Radiologists can help identify advanced ovarian cancer patients who have a poor prognosis based on measurements of muscle composition from CT images. This information is valuable to oncologists with respect to patient management, specifically by assessing a patient’s ability to undergo surgery and/or have neoadjuvant chemotherapy. In addition to clinical risk assessment, cancer teams can provide better counsel to patients and their families.
A multi-specialty team of researchers at Mayo Clinic in Rochester, MN, conducted a retrospective study of 296 advanced epithelial ovarian cancer patients to assess the impact of muscle composition and sarcopenia on overall survival and risk of death. Their findings, published in Gynecologic Oncology, determined that lower mean skeletal mass attenuation was associated with worse overall survival. However, it was not associated with progression-free survival for this patient cohort.
Patients suspected of or diagnosed with ovarian cancer typically have an abdominal and pelvic CT scan to determine size, extent and location of tumors. The scan shows skeletal muscle, muscle attenuation, and subcutaneous, intramuscular, and visceral adipose tissue. This enables identification of sarcopenia and sarcopenic obesity, two factors associated with shorter overall survival.
Sarcopenia is the loss of skeletal muscle mass with a decrease in functional strength. It is an important factor with respect to cancer patient evaluation. Sarcopenic obesity impacts morbidity and overall survival. Lead author Amanika Kumar, MD, a fellow in the Division of Gynecologic Surgery of the Department of Obstetrics and Gynecology, and colleagues, report that the condition can have a significant impact on surgical recovery, the ability to tolerate physiologic stress, and the ability to tolerate chemotherapy. They note that studies of other types of cancer show that sarcopenia has been linked to increased rates of infection, longer hospital stays, and decreased progression-free overall survival.
All 296 patients underwent primary cytoreductive surgery for stage IIIC and IV EOC between 2006 through 2012. Thirty days prior to surgery, patients had a CT of the abdomen and pelvis. Nearly half of the patients, 44.6%, were sarcopenic, and 18.9% of the total patient cohort were overweight/obese sarcopenic. The patients were followed between 8.6 and 29 months, with a median follow-up for survivors of 20.6 months.
For the study, a radiologist identified the single axial image at the level of the third lumbar vertebrae on which both transverse processes were first fully visualized. Axial CT images were then analyzed to determine cross-sectional skeletal muscle and adipose tissue areas according to attenuation thresholds using a simple, semi-automated software program (Slice-O-Matic, TomoVision, Magog, Quebec, Canada). Skeletal muscles measured included psoas, erector spinae, quadratus lumborum, transversus abdominis, external and internal obliques, and rectus abdominis muscles. A skeletal muscle index (SMI) was calculated for each patient.
The researchers determined that:
“CT body composition measurements of muscle mass and muscle quality are objective measurements that an be used to understand differences in patient-related factors as it pertains to health outcomes. This will be even more relevant in the age of pay for performance as it can help identify those patients at highest risk of poor surgical and oncologic outcomes,” they wrote.
When talking with Applied Radiology, co-author Andrea Mariani, MD, professor of obstetrics and gynecology in Mayo Clinic’s Division of Gynecologic Surgery said that he encourages radiologists to report muscle attenuation measurements as incidental findings, perhaps also including a reference to this published study. He said, “From my prospective as a surgeon, it would be certainly helpful to have CT scan-selected body composition measurements routinely reported in patients with suspect ovarian cancer, peritoneal carcinomatosis, and ascites.” Dr. Mariani also encourages radiologists to take a proactive role with oncologists to educate them about the value of muscle composition as an outcome factor in patients with advanced ovarian cancer.
Muscle composition measured by CT: A predictor of survival in advanced ovarian cancer. Appl Radiol.