Automated lesion detection of breast cancer in [18F] FDG PET/CT using a novel AI-Based workflow

UNLABELLED: Applications based on artificial intelligence (AI) and deep learning (DL) are rapidly being developed to assist in the detection and characterization of lesions on medical images. In this study, we developed and examined an image-processing workflow that incorporates both traditional image processing with AI technology and utilizes a standards-based approach for disease identification and quantitation to segment and classify tissue within a whole-body [ METHODS: One hundred thirty baseline PET/CT studies from two multi-institutional preoperative clinical trials in early-stage breast cancer were semi-automatically segmented using techniques based on PERCIST v1.0 thresholds and the individual segmentations classified as to tissue type by an experienced nuclear medicine physician. These classifications were then used to train a convolutional neural network (CNN) to automatically accomplish the same tasks. RESULTS: Our CNN-based workflow demonstrated Sensitivity at detecting disease (either primary lesion or lymphadenopathy) of 0.96 (95% CI [0.9, 1.0], 99% CI [0.87,1.00]), Specificity of 1.00 (95% CI [1.0,1.0], 99% CI [1.0,1.0]), DICE score of 0.94 (95% CI [0.89, 0.99], 99% CI [0.86, 1.00]), and Jaccard score of 0.89 (95% CI [0.80, 0.98], 99% CI [0.74, 1.00]). CONCLUSION: This pilot work has demonstrated the ability of AI-based workflow using DL-CNNs to specifically identify breast cancer tissue as determined by

Tumor and serum DNA methylation in women receiving preoperative chemotherapy with or without vorinostat in TBCRC008

BACKGROUND: Methylated gene markers have shown promise in predicting breast cancer outcomes and treatment response. We evaluated whether baseline and changes in tissue and serum methylation levels would predict pathological complete response (pCR) in patients with HER2-negative early breast cancer undergoing preoperative chemotherapy. METHODS: The TBCRC008 trial investigated pCR following 12 weeks of preoperative carboplatin and albumin-bound paclitaxel + vorinostat/placebo (n = 62). We measured methylation of a 10-gene panel by quantitative multiplex methylation-specific polymerase chain reaction and expressed results as cumulative methylation index (CMI). We evaluated association between CMI level [baseline, day 15 (D15), and change] and pCR using univariate and multivariable logistic regression models controlling for treatment and hormone receptor (HR) status, and performed exploratory subgroup analyses. RESULTS: In univariate analysis, one log unit increase in tissue CMI levels at D15 was associated with 40% lower chance of obtaining pCR (odds ratio, OR 0.60, 95% CI 0.37-0.97; p = 0.037). Subgroup analyses suggested a significant association between tissue D15 CMI levels and pCR in vorinostat-treated [OR 0.44 (0.20, 0.93), p = 0.03], but not placebo-treated patients. CONCLUSION: In this study investigating the predictive roles of tissue and serum CMI levels in patients with early breast cancer for the first time, we demonstrate that high D15 tissue CMI levels may predict poor response. Larger studies and improved analytical procedures to detect methylated gene markers in early stage breast cancer are needed. TBCRC008 is registered on ClinicalTrials.gov (NCT00616967)

Fixed-dose capecitabine is feasible: results from a pharmacokinetic and pharmacogenetic study in metastatic breast cancer

The pro-drug capecitabine is approved for treatment of anthracycline- and paclitaxel-resistant metastatic breast cancer. However, toxicity and large interpatient pharmacokinetic variability occur despite body surface area (BSA)-dosing. We hypothesized that a fixed-dose schedule would simplify dosing and provide an effective and safe alternative to BSA-based dosing

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

Liver Resection for Breast Cancer Liver Metastases A Cost-utility Analysis

OBJECTIVE: To estimate the cost-effectiveness of liver resection followed by adjuvant systemic therapy relative to systemic therapy alone for patients with breast cancer liver metastasis. BACKGROUND: Data on cost-effectiveness of liver resection for advanced breast cancer with liver metastasis are lacking. METHODS: A decision-analytic Markov model was constructed to evaluate the cost-effectiveness of liver resection followed by postoperative conventional systemic therapy (strategy A) versus conventional therapy alone (strategy B) versus newer targeted therapy alone (strategy C). The implications of using different chemotherapeutic regimens based on estrogen receptor and human epidermal growth factor receptor 2 status was also assessed. Outcomes included quality-adjusted life months (QALMs), incremental cost-effectiveness ratio, and net health benefit (NHB). RESULTS: NHB of strategy A was 10.9 QALMs compared with strategy B when letrozole was used as systemic therapy, whereas it was only 0.3 QALMs when docetaxel\u200a+\u200atrastuzumab was used as a systemic therapy. The addition of newer biological agents (strategy C) significantly decreased the cost-effectiveness of strategy B (conventional systemic therapy alone). The NHB of strategy A was 31.6 QALMs versus strategy C when palbociclib was included in strategy C; similarly, strategy A had a NHB of 13.8 QALMs versus strategy C when pertuzumab was included in strategy C. Monte-Carlo simulation demonstrated that the main factor influencing NHB of strategy A over strategy C was the cost of systemic therapy. CONCLUSIONS: Liver resection in patients with breast cancer liver metastasis proved to be cost-effective when compared with systemic therapy alone, particularly in estrogen receptor-positive tumors or when newer agents were used

Impact of Muscle Measures on Outcome in Patients Receiving Endocrine Therapy for Metastatic Breast Cancer: Analysis of ECOG-ACRIN E2112

Background: Observational data investigating the relationship between body habitus and outcomes in breast cancer have been variable and inconsistent, largely centered in the curative setting and focused on weight-based metrics. This study evaluated the impact of muscle measures on outcomes in patients with metastatic breast cancer receiving endocrine-based therapy. Methods: Baseline CT scans were collected from ECOG-ACRIN E2112, a randomized phase III placebo-controlled study of exemestane with or without entinostat. A CT cross-sectional image at the L3 level was extracted to obtain skeletal muscle mass and attenuation. Low muscle mass (LMM) was defined as skeletal muscle index <41 cm2/m2 and low muscle attenuation (LMA) as muscle density <25 HU or <33 HU if overweight/obese by body mass index (BMI). Multivariable Cox proportional hazard models determined the association between LMM or LMA and progression-free survival (PFS) and overall survival (OS). Correlations between LMM, LMA, and patient-reported outcomes were determined using 2-sample t tests. Results: Analyzable CT scans and follow-up data were available for 540 of 608 patients. LMM was present in 39% (n=212) of patients and LMA in 56% (n=301). Those with LMA were more likely to have obesity and worse performance status. LMM was not associated with survival (PFS hazard ratio [HR]: 1.13, P=.23; OS HR: 1.05, P=.68), nor was LMA (PFS HR: 1.01, P=.93; OS HR: 1.00, P=.99). BMI was not associated with survival. LMA, but not LMM, was associated with increased frequency of patient-reported muscle aches. Conclusions: Both low muscle mass and density are prevalent in patients with hormone receptor-positive metastatic breast cancer. Muscle measures correlated with obesity and performance status; however, neither muscle mass nor attenuation were associated with prognosis. Further work is needed to refine body composition measurements and select optimal cutoffs with meaningful endpoints in specific breast cancer populations, particularly those living with metastatic disease