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Giant cell tumor of bone (GCTB) undergoes a sarcomatous transformation. Secondary malignancy in giant cell tumor (MGCT) is associated with radiotherapy and has a dismal prognosis. We reviewed medical records to investigate the clinicopathological characteristics and prognosis of MGCT patients. The enrollment criterion was high-grade spindle-cell sarcoma, which developed at the site of prior GCTB treatment. Twelve patients were analyzed: six females and six males. The median age was 42.5 years. Benign recurrence occurred in five GCTB patients not treated with radiotherapy. No pulmonary implants were observed. The median latency to the malignant transformation was 63 months. Nine patients were AJCC stage IIB, and three were stage IVA. The median follow-up period after malignant transformation was 62.5 months. Five patients developed local recurrence, and six had distant metastasis. Five-year overall recurrence and metastasis-free survival rates were 61.9%, 66.7%, and 58.3%, respectively. Initial metastasis was a predictive factor for overall survival. Benign local recurrence of GCTB was also a negative factor for metastasis-free survival of MGCT patients. Differences in overall survival according to benign recurrence also showed a tendency toward significance. In our series, secondary MGCT did not occur after radiotherapy. The prognosis was better than previous findings. Benign recurrence of GCTB could reflect the prognosis of MGCT.

A Pleural effusion cytology is vital for treating metastatic breast cancer; however, concerns have arisen regarding the low accuracy and inter-observer variability in cytologic diagnosis. Although artificial intelligence-based image analysis has shown promise in cytopathology research, its application in diagnosing breast cancer in pleural fluid remains unexplored. To overcome these limitations, we evaluate the diagnostic accuracy of an artificial intelligence-based model using a large collection of cytopathological slides, to detect the malignant pleural effusion cytology associated with breast cancer. This study includes a total of 569 cytological slides of malignant pleural effusion of metastatic breast cancer from various institutions. We extracted 34,221 augmented image patches from whole-slide images and trained and validated a deep convolutional neural network model (DCNN) (Inception-ResNet-V2) with the images. Using this model, we classified 845 randomly selected patches, which were reviewed by three pathologists to compare their accuracy. The DCNN model outperforms the pathologists by demonstrating higher accuracy, sensitivity, and specificity compared to the pathologists (81.1% vs. 68.7%, 95.0% vs. 72.5%, and 98.6% vs. 88.9%, respectively). The pathologists reviewed the discordant cases of DCNN. After re-examination, the average accuracy, sensitivity, and specificity of the pathologists improved to 87.9, 80.2, and 95.7%, respectively. This study shows that DCNN can accurately diagnose malignant pleural effusion cytology in breast cancer and has the potential to support pathologists.

Massive retinal gliosis (MRG) is a rare condition of non-neoplastic glial proliferation, which forms massive lesions that fill the eye. MRG is commonly associated with phthisis bulbi (a non-functional eye), congenital anomalies, or malformations. Herein, we report a case of massive retinal gliosis associated with a traumatic phthisis bulbi, which was initially mistaken as a malignant intraocular tumor and confirmed only after an eye enucleation. A 70-year-old woman presented with a protruding ocular mass in her left eye which had slowly grown for a year. She had phthisis bulbi in her left eye due to trauma during her childhood. An orbital CT revealed an intraocular mass lesion with calcifications, raising the possibility of retinoblastoma or other malignant intraocular tumors. Enucleation of the left eye globe was performed. Histopathologic examination revealed exuberant proliferation of the glial cells, metaplastic bone formation, hyalinized vessels, and hyperplasia of the retinal pigment epithelium, confirming the diagnosis of MRG. Although rare, the possibility of MRG should be considered as a differential diagnosis when encountering an intraocular mass lesion, as it can be misdiagnosed as a malignant tumor.