI, 4.99-7.41]), and those with stage IV cancer had 8-fold greater odds for high health care costs (OR, 8.94 [95% CI, 7.43-10.80]). Receiving multiple treatment modalities also was associated with greater odds for high-cost care. Conclusions and Relevance:This cohort study found that more advanced disease stage and receiving multiple treatment modalities were the strongest predictors of high-cost care among patients diagnosed with head and neck cancer. Prioritizing research and implementation of screening programs, earlier cancer diagnoses, and effective treatment deescalation strategies might mitigate a significant portion of these high costs.

Background/Objectives: Patients with breast cancer who do not achieve a complete response to neoadjuvant chemotherapy (NAC) may benefit from intensified adjuvant systemic therapy. However, such treatment escalation is typically delayed until after tumour resection, which occurs several months into the treatment course. Quantitative ultrasound (QUS) can detect early microstructural changes in tumours and may enable timely identification of non-responders during NAC, allowing for earlier treatment intensification. In our previous prospective observational study, 100 breast cancer patients underwent QUS imaging before and four times during NAC. Machine learning algorithms based on QUS texture features acquired in the first week of treatment were developed and achieved 78% accuracy in predicting treatment response. In the current study, we aimed to validate these algorithms in an independent prospective cohort to assess reproducibility and confirm their clinical utility. Methods: We included breast cancer patients eligible for NAC per standard of care, with tumours larger than 1.5 cm. QUS imaging was acquired at baseline and during the first week of treatment. Tumour response was defined as a ≥30% reduction in target lesion size on the resection specimen compared to baseline imaging. Results: A total of 51 patients treated between 2018 and 2021 were included (median age 49 years; median tumour size 3.6 cm). Most were estrogen receptor–positive (65%) or HER2-positive (33%), and the majority received dose-dense AC-T (n = 34, 67%) or FEC-D (n = 15, 29%) chemotherapy, with or without trastuzumab. The support vector machine algorithm achieved an area under the curve of 0.71, with 86% accuracy, 91% specificity, 50% sensitivity, 93% negative predictive value, and 43% positive predictive value for predicting treatment response. Misclassifications were primarily associated with poorly defined tumours and difficulties in accurately identifying the region of interest. Conclusions: Our findings validate QUS-based machine learning models for early prediction of chemotherapy response and support their potential as non-invasive tools for treatment personalization and clinical trial development focused on early treatment intensification.

Purpose: This study is aimed at generating consensus among women who had ductal carcinoma in situ (DCIS) and healthcare professionals on how to improve communication about low-risk forms of DCIS and reduce affected women's diagnosis-related confusion and anxiety. Methods: We conducted a two-round online Delphi survey with affected women and professionals from across Canada. They rated items sourced from prior research and key informant interviews on a 7-point Likert scale. We retained items rated 6 or 7 by ≥ 80% of panelists. Results: Thirty-seven panelists (17 women, 20 professionals) completed Round 1 and 94.6% of those completed Round 2. Of 42 items rated, 18 were retained, 13 discarded, and 11 did not achieve consensus to retain or discard. Women and professionals agreed on 3 language approaches (use plain language, distinguish DCIS from invasive breast cancer, specify the risk of recurrence and spread) and 9 other strategies to help discuss DCIS (e.g., use visual aids, provide or refer women to culturally tailored DCIS-specific information, ensure physicians can access interpreters). Based on rating and comments, women were more enthusiastic than professionals about referring to abnormal cells rather than DCIS and scheduling longer or follow-up visits to address concerns. To disseminate these findings, panelists recommended public awareness campaigns for women and continuing education and professional society endorsement for physicians. Conclusion: These findings address gaps in prior research that recommended changing the DCIS label, but had not fully explored label preferences, or identified other ways to improve and support communication about DCIS.

Background/Objectives: Merkel cell carcinoma (MCC) is an uncommon but aggressive skin malignancy with a rising incidence. Limited data exist on the survival of MCC patients in Canada. This study analyzes the survival of patients diagnosed with MCC in Canada between 2000 and 2018 compared to those reported by the American Joint Committee on Cancer (AJCC) 8th edition. Risk factors included in the database were sex, age, and immunosuppression. Methods: We conducted a multicenter retrospective cohort study including patients diagnosed with stage I–IV MCC aged ≥18 from 10 Canadian university centers and three provinces. We evaluated differences in survival compared to the cohort included in the AJCC 8th edition. Results: Among 899 patients diagnosed with MCC in Canada, 327 (36.4%) had stage I, 195 (21.7%) had stage II, 305 (33.9%) had stage III, and 72 (8.0%) had stage IV at presentation. When examining risk factors, 61.1% (549) were male, 10.2% (92) were immunosuppressed, and age at diagnosis was 75 years (±11). The five-year overall survival for patients diagnosed in Canada at stage I was 56.8%, stage IIA 54.0%, stage IIB 28.0%, stage IIIA 52.7%, stage IIIB 40.2%, and stage IV 13.9%. Conclusions: Survival from MCC is low in Canada across all stages. Compared to the AJCC 8th edition, patients diagnosed with MCC in Canada have similar survival rates, except for patients diagnosed with stage IIIB, who have lower survival rates in the AJCC 8th edition. Further research is needed to improve the survival of this rare malignancy.

Objectives:. To determine associations between physician sex and use of postoperative healthcare resources among patients undergoing common surgeries in Ontario, Canada. Background:. Prior studies have shown that patients of female physicians experience better outcomes and have lower healthcare costs compared with patients of male physicians. Understanding differences in resource utilization may offer insights into the care pathways and practice patterns contributing to these differences. Methods:. We conducted a population-based, retrospective cohort study of adults (≥18 years of age) undergoing 1 of 25 common surgeries, between January 1, 2007, and December 31, 2019, in Ontario, Canada. The primary outcome was the utilization of one of the following: intensive care unit admission, other medical interventions (eg, tracheostomy, new dialysis starts, and home oxygen), and discharge care needs (eg inpatient rehab, long-term care, and home care use) within 30 days. The data were summarized using descriptive statistics and adjusted using multivariable generalized estimating equations. Results:. This population-based study included 1,100,193 patients (61.8% female). Patients treated by male surgeons had higher use of postoperative resources versus those with female surgeons within 30 days (adjusted rate 33.1; 95% confidence interval [CI]: 28.0–39.2 versus 31.2; 95% CI: 25.8–37.7), 90 days, and 1 year. Consistent with these findings, following adjustment for patient, surgeon, procedural, and hospital characteristics, patients treated by male surgeons were significantly more likely to utilize postoperative resources within 30 days (adjusted odds ratio: 1.14; 95% CI: 1.03–1.27; P = 0.010) and at other time points. This difference was primarily driven by the higher use of home care among patients with a male versus female surgeon at all time points (30 days: adjusted odds ratio, 1.13; 95% CI: 1.05–1.21; P = 0.002). Conclusions:. Patients with male surgeons had higher postoperative resource utilization when compared with those treated by female surgeons, which was almost entirely driven by the higher use of home care. Further mixed-methods investigation is needed to better understand other potentially relevant factors including surgical outcomes, individual patient preferences, and surgical team decision-making.

This work was conducted in order to validate a pre-treatment quantitative ultrasound (QUS) and texture derivative analyses-based prediction model proposed in our previous study to identify responders and non-responders to neoadjuvant chemotherapy in patients with breast cancer. The validation cohort consisted of 56 breast cancer patients diagnosed between the years 2018 and 2021. Among all patients, 53 were treated with neoadjuvant chemotherapy and three had unplanned changes in their chemotherapy cycles. Radio Frequency (RF) data were collected volumetrically prior to the start of chemotherapy. In addition to tumour region (core), a 5 mm tumour-margin was also chosen for parameters estimation. The prediction model, which was developed previously based on quantitative ultrasound, texture derivative, and tumour molecular subtypes, was used to identify responders and non-responders. The actual response, which was determined by clinical and pathological assessment after lumpectomy or mastectomy, was then compared to the predicted response. The sensitivity, specificity, positive predictive value, negative predictive value, and F1 score for determining chemotherapy response of all patients in the validation cohort were 94%, 67%, 96%, 57%, and 95%, respectively. Removing patients who had unplanned changes in their chemotherapy resulted in a sensitivity, specificity, positive predictive value, negative predictive value, and F1 score of all patients in the validation cohort of 94%, 100%, 100%, 50%, and 97%, respectively. Explanations for the misclassified cases included unplanned modifications made to the type of chemotherapy during treatment, inherent limitations of the predictive model, presence of DCIS in tumour structure, and an ill-defined tumour border in a minority of cases. Validation of a model was conducted in an independent cohort of patient for the first time to predict the tumour response to neoadjuvant chemotherapy using quantitative ultrasound, texture derivate, and molecular features in patients with breast cancer. Further research is needed to improve the positive predictive value and evaluate whether the treatment outcome can be improved in predicted non-responders by switching to other treatment options.

Several postmastectomy breast reconstruction techniques and procedures have been implemented, although with limited evaluation of benefits and adverse effects. We conducted a systematic review on the plane and timing of reconstruction, and on the use of nipple-sparing mastectomy, acellular dermal matrix, and autologous fat grafting as the evidence base for an updated clinical practice guideline on breast reconstruction for Ontario Health (Cancer Care Ontario). Both immediate and delayed reconstruction may be considered, with preferred timing depending on factors such as patient preferences, type of mastectomy, skin perfusion, comorbidities, pre-mastectomy breast size, and desired reconstructive breast size. Immediate reconstruction may provide greater psychological or quality of life benefits. In patients who are candidates for skin-sparing mastectomy and without clinical, radiological, and pathological indications of nipple-areolar complex involvement, nipple-sparing mastectomy is recommended provided it is technically feasible and acceptable aesthetic results can be achieved. Surgical factors including incision location are important to reduce necrosis by preserving blood supply and to minimize nerve damage. There is a role for both prepectoral and subpectoral implants; risks and benefits will vary, and decisions should be made during consultation between the patient and surgeons. In patients who are suitable candidates for implant reconstruction and have adequate mastectomy flap thickness and vascularity, prepectoral implants should be considered. Acellular dermal matrix (ADM) has led to an increased use of prepectoral reconstruction. ADM should not be used in case of poor mastectomy flap perfusion/ischemia that would otherwise be considered unsuitable for prepectoral reconstruction. Care should be taken in the selection and handling of acellular dermal matrix (ADM) to minimize risks of infection and seroma. Limited data from small studies suggest that prepectoral reconstruction without ADM may be feasible in some patients. Autologous fat grafting is recommended as a treatment for contour irregularities, rippling following implant-based reconstruction, and to improve tissue quality of the mastectomy flap after radiotherapy.

Previous work has demonstrated quantitative ultrasound (QUS) analysis techniques for extracting features and texture features from ultrasound radiofrequency data which can be used to distinguish between benign and malignant breast masses. It is desirable that there be good agreement between estimates of such features acquired using different ultrasound devices. Handheld ultrasound imaging systems are of particular interest as they are compact, relatively inexpensive, and highly portable. This study investigated the agreement between QUS parameters and texture features estimated from clinical ultrasound images of breast tumors acquired using two different ultrasound scanners: a traditional cart-based system and a wireless handheld ultrasound system. The 28 patients who participated were divided into two groups (benign and malignant). The reference phantom technique was used to produce functional estimates of the normalized power spectra and backscatter coefficient for each image. Root mean square differences of feature estimates were calculated for each cohort to quantify the level of feature variation attributable to tissue heterogeneity and differences in system imaging parameters. Cross-system statistical testing using the Mann–Whitney U test was performed on benign and malignant patient cohorts to assess the level of feature estimate agreement between systems, and the Bland–Altman method was employed to assess feature sets for systematic bias introduced by differences in imaging method. The range of p-values was 1.03 × 10−4 to 0.827 for the benign cohort and 3.03 × 10−10 to 0.958 for the malignant cohort. For both cohorts, all five of the primary QUS features (MBF, SS, SI, ASD, AAC) were found to be in agreement at the 5% confidence level. A total of 13 of the 20 QUS texture features (65%) were determined to exhibit statistically significant differences in the sample medians of estimates between systems at the 5% confidence level, with the remaining 7 texture features being in agreement. The results showed a comparable magnitude of feature variation between tissue heterogeneity and system effects, as well as a moderate level of statistical agreement between feature sets.

BACKGROUND:Wait time (WT) to surgery is a common quality indicator for colorectal cancer (CRC). However, the definition of WT targets and its association with clinically relevant outcomes remains poorly defined. We assessed the association between WT to CRC surgery and overall survival (OS) for curative-intent surgery. METHODS:We conducted a population-based retrospective cohort study of adults undergoing resection for stage I to III CRC (between 2007 and 2020), using health administrative data in Ontario, Canada. The exposure was WT, measured as the time from the decision to operate to surgery (in days). The outcome was OS, measured as time from surgery to death. Restricted cubic spline regression (RCS) examined the relationship between WT and hazards of death to identify meaningful WT thresholds. WT was then categorized as (a) traditional WT target (≤ 28 days) or (b) new data-informed target defined by RCS. Multivariable Cox proportional hazards explored the association between each WT target and the hazards of death after adjusting for confounders established a priori. RESULTS:Of 35,533 patients, 27,102 (76.3%) underwent surgery within the traditional WT target. The median WT was 19 days (interquartile range: 12-28). RCS revealed an inflection point around 45 days associated with increasing hazards of death. After adjusting for age, sex, comorbidity, cancer site, stage, neo-adjuvant or adjuvant therapy, and year of surgery, having surgery within the traditional WT target (≤ 28 days) was not associated with OS [hazards ratio (HR): 0.97; 95% CI: 0.92-1.02]. Having surgery within the new WT target (≤ 45 days) was independently associated with superior OS (HR: 0.90, 95% CI: 0.82-0.99). CONCLUSIONS:In patients undergoing curative-intent resection for stage I to III CRC, having surgery within traditional WT target of 28 days was not associated with OS. However, having surgery within a WT target of 45 days was independently associated with superior OS. These data highlight the need to reconsider WT targets for quality monitoring by linking to clinically meaningful outcomes.