Journal of clinical imaging science · 2026
Computed tomography and magnetic resonance imaging features of struma ovarii: A retrospective case series.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Xiang Lihua, He Xin, Jiang Nan, Shen Ying, Li Guangzheng, Yang Ling
Аннотация
OBJECTIVES: Struma ovarii (SO) is an extremely rare clinical condition. This study retrospectively analyzes clinical and imaging data from 11 misdiagnosed cases of struma ovarii to identify key diagnostic and differential imaging features.
MATERIAL AND METHODS: A retrospective analysis was performed on the clinical and imaging features of 11 patients with initially misdiagnosed but postoperatively confirmed ovarian struma, who were treated at our hospital. Imaging features analyzed included lesion size, computed tomography (CT) density, calcification status, magnetic resonance imaging (MRI) signal characteristics (cystic/solid components), enhancement intensity, and lymph node or distant metastasis. Clinical features analyzed comprised patient symptoms and laboratory test results.
RESULTS: All 11 unilateral ovarian lesions measured 10.77 ± 4.43 cm. MRI demonstrated markedly hypointense foci on T2-weighted images in the cyst wall septa in 90.9% of cases (10/11), isointense to mildly hyperintense signal on T1-weighted images in cystic cavities in 63.6% (7/11), and small to moderate volume ascites in 81.8% (9/11). On contrast-enhanced MRI, the solid components exhibited a honeycomb-like enhancement pattern: enhancement was comparable to the myometrium in 4 cases, greater in 4 cases, and slightly lower in 3 cases. One case demonstrated restricted diffusion on diffusion-weighted imaging along with multiple pelvic disseminated nodules. On non-contrast CT, all cases showed slightly high-density foci (66.56 ± 8.23 HU), with punctate or nodular calcifications in 54.5% (6/11). In the subset of three patients who underwent contrast-enhanced CT, marked enhancement of the solid components was observed in all cases.
CONCLUSION: The radiological manifestations of SO demonstrate distinct characteristic features. When combined with clinical findings, these imaging features may assist in diagnosis and improve diagnostic accuracy.
MATERIAL AND METHODS: A retrospective analysis was performed on the clinical and imaging features of 11 patients with initially misdiagnosed but postoperatively confirmed ovarian struma, who were treated at our hospital. Imaging features analyzed included lesion size, computed tomography (CT) density, calcification status, magnetic resonance imaging (MRI) signal characteristics (cystic/solid components), enhancement intensity, and lymph node or distant metastasis. Clinical features analyzed comprised patient symptoms and laboratory test results.
RESULTS: All 11 unilateral ovarian lesions measured 10.77 ± 4.43 cm. MRI demonstrated markedly hypointense foci on T2-weighted images in the cyst wall septa in 90.9% of cases (10/11), isointense to mildly hyperintense signal on T1-weighted images in cystic cavities in 63.6% (7/11), and small to moderate volume ascites in 81.8% (9/11). On contrast-enhanced MRI, the solid components exhibited a honeycomb-like enhancement pattern: enhancement was comparable to the myometrium in 4 cases, greater in 4 cases, and slightly lower in 3 cases. One case demonstrated restricted diffusion on diffusion-weighted imaging along with multiple pelvic disseminated nodules. On non-contrast CT, all cases showed slightly high-density foci (66.56 ± 8.23 HU), with punctate or nodular calcifications in 54.5% (6/11). In the subset of three patients who underwent contrast-enhanced CT, marked enhancement of the solid components was observed in all cases.
CONCLUSION: The radiological manifestations of SO demonstrate distinct characteristic features. When combined with clinical findings, these imaging features may assist in diagnosis and improve diagnostic accuracy.