Generalized lymphangiomatosis-A rare manifestation of lymphatic malformation

Generalized cystic lymphangiomatosis incidentally diagnosed in an asymptomatic adult: Imaging findings of a very rare case

Lymphangiomas are benign lesions of vascular origin with lymphatic differentiation, most commonly found in the head and neck. Generalized lymphangiomatosis is a very rare condition in adults, which is characterized by a diffuse proliferation of lymphatic vessels. The lymphangioma is composed of lymphatic endothelium-lined cystic spaces. This condition can be histologically differentiated from other vascular disorders such as cavernous or capillary hemangioma. However, many cases of lymphangioma can be confused with other vascular disorders, because of overlapping histologic findings. radiologic examinations, such as CT scan and MR imaging, are useful for assessing the morphologic feature and also the extent of disease, it is important to know the radiologic findings of generalized lymphangiomatosis. In this paper, we report a case of generalized lymphangiomatosis in a 42-year-old male who presented with left flank pain and hematuria. The first differential diagnosis was renal colic; hence he underwent an abdominopelvic computed tomography scan (CT scan). In the performed CT scan multiple cystic lesions were seen in the liver and spleen. Also, lytic lesions were seen in bones. CT-guided biopsy was performed and the result was compatible with generalized lymphangiomatosis, confirmed by cytology. Generalized lymphangiomatosis is a rarely reported disease in children and young adults. Delayed diagnosis in older patients or misdiagnosis is common due to its rarity and nonspecific clinical presentation. Different imaging modalities can incidentally diagnose the disease in asymptomatic patients. So radiologists should be aware of the disease manifestations in imaging modalities to diagnose the disease sooner and help the clinician start the therapy if needed.

Computed Tomography Image Characteristics before and after Interventional Treatment of Children's Lymphangioma under Artificial Intelligence Algorithm

The artificial intelligence algorithm was used to analyze the characteristics of computed tomography (CT) images before and after interventional treatment of children's lymphangioma. Retrospective analysis was performed, and 30 children with lymphangioma from the hospital were recruited as the study subjects. The ultrasound-guided bleomycin interventional therapy was adopted and applied to CT scanning through convolutional neural network (CNN). The CT imaging-related indicators before and after interventional therapy were detected, and feature analysis was performed. In addition, the CNN algorithm was adopted to segment the image of the tumor was clearer and more accurate. At the same time, the Dice similarity coefficient (DSC) of the CNN algorithm was 0.9, which had a higher degree of agreement. In terms of clinical symptoms, the cured children's lesions disappeared, the skin surface returned to normal color, and the treatment was smooth. In the two cases with effective treatment, the cystic mass at the lesion site was significantly smaller, and the nodules disappeared. CT images before interventional therapy showed that lymphangiomas in children were more common in the neck. The cystic masses at all lesion sites varied in diameter and size, and most of them were similar to round and irregular, with uniform density distribution. The boundary was clear, the cyst was solid, and there were different degrees of compression and spread to the surrounding structure. Most of them were polycystic, and a few of them were single cystic. After interventional treatment, CT images showed that 27 cases of cured children's lymphangioma completely disappeared. Lymphangioma was significantly reduced in two children with effective treatment. Edema around the tumor also decreased significantly. Patients who did not respond to the treatment received interventional treatment again, and the tumors disappeared completely on CT imaging. No recurrence or new occurrence was found in three-month follow-up. The total effective rate of interventional therapy for lymphangioma in children was 96.67%. The CNN algorithm can effectively compare the CT image features before and after interventional treatment for children's lymphangioma. It was suggested that the artificial intelligence algorithm-aided CT imaging examination was helpful to guide physicians in the accurate treatment of children's lymphangioma.