Relation between skeletal muscle volume and prognosis in rectal cancer patients undergoing neoadjuvant therapy

Assessing Quality of Life with the Novel QLQ-CAX24 Questionnaire and Body Composition Parameters in Rectal Cancer Patients: A Single-Center Prospective Study

BACKGROUND

Patients with rectal cancer (RC) are at risk of developing cancer-related cachexia, a complex metabolic syndrome that can negatively impact quality of life (QoL), treatment tolerance, and clinical response.

OBJECTIVES

The aim of the study was to explore the possible associations of the novel European Organization for Research and Treatment of Cancer QoL Questionnaire-Cancer Cachexia (EORTC QLQ-CAX24) scores with body composition parameters and physical performance in patients with locally advanced RC (LARC).

METHODS

This prospective observational study involved RC patients evaluated at the dedicated outpatient clinic of Clinical Nutrition at the Fondazione Policlinico Agostino Gemelli IRCCS. Patients with a confirmed diagnosis of LARC were enrolled between January and December 2023. The body composition parameters were measured using the preoperative computed tomography scan at the level of the third lumbar vertebra as well as using bioimpedance analysis before and after the radiotherapy treatment. QoL was measured by the EORTC QLQ-C30 and EORTC QLQ-CAX24 questionnaires.

RESULTS

A total of 56 RC patients were enrolled. Significant associations (p < 0.05) were found between EORTC QLQ-CAX24 values and the presence of cachexia, body composition, handgrip strength, and malnutrition diagnosis. Muscle mass was significatively also associated with EORTC QLQ-CAX24 results, suggesting a link between subjective perception of QoL and objectively measured body composition.

CONCLUSIONS

The EORTC CAX24 questionnaire can be an effective tool for monitoring changes in cachexia status during radiotherapy, enabling early detection of cachexia-related complications and timely intervention.

The prognostic significance of sarcopenia in patients treated with definitive radiotherapy: A systematic review

Sarcopenia describes the degenerative loss of muscle mass and strength, and is emerging as a pan-cancer prognostic biomarker. It is linked with increased treatment toxicity, decreased survival and significant healthcare financial burden. Systematic analyses of sarcopenia studies have focused on outcomes in patients treated surgically or with systemic therapies. There are few publications concerning patients treated with radiotherapy. This manuscript presents a pan-cancer systematic review of the association between sarcopenia and survival outcomes in patients treated with definitive (chemo-)radiotherapy. A literature search was performed, with 26 studies identified, including a total of 5,784 patients. The prognostic significance of sarcopenia was mixed. This may reflect lack of consensus in methods used to measure skeletal muscle mass and define sarcopenia. Many papers analyse small samples and present sarcopenia cutoffs optimised on the local population, which may not generalise to external populations. Recent advances in artificial intelligence allow for automatic measurement of body composition by segmenting the muscle compartment on routinely collected imaging. This provides opportunity for standardisation of measurement methods and definitions across populations. Adopting sarcopenia diagnosis into clinical workflows could reduce futile treatments and associated financial burden, by reducing treatment toxicities, and improving treatment completion, patient survival, and quality-of-life after cancer.

Artificial intelligence measured 3D lumbosacral body composition and clinical outcomes in rectal cancer patients

INTRODUCTION

Patient body composition (BC) has been shown to help predict clinical outcomes in rectal cancer patients. Artificial intelligence algorithms have allowed for easier acquisition of BC measurements, creating a comprehensive BC profile in patients using data from an entire three-dimensional (3D) region of the body. This study has utilized AI technology to measure BC from the entire lumbosacral (L1-S5) region and assessed the associations between BC and clinical outcomes in rectal cancer patients who have undergone neoadjuvant therapy followed by surgery.

METHODS

A retrospective, cross sectional analysis was performed on locally advanced rectal cancer (LARC) patients treated with neoadjuvant long-course chemoradiotherapy followed by curative resection with total mesorectal excision at a tertiary referral centre, Western Health, Melbourne, Australia. A pre-trained and validated in-house AI segmentation model was used to automatically segment and measure intramuscular adipose tissue (IMAT), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and skeletal muscle (SM) from CT slices across the entire L1-S5 level of each patient. Multivariate analysis between patient BC and clinical outcomes was performed.

RESULTS

Two hundred and fourteen patients were included in the study. One hundred and fifty-one (70.6%) patients were male and 63 (29.4%) patients were female. The average age at diagnosis was 62.4 (±12.7) years. SM density, but not volume, was associated with better overall survival (OS) (HR 0.24, P = 0.029), recurrence-free survival (RFS) (HR 0.45, P = 0.048) and decreased length of stay (LoS) (HR 1.58, P = 0.036). Both IMAT volume (HR 0.13, P = 0.008) and density (HR 0.26, P = 0.006) were associated with better OS.

CONCLUSION

This study measured 3D BC from the entire lumbosacral region of rectal cancer patients. SM density was the most significant BC parameter, and was associated with improved OS, RFS and LoS. This adds to growing evidence that SM is a key component of BC in cancer patients and should be optimized prior to treatment. IMAT was also a prognostic factor, giving rise to avenues of future research into the role of adiposity on nutrition and tumour immunology.

Artificial Intelligence-Driven Volumetric Analysis of Muscle Mass as a Predictor of Tumor Response to Neoadjuvant Chemoradiotherapy in Patients with Rectal Cancer

Background/Objectives: Artificial intelligence (AI)-based volumetric measurements for assessing sarcopenia are expected to offer comprehensive insight into three-dimensional muscle volume and distribution. Therefore, we investigated the role of sarcopenia using computed tomography (CT)-based automated AI volumetric muscle measurements in predicting neoadjuvant chemoradiotherapy (nCRT) response and prognosis in patients with rectal cancer who underwent nCRT. Methods: We retrospectively analyzed the data of patients who underwent nCRT followed by curative resection between March 2010 and August 2021. Sarcopenia was defined using the Q1 cutoff value of the volumetric skeletal muscle index (SMI). The association between pre-nCRT volumetric sarcopenia and nCRT response was analyzed using logistic regression. A Cox proportional hazards model was used to identify the prognostic value of the pre- and post-nCRT volumetric SMIs. Results: Notably, 22 (25.6%) of the 86 patients had volumetric sarcopenia. The sarcopenia group showed a poorer nCRT response than the non-sarcopenia group. Pre-nCRT sarcopenia was a significant predictor of poor nCRT response (OR, 0.34 [95% CI, 0.12-0.96]; p = 0.041). Furthermore, an increased volumetric SMI during nCRT was a more significant prognostic factor on recurrence-free survival (aHR, 0.26 [95% CI, 0.08-0.83]; p = 0.023) and overall survival (aHR, 0.41 [95% CI, 0.17-0.99]; p = 0.049) than a decreased SMI. Conclusions: Volumetric sarcopenia can be used to predict poor nCRT response. A reduction in volumetric sarcopenia can be a poor prognostic factor in patients with rectal cancer who undergo nCRT.

The application of QCT in the prognostic assessment of mCRC undergoing first-line treatment based on bevacizumab

BACKGROUND

Bevacizumab induces muscle atrophy by changing the gene expression level of muscle tissue. Quantitative computed tomography (QCT) enables precise measurement of various body compositions, including muscle area.

MATERIALS & METHODS

A total of 102 patients with metastatic colorectal cancer (mCRC) undergoing first-line chemotherapy based on bevacizumab were enrolled at thirst Affiliated Hospital of the University of Science and Technology of China. Their body compositions were measured respectively 1 month before and 1 month after the treatment.

RESULTS

Treatment-related decline in skeletal muscle index and visceral fat infiltration significantly affect patient prognosis.

CONCLUSION

A predictive model constructed by integrating changes in body composition with patient clinical characteristics effectively predicts the 9-month progression-free survival (PFS) of patients with mCRC.

The survival prediction of advanced colorectal cancer received neoadjuvant therapy-a study of SEER database

PURPOSE

The aim of study was to screen factors associated with the overall survival of colorectal cancer patients with lymph nodes metastasis who received neoadjuvant therapy and construct a nomogram model.

METHODS

All enrolled subjects of the SEER database were randomly assigned to the training and testing group in a ratio of 3:2. The patients of Tangdu Hospital were seemed as validation group. Univariate cox regression analysis, lasso regression and random forest survival were used to screen variables related to the survival of advanced CRC patients received neoadjuvant therapy in the training group. Area under curves were adopted to evaluate the 1,3,5-year prediction value of the optimal model in three cohorts. Calibration curves were drawn to observe the prediction accuracy of the nomogram model. Decision curve analysis was used to assess the potential clinical value of the nomogram model.

RESULTS

A total of 1833 subjects were enrolled in this study. After random allocation, 1055 cases of the SEER database served as the training group, 704 cases as the testing group and 74 patients from our center as the external validation group. Variables were screened by univariate cox regression used to construct a nomogram survival prediction model, including M, age, chemotherapy, CEA, perineural invasion, tumor size, LODDS, liver metastasis and radiation. The AUCs of the model for predicting 1-year OS in the training group, testing and validation group were 0.765 (0.703,0.827), 0.772 (0.697,0.847) and 0.742 (0.601,0.883), predicting 3-year OS were 0.761 (0.725,0.780), 0.742 (0.699,0.785), 0.733 (0.560,0.905) and 5-year OS were 0.742 (0.711,0.773), 0.746 (0.709,0.783), 0.838 (0.670,0.980), respectively. The calibration curves showed the difference between prediction probability of the model and the actual survival was not significant in three cohorts and the decision curve analysis revealed the practice clinical application value. And the prediction value of model was better for young CRC than older CRC patients.

CONCLUSION

A nomogram model including LODDS for the prognosis of advanced CRC received neoadjuvant therapy was constructed and verified based on the SEER database and single center practice. The accuracy and potential clinical application value of the model performed well, and the model had better predictive value for EOCRC than LOCRC.

Unveiling the Intricate Dance: How Cancer Orchestrates Muscle Wasting and Sarcopenia

Sarcopenia is a prevalent and clinically significant condition, particularly among older age groups and those with chronic disease. Patients with cancer frequently suffer from sarcopenia and progressive loss of muscle mass, strength, and function. The complex interplay between cancer and its treatment, including medical therapy, radiotherapy, and surgery, significantly contributes to the onset and worsening of sarcopenia. Cancer induces muscle wasting through inflammatory processes, metabolic alterations, and hormonal imbalance. Moreover, medical and radiation therapies exert direct toxic effects on muscles, contributing to the impairment of physical function. Loss of appetite, malnutrition, and physical inactivity further exacerbate muscle wasting in cancer patients. Imaging techniques are the cornerstones for sarcopenia diagnosis. Magnetic resonance imaging, computed tomography, and dual-energy X-ray absorptiometry provide valuable insights into muscle structure and quality. Although each modality has advantages and limitations, magnetic resonance imaging produces high-resolution images and provides dynamic information about muscle function. Despite these challenges, addressing sarcopenia is essential for optimizing treatment outcomes and improving survival rates in patients with cancer. This review explored the factors contributing to sarcopenia in oncologic patients, emphasizing the importance of early detection and comprehensive management strategies.

Artificial intelligence measured 3D body composition to predict pathological response in rectal cancer patients

BACKGROUND

The treatment of locally advanced rectal cancer (LARC) is moving towards total neoadjuvant therapy and potential organ preservation. Of particular interest are predictors of pathological complete response (pCR) that can guide personalized treatment. There are currently no clinical biomarkers which can accurately predict neoadjuvant therapy (NAT) response but body composition (BC) measures present as an emerging contender. The primary aim of the study was to determine if artificial intelligence (AI) derived body composition variables can predict pCR in patients with LARC.

METHODS

LARC patients who underwent NAT followed by surgery from 2012 to 2023 were identified from the Australian Comprehensive Cancer Outcomes and Research Database registry (ACCORD). A validated in-house pre-trained 3D AI model was used to measure body composition via computed tomography images of the entire Lumbar-3 vertebral level to produce a volumetric measurement of visceral fat (VF), subcutaneous fat (SCF) and skeletal muscle (SM). Multivariate analysis between patient body composition and histological outcomes was performed.

RESULTS

Of 214 LARC patients treated with NAT, 22.4% of patients achieved pCR. SM volume (P = 0.015) and age (P = 0.03) were positively associated with pCR in both male and female patients. SCF volume was associated with decreased likelihood of pCR (P = 0.059).

CONCLUSION

This is the first study in the literature utilizing AI-measured 3D Body composition in LARC patients to assess their impact on pathological response. SM volume and age were positive predictors of pCR disease in both male and female patients following NAT for LARC. Future studies investigating the impact of body composition on clinical outcomes and patients on other neoadjuvant regimens such as TNT are potential avenues for further research.

Impact of body composition parameters on radiation therapy compliance in locally advanced rectal cancer: A retrospective observational analysis

Background

The impact of body composition and sarcopenia in locally advanced rectal cancer (LARC) is still unclear, even several studies have been published on this issue. Our study aims to analyze the impact of sarcopenia on neoadjuvant chemoradiotherapy (nCRT) tolerance and survival outcomes.

Methods

This is a retrospective, monocentric study where LARC patients treated between 2010 and 2020 were enrolled. A single slice, from the pre-therapy simulation computed tomography (CT) scan, was used to perform the body composition analysis with dedicated software. The primary endpoint was the impact of body composition on radiotherapy (RT) interruption secondarily on overall survival (OS), disease-free survival (DFS), and local control (LC).

Results

The study included 628 LARC patients (40.9 % female, mean age 63.4 years): 24 % had low skeletal muscle index (SMI), 30 % had low muscle density (MD) and 17 (10.3 % of obese) were sarcopenic obese. Higher BMI (OR 2.38, 95 % CI 1.36-4.01) and lower SMI (0.73, 95 % CI 0.55-0.94) resulted as independent predictors of RT interruption. Sarcopenic obesity (HR 2.83, 95 % CI 1.24-6.45) was related to worse OS, while MD (0.96, 95 % CI 0.93-0.98), and higher SMI (0.97, 95 % CI 0.95-0.99) were related to better OS; a lower MD remained also associated even in adjusted multivariable analysis (0.96, 95 % CI0.93-0.98). Moreover, higher visceral adipose tissue (VAT) resulted associated with worse DFS (1.02, 95 % CI 1.01-1.03), while higher SMI was related to better Local Control (0.96, 95 % CI 0.93-0.99).

Conclusions

Body composition analysis, particularly of muscle and fat masses, may be a useful tool for better management of LARC patients undergoing RT. Increased collaboration between radiation oncologists and clinical nutritionists is advisable, to enable early nutritional support of LARC.

The Role of Exercise in Cancer-Related Sarcopenia and Sarcopenic Obesity

One of the most common adverse effects of cancer and its therapeutic strategies is sarcopenia, a condition which is characterised by excess muscle wasting and muscle strength loss due to the disrupted muscle homeostasis. Moreover, cancer-related sarcopenia may be combined with the increased deposition of fat mass, a syndrome called cancer-associated sarcopenic obesity. Both clinical conditions have significant clinical importance and can predict disease progression and survival. A growing body of evidence supports the claim that physical exercise is a safe and effective complementary therapy for oncology patients which can limit the cancer- and its treatment-related muscle catabolism and promote the maintenance of muscle mass. Moreover, even after the onset of sarcopenia, exercise interventions can counterbalance the muscle mass loss and improve the clinical appearance and quality of life of cancer patients. The aim of this narrative review was to describe the various pathophysiological mechanisms, such as protein synthesis, mitochondrial function, inflammatory response, and the hypothalamic-pituitary-adrenal axis, which are regulated by exercise and contribute to the management of sarcopenia and sarcopenic obesity. Moreover, myokines, factors produced by and released from exercising muscles, are being discussed as they appear to play an important role in mediating the beneficial effects of exercise against sarcopenia.

Everything You Always Wanted to Know about Sarcopenia but Were Afraid to Ask: A Quick Guide for Radiation Oncologists (Impact of Sarcopenia in Radiotherapy: The AFRAID Project)

Sarcopenia (SP) is a syndrome characterized by age-associated loss of skeletal muscle mass and function. SP worsens both acute and late radiation-induced toxicity, prognosis, and quality of life. Myosteatosis is a pathological infiltration of muscle tissue by adipose tissue which often precedes SP and has a proven correlation with prognosis in cancer patients. Sarcopenic obesity is considered a "hidden form" of SP (due to large fat mass) and is independently related to higher mortality and worse complications after surgery and systemic treatments with worse prognostic impact compared to SP alone. The evaluation of SP is commonly based on CT images at the level of the middle of the third lumbar vertebra. On this scan, all muscle structures are contoured and then the outlined surface area is calculated. Several studies reported a negative impact of SP on overall survival in patients undergoing RT for tumors of the head and neck, esophagus, rectum, pancreas, cervix, and lung. Furthermore, several appetite-reducing side effects of RT, along with more complex radiation-induced mechanisms, can lead to SP through, but not limited to, reduced nutrition. In particular, in pediatric patients, total body irradiation was associated with the onset of SP and other changes in body composition leading to an increased risk of cardiometabolic morbidity in surviving adults. Finally, some preliminary studies showed the possibility of effectively treating SP and preventing the worsening of SP during RT. Future studies should be able to provide information on how to prevent and manage SP before, during, or after RT, in both adult and pediatric patients.

Pre-Treatment Computed Tomography Radiomics for Predicting the Response to Neoadjuvant Chemoradiation in Locally Advanced Rectal Cancer: A Retrospective Study

Background and Purpose

Computerized tomography (CT) scans are commonly performed to assist in diagnosis and treatment of locally advanced rectal cancer (LARC). This study assessed the usefulness of pretreatment CT-based radiomics for predicting pathological complete response (pCR) of LARC to neoadjuvant chemoradiotherapy (nCRT).

Materials and Methods

Patients with LARC who underwent nCRT followed by total mesorectal excision surgery from July 2010 to December 2018 were enrolled in this retrospective study. A total of 340 radiomic features were extracted from pretreatment contrast-enhanced CT images. The most relevant features to pCR were selected using the least absolute shrinkage and selection operator (LASSO) method and a radiomic signature was generated. Predictive models were built with radiomic features and clinico-pathological variables. Model performance was assessed with decision curve analysis and was validated in an independent cohort.

Results

The pCR was achieved in 44 of the 216 consecutive patients (20.4%) in this study. The model with the best performance used both radiomics and clinical variables including radiomic signatures, distance to anal verge, lymphocyte-to-monocyte ratio, and carcinoembryonic antigen. This combined model discriminated between patients with and without pCR with an area under the curve of 0.926 and 0.872 in the training and the validation cohorts, respectively. The combined model also showed better performance than models built with radiomic or clinical variables alone.

Conclusion

Our combined predictive model was robust in differentiating patients with and without response to nCRT.