Mahwash Kassi1, Venkateshwar Polsani2, Robert C Schutt3, Solomon Wong1, Faisal Nabi1, Michael J Reardon1, Dipan J Shah4. 1. Houston Methodist DeBakey Heart and Vascular Center, Houston, Tex. 2. Piedmont Heart Institute, Atlanta, Ga. 3. Memorial Hermann Medical Group, Houston, Tex. 4. Houston Methodist DeBakey Heart and Vascular Center, Houston, Tex. Electronic address: djshah@houstonmethodist.org.
Abstract
BACKGROUND: The purpose of this analysis is to describe the differences in cardiac magnetic resonance characteristics between benign and malignant tumors, which would be helpful for surgical planning. METHODS: This was a prospective cohort study of 130 patients who underwent cardiac magnetic resonance imaging for evaluation of a suspected cardiac mass. After excluding thrombi and tumors without definitive diagnosis, 66 tumors were evaluated for morphologic features and tissue composition. RESULTS: Of the 66 patients, 39 (59.0%) had malignant tumors and 27 (41.0%) had benign tumors. Patients with malignant tumors were younger when compared with those with benign tumors (age 51 years [42.8-60.0] vs 65 years [60.0-71.0] median). Malignant tumors more often demonstrated tumor invasion (69% vs 0% P < .001) and were more often associated with pericardial effusion (41% vs 7.4% P = .004). Presence of first-pass perfusion (100% vs 33% P < .001) and late gadolinium enhancement (100% vs 59.2%, P < .001) were significantly higher in malignant tumors. In logistic regression modeling, tumor invasion (P < .001) and first-pass perfusion (P < .001) were independently associated with malignancy. Furthermore, using classification and regression tree analysis, we developed a decision tree algorithm to help differentiate benign from malignant tumors (diagnostic accuracy ∼90%). The algorithm-weighted cost of misclassifying a malignant tumor as benign was twice that of classifying a benign tumor as malignant. CONCLUSIONS: Our study demonstrates that cardiac magnetic resonance imaging is a useful noninvasive method for differentiating malignant from benign cardiac tumors. Tumor size, invasion, and first-pass perfusion were useful imaging characteristics in differentiating benign from malignant tumors.
BACKGROUND: The purpose of this analysis is to describe the differences in cardiac magnetic resonance characteristics between benign and malignant tumors, which would be helpful for surgical planning. METHODS: This was a prospective cohort study of 130 patients who underwent cardiac magnetic resonance imaging for evaluation of a suspected cardiac mass. After excluding thrombi and tumors without definitive diagnosis, 66 tumors were evaluated for morphologic features and tissue composition. RESULTS: Of the 66 patients, 39 (59.0%) had malignant tumors and 27 (41.0%) had benign tumors. Patients with malignant tumors were younger when compared with those with benign tumors (age 51 years [42.8-60.0] vs 65 years [60.0-71.0] median). Malignant tumors more often demonstrated tumor invasion (69% vs 0% P < .001) and were more often associated with pericardial effusion (41% vs 7.4% P = .004). Presence of first-pass perfusion (100% vs 33% P < .001) and late gadolinium enhancement (100% vs 59.2%, P < .001) were significantly higher in malignant tumors. In logistic regression modeling, tumor invasion (P < .001) and first-pass perfusion (P < .001) were independently associated with malignancy. Furthermore, using classification and regression tree analysis, we developed a decision tree algorithm to help differentiate benign from malignant tumors (diagnostic accuracy ∼90%). The algorithm-weighted cost of misclassifying a malignant tumor as benign was twice that of classifying a benign tumor as malignant. CONCLUSIONS: Our study demonstrates that cardiac magnetic resonance imaging is a useful noninvasive method for differentiating malignant from benign cardiac tumors. Tumor size, invasion, and first-pass perfusion were useful imaging characteristics in differentiating benign from malignant tumors.
Authors: Ayaz Aghayev; Michael K Cheezum; Michael L Steigner; Negareh Mousavi; Robert Padera; Ana Barac; Raymond Y Kwong; Marcelo F Di Carli; Ron Blankstein Journal: J Nucl Cardiol Date: 2021-09-02 Impact factor: 3.872
Authors: Chetan Shenoy; John D Grizzard; Dipan J Shah; Mahwash Kassi; Michael J Reardon; Marianna Zagurovskaya; Han W Kim; Michele A Parker; Raymond J Kim Journal: Eur Heart J Date: 2021-12-28 Impact factor: 35.855