Standardization of body composition status in patients with advanced urothelial tumors: the role of a CT-based aI-powered software for the assessment of sarcopenia and patient outcome correlation

Background: Sarcopenia is a well know prognostic factor in oncology, influencing patients' quality of life and survival. We aimed to investigate the role of sarcopenia, assessed by a Computed Tomography (CT)-based artificial intelligence (AI)-powered-software, as a predictor of objective clinical benefit in advanced urothelial tumors and its correlations with oncological outcomes. Methods: We retrospectively searched patients with advanced urothelial tumors, treated with systemic platinum-based chemotherapy and an available total body CT, performed before and after therapy. An AI-powered software was applied to CT to obtain the Skeletal Muscle Index (SMI-L3), derived from the area of the psoas, long spine, and abdominal muscles, at the level of L3 on CT axial images. Logistic and Cox-regression modeling was implemented to explore the association of sarcopenic status and anthropometric features to the clinical benefit rate and survival endpoints. Results: 97 patients were included, 66 with bladder cancer and 31 with upper-tract urothelial carcinoma. Clinical benefit outcomes showed a linear positive association with all the observed body composition variables variations. The chances of not experiencing disease progression were positively associated with ∆_SMI-L3, ∆_psoas, and ∆_long spine muscle when they ranged from ~10-20% up to ~45-55%. Greater survival chances were matched by patients achieving a wider ∆_SMI-L3, ∆_abdominal and ∆_long spine muscle. Conclusions: A CT-based AI-powered software body composition and sarcopenia analysis provide prognostic assessments for objective clinical benefits and oncological outcomes

Reductions in Muscle Quantity and Quality in Old and Very Old Men: New Insights into the Progression of Sarcopenia

Healthy adult aging is associated with sarcopenia; a loss of skeletal muscle mass known as. Major contributors to this process include functional and morphological changes in the contractile tissue and within the neuromuscular system. Currently, the relationship between muscle mass, normalized strength, structural integrity, and neuromuscular properties [such as motor unit number estimates (MUNE)], in the tibialis anterior (TA) with aging is largely unknown. Therefore, to examine this relationship we recruited twelve young (25 ± 3 years old), six old (68 ± 5 years old) and six very old (79 ± 3 years old) men. Magnetic resonance (MR) images were obtained from the entire musculature of the leg from the tibial plateau to the malleoli. Muscle cross-sectional areas (CSA) were calculated using image processing software. Strength was measured as maximal isometric voluntary dorsiflexion contraction (MVC) torque; this was then normalized to CSA. Structural integrity of the muscle was evaluated by magnetization transfer ratio (MTR) using magnetic resonance imaging (MRI). Neuromuscular measures were also collected and decomposition-enhanced spike-triggered averaging was used to collect surface and intramuscular electromyography (EMG) signals. From these data, estimates of motor unit numbers were made. Muscle CSA was less only in the very old (11.2cm2), no differences existed between the young (13.4cm2) and old (11.7cm2). Strength was ~26% lower in the old and ~24% in the very old than the young. When strength was normalized to CSA there were no differences between the groups. Very old men had ~8% lower MTR values than the young and old men, with no differences between young and old. Neuromuscular measures, specifically the combination of a decreased compound muscle action potential (CMAP) and increased surface motor unit potential (SMUP), resulted in a decrease in MUNE between young [~147 motor units (MU)] and old (~109 MUs) and also between young and very old (~80 MUs). In conclusion, muscular structure and function appear to be maintained in the older adult due to compensatory motor unit remodeling; however in the very old adult the structural integrity of the muscle becomes compromised as motor unit losses are greater resulting in the acceleration of sarcopenia

Resection of colorectal liver metastases - Impact of preoperative chemotherapy

Background Colorectal cancer is a leading cause of cancer related death worldwide. 20-30 % of patients will develop colorectal liver metastases (CRLMs). Surgical resection is the mainstay of treatment for CRLMs, and is often combined with perioperative chemotherapy, which can prolong progression-free survival after resection. Moreover, observation of CRLMs response to preoperative chemotherapy can help to identify patients with progressive disease, which allows for treatment adjustment. However, preoperative chemotherapy can induce liver parenchymal injury, which can negatively affect surgical outcome and be difficult to detect in the preoperative setting. In addition, a worse surgical outcome has also been reported in patients with low preoperative muscle mass. Little is known about whether preoperative chemotherapy worsens skeletal muscle depletion.AimsTo investigate effects of preoperative chemotherapy on the liver and preoperative muscle mass in patients undergoing liver resection for CRLMs, and to investigate whether diffusion-weighted magnetic resonance imaging (MRI) can be used to assess response in CRLMs to preoperative chemotherapy. Patients and methodsIn study I, liver volume measurements were conducted on pre- and postoperative computed tomography (CT) or MRI images in 74 patients who underwent major liver resections for CRLMs. In study II, intraoperative measurement of liver microcirculation was performed using sidestream dark-field imaging in 40 patients before and after liver resection. In study III, liver and spleen elastography was performed in 35 patients before and after liver resection. In study IV, measurement of skeletal muscle mass was carried out on pre- and posttreatment CT images in 97 patients undergoing neoadjuvant chemotherapy for CRLMs. In study V, measurements of the apparent diffusion coefficient (ADC) on pre- and postchemotherapy diffusion-weighted MRI in 49 CRLMs in 27 patients were conducted and compared to the metastases’ pathological chemotherapy response. Results and conclusionsPreoperative chemotherapy for CRLMs negatively affects the liver volume regeneration after a liver resection. The sooner the resection is carried out after the cessation of chemotherapy, the greater the impact on regeneration. Patients with a transient postoperative liver insufficiency have a lower liver volume regeneration than others. A major liver resection leads to an increase in sinusoidal blood velocity and increase in liver and spleen stiffness. Hepatic microcirculation is altered in patients with liver parenchymal injury. Patients lose muscle mass during neoadjuvant chemotherapy, and muscle loss impairs the conditions for adjuvant chemotherapy. After preoperative chemotherapy, an increase in ADC occurs in both pathological responding and non-responding CRLMs, and in study V, there was no difference in the relative change of ADC between the pathological responding and non-responding CRLMs

Analyse der Körperzusammensetzung: Messung der Skelettmuskulatur mit Computertomographie und Implikationen für die Patientenversorgung

Objective: This thesis aims to evaluate the relationship between the skeletal muscle index derived from computed tomography (CT) images and patient outcomes, as well as its implications for patient care. This goal was pursued in five individual studies: Studies A and B evaluated the relationship between the lumbar skeletal muscle index (L3SMI) and patient outcomes in the intensive care unit (ICU) and oncology setting, respectively. Studies C and D evaluated the effect of CT acquisition parameters on body composition measures. Study E proposed a novel technique to automate the segmentation of skeletal muscle using a fully automated deep learning system. Material and methods: In total, 1328 axial CT images were included in the five studies. Patients in studies A and B were part of the clinical trials NCT01967056 and NCT01401907 at Massachusetts General Hospital (MGH), respectively. Body composition indices were computed using semi-automated segmentation. Multivariable regression models with a priori defined covariates were used to analyze clinical outcomes. To evaluate whether CT acquisition parameters influence segmentation, the Bland-Altman approach was used. In study E, a fully convolutional neural network was implemented for deep learning-based automatic segmentation. Results: Study A found lower L3SMI to be a predictor of increased mortality within 30 days of extubation (p = 0.033), increased rate of pneumonia within 30 days of extubation (p = 0.002), increased adverse discharge disposition (p = 0.044), longer hospital stays post-extubation (p = 0.048), and higher total hospital costs (p = 0.043). In study B, low L3SMI was associated with worse quality of life (p = 0.048) and increased depression symptoms (p = 0.005). Threshold-based segmentation of skeletal muscle in study C and adipose tissue compartments in study D were significantly affected by CT acquisition parameters. The proposed deep learning system in study E provided automatic segmentation of skeletal muscle cross-sectional area and achieved a high congruence to segmentations performed by domain experts (average Dice coefficient of 0.93). Conclusion: L3SMI is a useful tool for the assessment of muscle mass in clinical practice. In critically ill patients, L3SMI can provide clinically useful information about patient outcomes at the time of extubation. Patients with advanced cancer who suffered from low muscle mass reported worse quality of life and increased depression symptoms. This highlights the clinical relevance of addressing muscle loss early on as part of a multimodal treatment plan. Importantly, indices utilized in body composition analysis are significantly affected by CT acquisition parameters. These effects should be considered when body composition analysis is used in clinical practice or research studies. Finally, our fully automated deep learning system enabled instantaneous segmentation of skeletal muscle.Zielsetzung: Das Ziel der vorliegenden Dissertation war es, den Einfluss des auf CT-Bildern berechneten Skelettmuskelindexes auf klinische Ergebnisse von Patienten und die daraus resultierenden Implikationen für die Patientenversorgung zu evaluieren. Dieses Ziel wurde in fünf Einzelstudien verfolgt: In den Studien A und B wurde der Einfluss des lumbalen Skelettmuskelindex (L3SMI) auf klinische Endpunkte von Patienten auf der Intensivstation sowie in der Onkologie untersucht. Die Studien C und D evaluierten die Auswirkungen von CT-Akquisitionsparametern auf Indizes der Körperzusammensetzung. Studie E stellte eine neuartige Technik der automatisierten Segmentierung von Skelettmuskulatur vor, die durch maschinelles Lernen ermöglicht wurde. Material und Methoden: Insgesamt wurden 1328 axiale CT-Bilder in die fünf Studien eingeschlossen. Die Patienten der Studien A und B waren Teilnehmer der klinischen Studien NCT01967056 und NCT01401907 am Massachusetts General Hospital. Die Indizes der Körperzusammensetzung wurden mithilfe halbautomatischer Segmentierung berechnet. Die klinischen Endpunkte wurden in multivariablen Regressionsmodellen mit a priori definierten Kovariaten analysiert. Um zu evaluieren, ob CT-Akquisitionsparameter die Segmentierung beeinflussen, wurde der Bland-Altman-Ansatz verwendet. In Studie E wurden ein künstliches neuronales Netzwerk sowie maschinelles Lernen für die automatische Segmentierung eingesetzt. Ergebnisse: In Studie A war ein niedriger L3SMI ein Prädiktor für eine höhere Mortalität (p = 0.033) und Pneumonierate (p = 0.002) innerhalb von 30 Tagen nach der Extubation sowie für mehr ungünstige Entlassungen (p = 0.044) und höhere Behandlungskosten für den gesamten Krankenhausaufenthalt (p = 0.043). Ein niedriger L3SMI war in Studie B mit einer schlechteren Lebensqualität (p = 0.048) und stärkeren depressiven Symptomen (p = 0.005) assoziiert. Die schwellenwertbasierte Segmentierung der Skelettmuskulatur in Studie C und der Fettgewebekompartimente in Studie D wurde durch CT-Akquisitionsparameter signifikant beeinflusst. Das in Studie E vorgestellte vollautomatische Segmentierungssystem erreichte eine hohe Übereinstimmung mit den durch Experten erstellten Segmentationen (durchschnittlicher Dice-Koeffizient von 0.93). Fazit: Der L3SMI ist ein Werkzeug zur Beurteilung von Muskelmasse. Bei Intensivpatienten kann L3SMI zum Zeitpunkt der Extubation nützliche klinische Informationen liefern. Patienten mit fortgeschrittener Krebserkrankung, die zudem eine geringere Muskelmasse hatten, berichteten über eine schlechtere Lebensqualität und stärkere depressive Symptome. Dies unterstreicht die Notwendigkeit, die Muskulatur frühzeitig als Teil eines multimodalen Behandlungskonzeptes zu adressieren. Die Indizes der Körperzusammensetzung werden signifikant von CT-Akquisitionsparametern beeinflusst. Darüber hinaus ermöglichte unser vollautomatisiertes System dank maschinellen Lernens die verzögerungsfreie Segmentierung von Skelettmuskulatur

Quantitative Magnetic Resonance Imaging Techniques for the Measurement of Organ Fat and Body Composition - Validation and Initial Clinical Utility

Ectopic fat is defined by excess deposition of triglycerides in non-adipose tissues that normally contain only small amounts of fat. Measuring the distribution of ectopic fat is important for understanding the pathogenesis of diseases such as obesity and type 2 diabetes mellitus (T2DM) and understanding variation in treatment response amongst patients. Body composition (the proportion of fat and lean mass in the body) is thought to influence both the development of T2DM and outcomes for treatments such as weight-loss surgery. It can also affect clinical outcomes in chronic diseases and malignancy. Quantitative magnetic resonance imaging (qMRI) enables objective measurements of tissue characteristics to be made directly from acquired data. In this thesis, a qMRI protocol based on chemical shift-encoded (CSE)-MRI, specifically the derived proton density fat fraction (PDFF) measurements, was validated against phantoms, and in volunteers and patients with obesity. A new, semi-automated tool for measurement of body composition from CSE-MRI images was developed and validated. CSE-MRI was used to quantify ectopic organ fat depots and body composition in diseases including obesity, T2DM and cancer. Specifically, differences in organ fat between patients with and without remission of T2DM after bariatric surgery was explored. Body composition was investigated in T2DM remission and it was also compared between patients with colorectal and lung cancer undergoing whole body MRI staging. Data from the pilot phase of a study investigating a new duodenal surfacing procedural treatment for T2DM (Revita-2) is presented, demonstrating the utility of hepatic fat content measured using PDFF as an endpoint in an international, multi-centre clinical trial. Finally, I describe the development of a novel technique for quantification of bone mineral density (BMD) using CSE-MRI techniques. The methodology and tools described in this thesis could be used to measure ectopic fat and body composition in future studies and have the potential for integration into clinical care pathways

Sarcopenia is associated with reduced survival in patients with advanced hepatocellular carcinoma undergoing sorafenib treatment

Background: Sarcopenia has been associated with poor outcomes in patients with cirrhosis and solid tumours. Objective: Analyse the influence of sarcopenia on survival and treatment duration in patients with advanced hepatocellular carcinoma (HCC) treated with sorafenib. Methods: We conducted a multicentre, retrospective study on 96 patients with advanced HCC treated with sorafenib, all with available abdominal computed tomography (CT) scan within 30 days from treatment start. Anthropometric, laboratory, treatment and follow-up data were collected. Sarcopenia was defined by reduced skeletal muscle index calculated from an L3 section CT image. Results: Sarcopenia was present in 49% of patients. Patients were divided into two groups according to sarcopenia: age was significantly higher in the sarcopenic group (SG) (66 years (31\u201387) versus 72 years (30\u201384), p = 0.04], with no difference in other baseline characteristics. The SG showed shorter overall survival (OS) (39 (95% confidence interval (CI) 26\u201350) versus 61 (95% CI 47\u201377) weeks (p = 0,01)) and shorter time on treatment (12.3 (95% CI 8\u201319) versus 25.9 (95% CI 15\u201333) weeks (p = 0.0044)). At multivariate analysis, sarcopenia was independently associated to reduced OS (p = 0.03) and reduced time on treatment (p = 0.001). Conclusion: Sarcopenia is present in almost half of patients with advanced HCC, and is associated with reduced survival and reduced duration of oral chemotherapy

Radiological assessment of muscle mass and quality (sarcopenia) in women with breast cancer

Purpose Sarcopenia, the loss of muscle mass, is divided in “primary” or “age-related” and “secondary” when causal factors other than ageing are evident. Cancer is one of the major causes of secondary sarcopenia, associated with negative clinical outcome, even in breast cancer (BC). BC is the most frequently diagnosed cancer in women worldwide. Computer Tomography (CT) is considered the gold standard to evaluate sarcopenia, also in BC patients. Other radiological techniques (Magnetic Resonance Imaging, MRI and Ultrasound, US) can be easily used to assess body composition, especially when CT is not available. The aim of my study was to evaluate with radiological techniques the muscle mass variation in women with BC recruited both prospectively and retrospectively at our University Hospital. A new method to assess muscle mass on breast MRI was developed. The first step was to find if there was a correlation between psoas muscle area (PMA) assessed on CT images and pectoralis muscle area (TPA) assessed on breast MRI. Material and Methods A total of 26 women included in the study was evaluated with both body CT and breast MRI. Reconstructed axial images with both a 1.25-mm and a 5-mm slice thickness and axial T1-weighted images were evaluated by two radiologists to calculate TPA and PMA. Descriptive statistical analysis included inter- and intra-reader agreement and the correlation between TPA on CT and PMA on MRI. Results Comparing axial 5-mm-slice-thickness body CT images and T1-weighted fat-saturated MR images, the Pearson r correlation coefficient was 0.52. Comparing axial 1.25-mm slice thickness body CT images and T1-weighted MR images, the Pearson r (– 1 < r < + 1) correlation coefficient was 0.70 and the coefficient of determination was 0.49, p < 0.05. The inter-reader agreement was almost perfect (0.81–1) for axial 1.25-mm and 5-mm CT images, respectively. The intra-reader agreement of reader 1 was k = 0.98 and k = 0.94 for 1.25-mm and 5-mm CT images, respectively. The intra-reader agreement of reader 2 was 0.95 and 0.94 for 1.25-mm and 5-mm, respectively. On axial pre-contrast T1-weighted images, the inter-reader agreement was 0.61, p < 0.05, considered good (0.61–0.8). Intra-observer agreement of reader 1 and reader 2 for PMA estimation were good (0.62 and 0.64). Conclusion The results demonstrated a strong correlation between PMA assessed on breast MRI and TPA assessed on body CT images. In addition, the technique for measurement of PMA has also been shown to be highly reproducible between different readers.Purpose Pectoralis muscle area (PMA) assessed on breast MRI represented a new method that could be used to evaluate muscle mass in breast cancer (BC) patients, even when body CT is not available. We decided to test the clinical applicability of our method, in particular to evaluate whether the PMA, assessed on breast MRI, varied in BC women, who underwent Neoadjuvant Chemotherapy (NAC). NAC is a type of systemic therapy administered prior to surgery. Material and Methods A total of 110 consecutive patients who were treated with NAC for histologically proven primary BC and in whom tumor response was checked with standard breast MRI were included. Two radiologists calculated the pectoralis muscle cross-sectional area before and after NAC. Wilcoxon-Mann-Whitney U test was used to compare the median values and percentage changes of PMA on MRI examinations, acquired at the beginning of NAC and at the end of NAC. A multivariate regression analysis was performed to evaluate if muscle mass loss correlated with age, time between MRI exams, estrogen and progesterone receptor status, human epidermal growth factor receptor status (HER-2), Ki-67 expression, lymph node status, RECIST criteria, histological type, molecular categories, and grade. Inter- and intra-reader agreement were calculated using Cohen’s kappa test. Results Time between the MRI examinations, before starting NAC and after completing NAC, was 166.8 ± 50 days. PMA calculated pre-NAC (8.14 cm2) was larger than PMA calculated post-NAC (7.03 cm2) (p < 0.001). According to the Response Evaluation Criteria in Solid Tumors (RECIST) criteria, there were no significant differences between responders (complete or partial response) and non-responders (p = 0.362). The multivariate regression analysis did not show any significant relationships between ΔPMA and age, time between MRI exams, estrogen and progesterone receptor status, human epidermal growth factor receptor status (HER-2), Ki-67 expression, lymph node status, RECIST criteria, histological type, average lesion size, molecular categories, and grade. Inter-reader (k = 0.72) and intra-reader agreement (0.69 and 0.71) in PMA assessment were good. Conclusion Pectoralis muscle mass varies in breast cancer patients undergoing NAC and this difference can be estimated directly on standard breast MRI. Pectoralis muscle mass variation assessed on breast MRI may help the evaluation of the risk of toxicities and may optimize patient selection for specific therapeutic protocols with better clinical outcomes.Purpose Cancer is one of the most important causes of sarcopenia, i.e. loss of muscle mass, that is associated with negative clinical outcome, even in breast cancer (BC). BC represents the most common tumor type in young women of reproductive age. The aim of the study is to evaluate if there is pectoralis muscle area (PMA) depletion, reflecting loss of muscle mass, on MRI exams during neoadjuvant chemotherapy (NAC) and to correlate this variation with clinical and histopathological data. Material and Methods A total of 51 patients histologically proven primary invasive ductal breast cancer between January 2019 and September 2021, treated with NAC and in whom tumor response was assessed with breast MRI. Results Time between the two MRI examination (before and after NAC) was 158±25.5 days. Pre-NAC PMA mean value was larger than post-NAC PMA mean value (9.6±2.6 cm2 vs. 8.7±2.2 cm2, p<0.001, delta value 1.41). According to the RECIST criteria, no significant differences between complete and partial response were found. Multivariate regression analysis did not show any significant relationships between ΔPMA and age, time between MRI examinations, estrogen and progesterone receptor status, human epidermal growth factor receptor 2 status, Ki-67 expression, lymph node involvement, RECIST criteria, histological type, and different regimes of NAC. Inter-reader (k=0.75) and intra-reader agreement (0.68 and 0.72) in PMA assessment were good. Conclusions The final study showed body composition changes in terms of loss of skeletal muscle mass in young premenopausal patients with invasive ductal breast cancer undergoing NAC regimes, whose radiological response was assessed on consecutive breast MRI examinations. PMA variation on breast MRI could be a potential tool to diagnose early skeletal muscle mass loss during NAC, emphasizing the risk of increased chemotoxicities and improving patient outcome

Diet-Induced and Age-Related Changes in the Quadriceps Muscle: MRI and MRS in a Rat Model of Sarcopenia

Background: Knowledge about the molecular pathomechanisms of sarcopenia is still sparse, especially with regard to nutritional risk factors and the subtype of sarcopenic obesity. Objective: The aim of this study was to characterize diet-induced and age-related changes on the quality and quantity of the quadriceps muscle in a rat model of sarcopenia by different magnetic resonance (MR) techniques. Methods: A total of 36 6-month-old male Sprague-Dawley rats were randomly subdivided into 2 groups and received either a high-fat diet (HFD) or a control diet (CD). At the age of 16 months, 15 HFD and 18 CD rats underwent MR at 1.5 T. T1-weighted images as well as T2 relaxation time maps were acquired perpendicular to the long axis of the quadriceps muscles. Maximum cross-sectional area (CSA) of the quadriceps muscle was measured on T1-weighted images, and T2 relaxation times of muscle were assessed in a region without visible intramuscular fat (T2lean muscle) and across the complete CSA (T2muscle). Furthermore, 1H-MR spectroscopy was performed to evaluate the relative lipid content of the quadriceps muscles. These measurements were repeated 5 months later in the surviving 8 HFD and 14 CD rats. Results: HFD rats revealed significantly decreased CSA and CSA per body weight (BW) as well as prolonged T2 relaxation times of muscle. A higher weight gain (upper tertile during the first 6 months of diet in CD rats) resulted in a significant change of T2muscle, but had no relevant impact on CSA. Advancing age up to 21 months led to significantly decreased BW, CSA and CSA/BW, significantly prolonged T2muscle and T2lean muscle and enlarged lipid content in the quadriceps muscle. Conclusions: In an experimental setting a chronically fat-enriched diet was shown to have a relevant and age-associated influence on both muscle quantity and quality. By translational means the employed MR techniques give rise to the possibility of an early detection and noninvasive quantification of sarcopenia in humans, which is highly relevant for the field of geriatrics