Background: Pancreatic hamartomas are rare entities and difficult to diagnose before resection. We report a case of resected pancreatic hamartoma and literature review of typical characteristics of the lesion. Case presentation: A 78-year-old man presented with a mass in his pancreas, which was incidentally identified when he experienced pneumonia. No remarkable symptoms were observed, and laboratory tests showed no abnormalities, except a slight carcinoembryonic antigen elevation. Enhanced computed tomography and magnetic resonance imaging showed a well-demarcated solid mass with heterogeneous contrast that was 2 cm in size. A gradual enhancement pattern was also observed. The biopsy revealed no specific findings; therefore, surgical resection was necessitated to confirm the diagnosis. Histopathologically, ducts, acinar cells, and adipose cells without atypia were observed among abundant fibrous stroma, but islets of Langerhans and peripheral nerves were absent. An immunohistochemical examination demonstrated CD34 and c-kit positive staining in the stromal cells, S-100 positivity in the adipose cells, and a lack of elastic fibers in the duct walls. The lesion was diagnosed as a pancreatic hamartoma. Conclusion: Asymptomatic pancreatic hamartomas can avoid resection. A careful consideration of imaging and appropriate immunohistochemistry of biopsy specimen may facilitate accurate diagnosis before resection. Therefore, sufficient recognition of the characteristics of pancreatic hamartomas is desirable.

We report serial neuroradiological studies in a patient with focal cerebritis in the head of the left caudate nucleus. On the day after the onset of symptoms, CT showed an ill-defined low density lesion. The lack of contrast enhancement appeared to be the most important finding for differentiating focal cerebritis from an encapsulated brain abscess or a tumour. MRI two days later revealed the centre of the lesion to be of slightly low intensity on T1-weighted inversion recovery (IR) images and very low intensity on T2-weighted spin echo images, which appeared to correspond to the early cerebritis stage of experimentally induced cerebritis and brain abscess. Ten days after the onset of symptoms, CT revealed a thin ring of enhancement in the head of the caudate nucleus, and a similar small ring was seen in the hypothalamus 16 days after the onset, corresponding to the late cerebritis stage. MRI nine days later revealed ill-defined high signal lesions within the involved area on the T1-weighted IR images. To our knowledge, this is the first published MRI documentation of the early cerebritis stage developing into an encapsulated brain abscess. The mechanisms underlying of these radiographic changes are discussed.

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Despite the dedicated research of artificial intelligence (AI) for pathological images, the construction of AI applicable to histopathological tissue subtypes, is limited by insufficient dataset collection owing to disease infrequency. Here, we present a solution involving the addition of supplemental tissue array (TA) images that are adjusted to the tonality of the main data using a cycle-consistent generative adversarial network (CycleGAN) to the training data for rare tissue types. F1 scores of rare tissue types that constitute < 1.2% of the training data were significantly increased by improving recall values after adding color-adjusted TA images constituting < 0.65% of total training patches. The detector also enabled the equivalent discrimination of clinical images from two distinct hospitals and the capability was more increased following color-correction of test data before AI identification (F1 score from 45.2 ± 27.1 to 77.1 ± 10.3, p<0.01). These methods also classified intraoperative frozen sections, while excessive supplementation paradoxically decreased F1 scores. These results identify strategies for constructing AI with an imbalance among the training data, which is important for constructing AI for practical histopathological classification.

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