Dataset Information

Right atrial cavernous hemangioma.

ABSTRACT: Benign cardiac hemangiomas are rare tumors that may present in or out side of the heart, epicardium being the most common site. Echocardiography is the method of choice in diagnosing cardiac masses and though 3D TEE may seem to add exact information about the location, the time constraint in doing a comprehensive examination along with 3D rendering inside operation room may become an hindrance.

SUBMITTER: Shashikanth M

PROVIDER: S-EPMC7559951 | biostudies-literature | 2020 Jul-Sep

REPOSITORIES: biostudies-literature

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Right atrial cavernous hemangioma.

Shashikanth Manikappa M Nicola Sandler S Yi Chen C Julian Smith S

Annals of cardiac anaesthesia 20200701 3

Benign cardiac hemangiomas are rare tumors that may present in or out side of the heart, epicardium being the most common site. Echocardiography is the method of choice in diagnosing cardiac masses and though 3D TEE may seem to add exact information about the location, the time constraint in doing a comprehensive examination along with 3D rendering inside operation room may become an hindrance. ...[more]

PMID: 32687093

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Project description:BackgroundCavernous hemangiomas, more accurately defined as cavernous venous malformations, constitute the most common primary intraorbital tumors of adults comprising 4-9% of all tumors,[4] and the second most frequent cause of unilateral proptosis after thyroid-related orbitopathy.[3] Over 80% are located within the intraconal compartment, most commonly in the lateral aspect.[1] Surgical treatment for orbital cavernous hemangioma is generally required in symptomatic cases, optic nerve compression, and cosmetically disfiguring proptosis.[2] Transcranial approaches, the most familiar approaches for neurosurgeons, provide wide access to the entire superior and lateral orbit. They usually offer direct visualization, allowing for a safer dissection, while minimizing significant injury to the native neural and vascular anatomy of the orbit.[5] Although transcranial approaches continue to evolve, in many cases, they have been supplanted by endoscopic skull base approaches and modifications to deep lateral orbitotomy approaches.[5].Case descriptionA 62-year-old male patient presented with slowly expanding left proptosis, which he had first noticed 3 years before presentation. He was already blind in his right eye due to a history of traumatic amaurosis in childhood. The left eye examination revealed severe proptosis with restricted eye movement in all directions and significant visual impairment (visual acuity of 20/300, expressed by Snellen test, with no improvement on correction). MRI of the orbit showed a large left superolateral intraconal cavernous hemangioma compressing and displacing the optic nerve, with the typical feature of slow gradual irregular enhancement with delayed washout on contrast-enhanced image. A one-piece modified orbitozygomatic approach was performed and a total en block resection was achieved. The bone flap was fixed with titanium miniplates and screws, the temporal muscle and the skin were closed in a standard fashion. The patient did not present any new deficit in the postoperative period. The patient had good functional and cosmetic outcomes with resolution of proptosis, restoration of eye movements, and improvement of visual acuity in the 3-month follow-up. Postoperative MRI showed total resection.ConclusionThe orbitozygomatic approach for large orbital cavernous hemangioma provides satisfactory orbital decompression and large working space, reduces traction, and increases visualization and freedom to dissect small vessels and nerves that may be tightly attached to the tumor pseudocapsule.

Project description:BackgroundCavernous hemangioma and schwannoma are tumors that both occur in the orbit. Because the treatment strategies of these two tumors are different, it is necessary to distinguish them at treatment initiation. Magnetic resonance imaging (MRI) is typically used to differentiate these two tumor types; however, they present similar features in MRI images which increases the difficulty of differential diagnosis. This study aims to devise and develop an artificial intelligence framework to improve the accuracy of clinicians' diagnoses and enable more effective treatment decisions by automatically distinguishing cavernous hemangioma from schwannoma.MethodsMaterial: As the study materials, we chose MRI images as the study materials that represented patients from diverse areas in China who had been referred to our center from more than 45 different hospitals. All images were initially acquired on films, which we scanned into digital versions and recut. Finally, 11,489 images of cavernous hemangioma (from 33 different hospitals) and 3,478 images of schwannoma (from 16 different hospitals) were collected. Labeling: All images were labeled using standard anatomical knowledge and pathological diagnosis. Training: Three types of models were trained in sequence (a total of 96 models), with each model including a specific improvement. The first two model groups were eye- and tumor-positioning models designed to reduce the identification scope, while the third model group consisted of classification models trained to make the final diagnosis.ResultsFirst, internal four-fold cross-validation processes were conducted for all the models. During the validation of the first group, the 32 eye-positioning models were able to localize the position of the eyes with an average precision of 100%. In the second group, the 28 tumor-positioning models were able to reach an average precision above 90%. Subsequently, using the third group, the accuracy of all 32 tumor classification models reached nearly 90%. Next, external validation processes of 32 tumor classification models were conducted. The results showed that the accuracy of the transverse T1-weighted contrast-enhanced sequence reached 91.13%; the accuracy of the remaining models was significantly lower compared with the ground truth.ConclusionsThe findings of this retrospective study show that an artificial intelligence framework can achieve high accuracy, sensitivity, and specificity in automated differential diagnosis between cavernous hemangioma and schwannoma in a real-world setting, which can help doctors determine appropriate treatments.

Dataset Information

Right atrial cavernous hemangioma.

Publications

Right atrial cavernous hemangioma.

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