Ji Eun Park1, Young Jin Ryu2,3, Ji Young Kim1,4, Young Hoon Kim1,4, Ji Young Park5, Hyunju Lee5,6, Hyoung Soo Choi5,6. 1. Department of Radiology, Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam, 13620, South Korea. 2. Department of Radiology, Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam, 13620, South Korea. ryuyoungjin1@gmail.com. 3. Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea. ryuyoungjin1@gmail.com. 4. Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea. 5. Department of Pediatrics, Seoul National University Bundang Hospital, Seongnam, South Korea. 6. Department of Pediatrics, Seoul National University College of Medicine, Seoul, South Korea.
Abstract
OBJECTIVES: To establish a diagnostic tree analysis (DTA) model based on ultrasonography (US) findings and clinical characteristics for differential diagnosis of common causes of cervical lymphadenopathy in children. METHODS: A total of 242 patients (131 boys, 111 girls; mean age, 11.2 ± 0.3 years; range, 1 month-18 years) with pathologically confirmed Kikuchi disease (n = 127), reactive hyperplasia (n = 64), lymphoma (n = 24), or suppurative lymphadenitis (n = 27) who underwent neck US were included. US images were retrospectively reviewed to assess lymph node (LN) characteristics, and clinical information was collected from patient records. DTA models were created using a classification and regression tree algorithm on the basis of US imaging and clinical findings. The patients were randomly divided into training (70%, 170/242) and validation (30%, 72/242) datasets to assess the diagnostic performance of the DTA models. RESULTS: In the DTA model based on all predictors, perinodal fat hyperechogenicity, LN echogenicity, and short diameter of the largest LN were significant predictors for differential diagnosis of cervical lymphadenopathy (overall accuracy, 85.3% and 83.3% in the training and validation datasets). In the model based on categorical parameters alone, perinodal fat hyperechogenicity, LN echogenicity, and loss of fatty hilum were significant predictors (overall accuracy, 84.7% and 86.1% in the training and validation datasets). CONCLUSIONS: Perinodal fat hyperechogenicity, heterogeneous echotexture, short diameter of the largest LN, and loss of fatty hilum were significant US findings in the DTA for differential diagnosis of cervical lymphadenopathy in children. KEY POINTS: • Diagnostic tree analysis model based on ultrasonography and clinical findings would be helpful in differential diagnosis of pediatric cervical lymphadenopathy. • Significant predictors were perinodal fat hyperechogenicity, heterogeneous echotexture, short diameter of the largest LN, and loss of fatty hilum.
OBJECTIVES: To establish a diagnostic tree analysis (DTA) model based on ultrasonography (US) findings and clinical characteristics for differential diagnosis of common causes of cervical lymphadenopathy in children. METHODS: A total of 242 patients (131 boys, 111 girls; mean age, 11.2 ± 0.3 years; range, 1 month-18 years) with pathologically confirmed Kikuchi disease (n = 127), reactive hyperplasia (n = 64), lymphoma (n = 24), or suppurative lymphadenitis (n = 27) who underwent neck US were included. US images were retrospectively reviewed to assess lymph node (LN) characteristics, and clinical information was collected from patient records. DTA models were created using a classification and regression tree algorithm on the basis of US imaging and clinical findings. The patients were randomly divided into training (70%, 170/242) and validation (30%, 72/242) datasets to assess the diagnostic performance of the DTA models. RESULTS: In the DTA model based on all predictors, perinodal fat hyperechogenicity, LN echogenicity, and short diameter of the largest LN were significant predictors for differential diagnosis of cervical lymphadenopathy (overall accuracy, 85.3% and 83.3% in the training and validation datasets). In the model based on categorical parameters alone, perinodal fat hyperechogenicity, LN echogenicity, and loss of fatty hilum were significant predictors (overall accuracy, 84.7% and 86.1% in the training and validation datasets). CONCLUSIONS: Perinodal fat hyperechogenicity, heterogeneous echotexture, short diameter of the largest LN, and loss of fatty hilum were significant US findings in the DTA for differential diagnosis of cervical lymphadenopathy in children. KEY POINTS: • Diagnostic tree analysis model based on ultrasonography and clinical findings would be helpful in differential diagnosis of pediatric cervical lymphadenopathy. • Significant predictors were perinodal fat hyperechogenicity, heterogeneous echotexture, short diameter of the largest LN, and loss of fatty hilum.
Authors: Joseph M Aulino; Claudia F E Kirsch; Judah Burns; Paul M Busse; Santanu Chakraborty; Asim F Choudhri; David B Conley; Christopher U Jones; Ryan K Lee; Michael D Luttrull; Toshio Moritani; Bruno Policeni; Maura E Ryan; Lubdha M Shah; Aseem Sharma; Robert Y Shih; Rathan M Subramaniam; Sophia C Symko; Julie Bykowski Journal: J Am Coll Radiol Date: 2019-05 Impact factor: 5.532