Prediction of heart failure and all-cause mortality using cardiac ultrasomics in patients with breast cancer
© 2024. The Author(s), under exclusive licence to Springer Nature B.V..
Breast cancer chemotherapy/immunotherapy can be associated with treatment-limiting cardiotoxicity. Radiomics techniques applied to ultrasound, known as ultrasomics, can be used in cardio-oncology to leverage echocardiography for added prognostic value. To utilize ultrasomics features collected prior to antineoplastic therapy to enhance prediction of mortality and heart failure (HF) in patients with breast cancer. Patients were retrospectively recruited in a study at the West Virginia University Cancer Institute. The final inclusion criteria were met by a total of 134 patients identified for the study. Patients were imaged using echocardiography in the parasternal long axis prior to receiving chemotherapy. All-cause mortality and HF, developed during treatment, were the primary outcomes. 269 features were assessed, grouped into four major classes: demographics (n = 21), heart function (n = 7), antineoplastic medication (n = 17), and ultrasomics (n = 224). Data was split into an internal training (60%, n = 81) and testing (40%, n = 53) set. Ultrasomics features augmented classification of mortality (area under the curve (AUC) 0.89 vs. 0.65, P = 0.003), when compared to demographic variables. When developing a risk prediction score for each feature category, ultrasomics features were significantly associated with both mortality (P = 0.031, log-rank test) and HF (P = 0.002, log-rank test). Further, only ultrasomics features provided significant improvement over demographic variables when predicting mortality (C-Index: 0.78 vs. 0.65, P = 0.044) and HF (C-Index: 0.77 vs. 0.60, P = 0.017), respectively. With further investigation, a clinical decision support tool could be developed utilizing routinely obtained patient data alongside ultrasomics variables to augment treatment regimens.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2024 |
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| Enthalten in: |
The international journal of cardiovascular imaging - (2024) vom: 16. Apr. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Hathaway, Quincy A [VerfasserIn] |
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| Links: |
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| Themen: |
Cardiotoxicity |
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| Anmerkungen: |
Date Revised 16.04.2024 published: Print-Electronic Citation Status Publisher |
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| doi: |
10.1007/s10554-024-03101-2 |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM371147387 |
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| 520 | |a Breast cancer chemotherapy/immunotherapy can be associated with treatment-limiting cardiotoxicity. Radiomics techniques applied to ultrasound, known as ultrasomics, can be used in cardio-oncology to leverage echocardiography for added prognostic value. To utilize ultrasomics features collected prior to antineoplastic therapy to enhance prediction of mortality and heart failure (HF) in patients with breast cancer. Patients were retrospectively recruited in a study at the West Virginia University Cancer Institute. The final inclusion criteria were met by a total of 134 patients identified for the study. Patients were imaged using echocardiography in the parasternal long axis prior to receiving chemotherapy. All-cause mortality and HF, developed during treatment, were the primary outcomes. 269 features were assessed, grouped into four major classes: demographics (n = 21), heart function (n = 7), antineoplastic medication (n = 17), and ultrasomics (n = 224). Data was split into an internal training (60%, n = 81) and testing (40%, n = 53) set. Ultrasomics features augmented classification of mortality (area under the curve (AUC) 0.89 vs. 0.65, P = 0.003), when compared to demographic variables. When developing a risk prediction score for each feature category, ultrasomics features were significantly associated with both mortality (P = 0.031, log-rank test) and HF (P = 0.002, log-rank test). Further, only ultrasomics features provided significant improvement over demographic variables when predicting mortality (C-Index: 0.78 vs. 0.65, P = 0.044) and HF (C-Index: 0.77 vs. 0.60, P = 0.017), respectively. With further investigation, a clinical decision support tool could be developed utilizing routinely obtained patient data alongside ultrasomics variables to augment treatment regimens | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Cardiotoxicity | |
| 650 | 4 | |a Chemotherapy | |
| 650 | 4 | |a Echocardiography | |
| 650 | 4 | |a Immunotherapy | |
| 650 | 4 | |a Radiomics | |
| 650 | 4 | |a Ultrasound | |
| 700 | 1 | |a Abdeen, Yahya |e verfasserin |4 aut | |
| 700 | 1 | |a Conte, Justin |e verfasserin |4 aut | |
| 700 | 1 | |a Hass, Rotem |e verfasserin |4 aut | |
| 700 | 1 | |a Santer, Matthew J |e verfasserin |4 aut | |
| 700 | 1 | |a Alyami, Bandar |e verfasserin |4 aut | |
| 700 | 1 | |a Avalon, Juan Carlo |e verfasserin |4 aut | |
| 700 | 1 | |a Patel, Brijesh |e verfasserin |4 aut | |
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