Pretreatment CT and PET radiomics predicting rectal cancer patients in response to neoadjuvant chemoradiotherapy.

BACKGROUND: The purpose of this study was to characterize pre-treatment non-contrast computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (PET) based radiomics signatures predictive of pathological response and clinical outcomes in rectal cancer patients treated with neoadjuvant chemoradiotherapy (NACR T). MATERIALS AND METHODS: An exploratory analysis was performed using pre-treatment non-contrast CT and PET imaging dataset. The association of tumor regression grade (TRG) and neoadjuvant rectal (NAR) score with pre-treatment CT and PET features was assessed using machine learning algorithms. Three separate predictive models were built for composite features from CT + PET. RESULTS: The patterns of pathological response were TRG 0 (n = 13; 19.7%), 1 (n = 34; 51.5%), 2 (n = 16; 24.2%), and 3 (n = 3; 4.5%). There were 20 (30.3%) patients with low, 22 (33.3%) with intermediate and 24 (36.4%) with high NAR scores. Three separate predictive models were built for composite features from CT + PET and analyzed separately for clinical endpoints. Composite features with α = 0.2 resulted in the best predictive power using logistic regression. For pathological response prediction, the signature resulted in 88.1% accuracy in predicting TRG 0 vs. TRG 1-3; 91% accuracy in predicting TRG 0-1 vs. TRG 2-3. For the surrogate of DFS and OS, it resulted in 67.7% accuracy in predicting low vs. intermediate vs. high NAR scores. CONCLUSION: The pre-treatment composite radiomics signatures were highly predictive of pathological response in rectal cancer treated with NACR T. A larger cohort is warranted for further validation.

Modeling precision genomic-based radiation dose response in rectal cancer.

Aim: Genomic-based risk stratification to personalize radiation dose in rectal cancer. Patients & methods: We modeled genomic-based radiation dose response using the previously validated radiosensitivity index (RSI) and the clinically actionable genomic-adjusted radiation dose. Results: RSI of rectal cancer ranged from 0.19 to 0.81 in a bimodal distribution. A pathologic complete response rate of 21% was achieved in tumors with an RSI <0.31 at a minimal genomic-adjusted radiation dose of 29.76 when modeling RxRSI to the commonly prescribed physical dose of 50 Gy. RxRSI-based dose escalation to 55 Gy in tumors with an RSI of 0.31-0.34 could increase pathologic complete response by 10%. Conclusion: This study provides a theoretical platform for development of an RxRSI-based prospective trial in rectal cancer.

Impact of fixation mechanism and helix retraction status on right ventricular lead extraction.

Background: The impact of lead fixation mechanism on extractability is poorly characterized. Objective: We aimed to compare the technical difficulty of transvenous lead extraction (TLE) of active vs passive fixation right ventricular (RV) leads. Methods: A total of 408 patients who underwent RV TLE by a single expert electrophysiologist at Oregon Health & Science University between October 2011 and June 2022 were identified and retrospectively analyzed; 331 (81%) had active fixation RV leads and 77 (19%) had passive fixation RV leads. The active fixation cohort was further stratified into those with successfully retracted helices (n = 181) and failed helix retraction (n = 109). A numerical system (0-9) devised using 6 procedural criteria quantified a technical extraction score (TES) for each RV TLE. The TES was compared between groups. Results: Helix retraction was successful in ≥55% of active fixation TLEs. The mean TES for active-helix retracted, active-helix non-retracted, and passive fixation groups was 1.8, 3.5, and 3.7, respectively. The TES of the active-helix retracted group was significantly lower than those of the active-helix non-retracted group (adjusted P < .01) and the passive fixation group (adjusted P < .01). There was no significant difference in TES between the passive fixation and active-helix non-retracted groups in multivariate analysis (P = .18). The TLE success rate of the entire cohort was >97%, with a major complication rate of 0.5%. Conclusion: TLE of active fixation leads where helical retraction is achieved presents fewer technical challenges than does passive fixation RV lead extraction; however, if the helix cannot be retracted, active and passive TLE procedures present similar technical challenges.

Determining Optimal Follow-up for Patients With Anal Cancer Following Chemoradiation.

BACKGROUND: US health care is increasingly defined by over expenditure and inefficiency. Optimizing patient follow-up is critical, especially in cancers treated with high control rates. To optimize patient care, this study assessed time to disease recurrence or toxicity in patients with anal carcinoma. MATERIALS AND METHODS: In total, 140 patients with biopsy-proven, nonmetastatic anal carcinoma, treated with chemoradiation utilizing intensity-modulated radiation therapy, were identified from our institutional database. This retrospective study evaluated local recurrence (LR), distant metastasis (DM), overall survival (OS), and late ≥grade 3 toxicity (LG3T). Patients were followed posttreatment every 3 months for 2 years, every 6 months in years 3 to 5, then yearly thereafter per NCCN recommendations. RESULTS: The median age and follow-up was 58 years and 27 months, respectively. Patients were categorized into high (n=61; 44%) and low (n=77; 55%) risk groups based on stage. The 2-year LC, DMFS, and OS were 93%, 94%, and 89% and 5-year LC, DMFS, OS were 92%, 87%, and 85%, respectively. Overall, there were 29 events (9 LR, 11 DM, and 9 LG3T), with 62% of events occurring within year 1 and 79% within 2 years. Stratified by event type, at 2 years 89% of LR, 64% of DM, and 89% LG3T were identified. At the remaining follow-up points, the event incidence rate was 1.3%. CONCLUSION: With the majority of recurrences/toxicities occurring within the first 2 years, a reduction in follow-up during years 3 to 5 may provide adequate surveillance. Revisions of the current recommendations could maximize resources while improving patient quality of life.

CT-based radiomic features to predict pathological response in rectal cancer: A retrospective cohort study.

INTRODUCTION: Innovative biomarkers to predict treatment response in rectal cancer would be helpful in optimizing personalized treatment approaches. In this study, we aimed to develop and validate a CT-based radiomic imaging biomarker to predict pathological response. METHODS: We used two independent cohorts of rectal cancer patients to develop and validate a CT-based radiomic imaging biomarker predictive of treatment response. A total of 91 rectal cancer cases treated from 2009 to 2018 were assessed for the tumour regression grade (TRG) (0 = pathological complete response, pCR; 1 = moderate response; 2 = partial response; 3 = poor response). Exploratory analysis was performed by combining pre-treatment non-contrast CT images and patterns of TRG. The models built from the training cohort were further assessed using the independent validation cohort. RESULTS: The patterns of pathological response in training and validation groups were TRG 0 (n = 14, 23.3%; n = 6, 19.4%), 1 (n = 31, 51.7%; n = 15, 48.4%), 2 (n = 12, 20.0%; n = 7, 22.6%) and 3 (n = 3, 5.0%; n = 3, 9.7%), respectively. Separate predictive models were built and analysed from CT features for pathological response. For pathological response prediction, the model including 8 radiomic features by random forest method resulted in 83.9% accuracy in predicting TRG 0 vs TRG 1-3 in validation. CONCLUSION: The pre-treatment CT-based radiomic signatures were developed and validated in two independent cohorts. This imaging biomarker provided a promising way to predict pCR and select patients for non-operative management.