A Morphomic Index Is an Independent Predictor of Survival After Lung Cancer Resection

Prognostic Value of Lumbar Muscle Morphometrics for Survival of Patients with Spinal Metastasis: A Systematic Review and Meta-Analysis

BACKGROUND

Spinal metastasis, a prevalent complication of advanced malignancy, poses significant challenges in patient management due to its potential to compromise spinal stability and quality of life. Accurate prognostication is crucial for tailored therapeutic strategies. This meta-analysis aimed to evaluate the prognostic significance of sarcopenia and lumbar muscle morphometrics in patients with spinal metastasis.

METHODS

Electronic databases, including PubMed, Embase, and CENTRAL, were searched up to August 2024. Studies were included if they reported quantitative data on sarcopenia or lumbar muscle morphometric parameters and survival outcomes in patients with spinal metastasis. A quantitative meta-analysis was performed with hazard ratio as the effect size. Heterogeneity was assessed using the Cochran Q test and I2 statistic. Publication bias was evaluated through funnel plot symmetry and Egger's and Begg's regression tests.

RESULTS

Our search identified 17 retrospective cohort studies comprising 3023 patients. Various parameters were employed to assess sarcopenia, encompassing cross-sectional area (CSA) of the psoas muscles (left, right, total, or averaged), the ratio of psoas CSA to vertebral CSA, the ratio of psoas CSA to squared body height, and densities of the psoas or paravertebral muscles. Meta-analysis revealed that total/mean psoas area, when grouped by tertiles or medians, held independent prognostic value for survival outcomes. The ratio of psoas area to vertebral area also demonstrated significant prognostic value when grouped by tertiles or medians.

CONCLUSIONS

Lumbar muscle morphometrics are independent prognostic factors for survival in patients with spinal metastasis. Integrating of these metrics into clinical decision-making could enhance personalized therapeutic strategies and prognostic accuracy.

The Emerging Role and Clinical Applications of Morphomics in Diagnostic Imaging

Analytic morphomics refers to the accurate measurement of specific biological markers of human body composition in diagnostic medical imaging. The increasing prevalence of disease processes that alter body composition including obesity, cachexia, and sarcopenia has generated interest in specific targeted measurement of these metrics to possibly prevent or reduce negative health outcomes. Typical morphomic measurements include the area and density of muscle, bone, vascular calcification, visceral fat, and subcutaneous fat on a specific validated axial level in the patient's cross-sectional diagnostic imaging. A distinct advantage of these measurements is that they can be made retrospectively and opportunistically with pre-existing datasets. We provide a narrative review of the current state of art in morphomics, but also consider some potential future directions for this exciting field. Imaging based quantitative assessment of body composition has enormous potential across the breadth and scope of modern clinical practice. From risk stratification to treatment planning, and outcome assessment, all can be enhanced with the use of analytic morphomics. Moreover, it is likely that many new opportunities for personalized medicine will emerge as the field evolves. As radiologists, embracing analytic morphomics will enable us to contribute added value in the care of every patient.

Adiposity and cancer survival: a systematic review and meta-analysis

PURPOSE

The increasing availability of clinical imaging tests (especially CT and MRI) that directly quantify adipose tissue has led to a rapid increase in studies examining the relationship of visceral, subcutaneous, and overall adiposity to cancer survival. To summarize this emerging body of literature, we conducted a systematic review and meta-analysis of imaging-measured as well as anthropometric proxies for adipose tissue distribution and cancer survival across a wide range of cancer types.

METHODS

Using keywords related to adiposity, cancer, and survival, we conducted a systematic search of the literature in PubMed and MEDLINE, Embase, and Web of Science Core Collection databases from database inception to 30 June 2021. We used a random-effect method to calculate pooled hazard ratios (HR) and corresponding 95% confidence intervals (CI) within each cancer type and tested for heterogeneity using Cochran's Q test and the I2 test.

RESULTS

We included 203 records for this review, of which 128 records were utilized for quantitative analysis among 10 cancer types: breast, colorectal, gastroesophageal, head and neck, hepatocellular carcinoma, lung, ovarian, pancreatic, prostate, and renal cancer. We found that imaging-measured visceral, subcutaneous, and total adiposity were not significantly associated with increased risk of overall mortality, death from primary cancer, or cancer progression among patients diagnosed with these 10 cancer types; however, we found significant or high heterogeneity for many cancer types. For example, heterogeneity was similarly high when the pooled HRs (95% CI) for overall mortality associated with visceral adiposity were essentially null as in 1.03 (0.55, 1.92; I2 = 58%) for breast, 0.99 (0.81, 1.21; I2 = 71%) for colorectal, versus when they demonstrated a potential increased risk 1.17 (0.85, 1.60; I2 = 78%) for hepatocellular carcinoma and 1.62 (0.90, 2.95; I2 = 84%) for renal cancer.

CONCLUSION

Greater adiposity at diagnosis (directly measured by imaging) is not associated with worse survival among cancer survivors. However, heterogeneity and other potential limitations were noted across studies, suggesting differences in study design and adiposity measurement approaches, making interpretation of meta-analyses challenging. Future work to standardize imaging measurements and data analyses will strengthen research on the role of adiposity in cancer survival.

Sarcopenia on preoperative chest computed tomography predicts cancer-specific and all-cause mortality following pneumonectomy for lung cancer: A multicenter analysis

Background

Mortality risk prediction in patients undergoing pneumonectomy for non‐small cell lung cancer (NSCLC) remains imperfect. Here, we aimed to assess whether sarcopenia on routine chest computed tomography (CT) independently predicts worse cancer‐specific (CSS) and overall survival (OS) following pneumonectomy for NSCLC.

Methods

We included consecutive adults undergoing standard or carinal pneumonectomy for NSCLC at Massachusetts General Hospital and Heidelberg University from 2010 to 2018. We measured muscle cross‐sectional area (CSA) on CT at thoracic vertebral levels T8, T10, and T12 within 90 days prior to surgery. Sarcopenia was defined as T10 muscle CSA less than two standard deviations below the mean in healthy controls. We adjusted time‐to‐event analyses for age, body mass index, Charlson Comorbidity Index, forced expiratory volume in 1 second in % predicted, induction therapy, sex, smoking status, tumor stage, side of pneumonectomy, and institution.

Results

Three hundred and sixty‐seven patients (67.4% male, median age 62 years, 16.9% early‐stage) underwent predominantly standard pneumonectomy (89.6%) for stage IIIA NSCLC (45.5%) and squamous cell histology (58%). Sarcopenia was present in 104 of 367 patients (28.3%). Ninety‐day all‐cause mortality was 7.1% (26/367). After a median follow‐up of 20.5 months (IQR, 9.2–46.9), 183 of 367 patients (49.9%) had died. One hundred and thirty‐three (72.7%) of these deaths were due to lung cancer. Sarcopenia was associated with shorter CSS (HR 1.7, p = 0.008) and OS (HR 1.7, p = 0.003).

Conclusions

This transatlantic multicenter study confirms that sarcopenia on preoperative chest CT is an independent risk factor for CSS and OS following pneumonectomy for NSCLC.