Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for nasopharyngeal carcinoma identification during biopsy is low, thus leading to delayed or missed diagnosis for nasopharyngeal carcinoma upon initial attempt. Here, we aimed to develop an artificial intelligence tool to detect nasopharyngeal malignancies and guide biopsy under endoscopic examination based on deep learning.
Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for nasopharyngeal carcinoma identification during biopsy is low, thus leading to delayed or missed diagnosis for nasopharyngeal carcinoma upon initial attempt. Here, we aimed to develop an artificial intelligence tool to detect nasopharyngeal malignancies and guide biopsy under endoscopic examination based on deep learning.
Study Type
OBSERVATIONAL
Enrollment
100
For each participant presenting with a suspicious nasopharyngeal lesion, the attending physician will assess the lesion and determine the appropriate biopsy approach. The physician may decide on multiple biopsies from the lesion area, including one sample from within the lesion itself, another from 5-8 mm outside the lesion, and a third from 8-10 mm beyond the lesion. Alternatively, a single biopsy may be deemed sufficient based on the clinical judgment. Each of these specimens will undergo pathological examination to confirm whether they are carcinomatous or non-carcinomatous.
Fujian Provincial Cancer Hospital
Fuzhou, Fujian, China
RECRUITINGGuangdong Provincial People's Hospital
Guangzhou, Guangdong, China
RECRUITINGNanfang Hospital, Southern Medical University
Guangzhou, Guangdong, China
Aera under the receiver operating characteristic curve (AUC)
AUC of an deep learning-based model in discriminating nasopharyngeal carcinoma from bengin lesion.
Time frame: three months
Accuray
The agreement between the deep learning-based model and the histopathological diagnosis of the three biopsy specimens (inside the lesion, 5-8 mm outside the lesion, and 8-10 mm outside the lesion).
Time frame: three months
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Sun Yat-Sen University Cancer Center
Guangzhou, Guangdong, China
RECRUITINGHainan Provincial People's Hospital
Haikou, Hainan, China
RECRUITING