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Large cell neuroendocrine carcinoma (LCNEC) is an extremely rare malignant tumor of the colon, presenting with more severe clinical outcomes in comparison to colonic adenocarcinoma. There are very few reported cases in the literature. We hereby add our voice to the incidence of this disease by presenting the first report of a patient with ileocolic intussusception secondary to a large cell neuroendocrine cancer of the cecum. The patient was a 48-year-old woman who presented with acute onset of generalized abdominal pain and leukocytosis. CT scan revealed an ileocecal intussusception and multiple liver metastases suggestive of a malignant bowel lesion. She underwent emergency surgery, and an extended right hemicolectomy with ileo-transverse anastomosis was performed. Histology of the resected lesion revealed large cell neuroendocrine carcinoma of the cecum with invasion through the muscularis propria into peri colorectal tissues. The tumor retained mismatch repair (MMR) proteins with low potential for microsatellite instability (MSI). With a clinical diagnosis of stage IV LCNEC, the patient began platinum doublet chemotherapy with carboplatin and etoposide; however, her disease progressed, and the patient expired within a few months after her diagnosis. Clinical diagnosis of adult intussusception should prompt clinicians to rule out malignant etiology. This patient had a large cell neuroendocrine carcinoma of the colon, a rare and extremely aggressive malignancy. Patients with LCNEC will benefit from a multidisciplinary approach to treatment.
RESUMO
Esophageal and gastroesophageal junction (GEJ) malignancies are aggressive, and survival is poor once metastasis occurs. The most common sites of metastatic involvement include the liver, lymph nodes, lung, peritoneum, adrenal glands, bone, and brain, while skeletal muscle (SM) involvement is rare. We report a case of a 68-year-old female who presented with intractable emesis for one month and was found to have a primary GEJ adenocarcinoma measuring up to 6.7 cm. Endoscopic biopsy revealed poorly differentiated GEJ adenocarcinoma with positive AE1/AE3 immunostains. Positron emission tomography/computed tomography and magnetic resonance imaging revealed metastases to the omentum and left lower extremity SMs, including the proximal adductor longus, adductor magnus, and gluteus minimus. This study reviews the literature on SM metastasis in esophageal and GEJ cancer, GEJ cancer classification, incidence, treatment, and prognosis.
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Schwannomas are benign tumors arising from well-differentiated Schwann cells of peripheral nerves. They are usually found on the limbs, head, and neck. It is uncommon for schwannoma to occur in the pelvis and when it does, it is often diagnosed late. Pelvic schwannoma when diagnosed are often bigger in size (>5 cm) and may present with local symptoms such as constipation and bladder outlet obstruction. We hereby present a patient with concurrent metastatic prostate carcinoma and pelvic schwannoma. The patient is a 57-year-old man initially diagnosed with prostate cancer and was lost to follow-up. One year later, he presented with metastatic prostate disease and bladder outlet obstruction. Further evaluation revealed a concurrent pelvic mass that was increasing in size. The biopsy of this mass was suggestive of schwannoma. It was decided at the multidisciplinary tumor board conference to offer treatment for his metastatic prostate disease and observe the schwannoma. His obstructive symptoms worsened in the face of clinical evidence of regression of his prostatic disease, and it was decided to resect the pelvic mass. The surgery revealed a huge soft tissue mass within the pelvis that was adherent to the bladder, prostate, and rectum. Morphology and immunohistochemistry studies of the pelvic mass confirmed the diagnosis of ancient schwannoma. We hereby highlight the clinical importance of this presentation and the diagnostic and therapeutic dilemma involved in the management of this patient who presented with two pathologic conditions causing similar symptoms but of different prognostic and therapeutic significance.
RESUMO
Importance: Anatomic pathology reports are an essential part of health care, containing vital diagnostic and prognostic information. Currently, most patients have access to their test results online. However, the reports are complex and are generally incomprehensible to laypeople. Artificial intelligence chatbots could potentially simplify pathology reports. Objective: To evaluate the ability of large language model chatbots to accurately explain pathology reports to patients. Design, Setting, and Participants: This cross-sectional study used 1134 pathology reports from January 1, 2018, to May 31, 2023, from a multispecialty hospital in Brooklyn, New York. A new chat was started for each report, and both chatbots (Bard [Google Inc], hereinafter chatbot 1; GPT-4 [OpenAI], hereinafter chatbot 2) were asked in sequential prompts to explain the reports in simple terms and identify key information. Chatbot responses were generated between June 1 and August 31, 2023. The mean readability scores of the original and simplified reports were compared. Two reviewers independently screened and flagged reports with potential errors. Three pathologists reviewed the flagged reports and categorized them as medically correct, partially medically correct, or medically incorrect; they also recorded any instances of hallucinations. Main Outcomes and Measures: Outcomes included improved mean readability scores and a medically accurate interpretation. Results: For the 1134 reports included, the Flesch-Kincaid grade level decreased from a mean of 13.19 (95% CI, 12.98-13.41) to 8.17 (95% CI, 8.08-8.25; t = 45.29; P < .001) by chatbot 1 and 7.45 (95% CI, 7.35-7.54; t = 49.69; P < .001) by chatbot 2. The Flesch Reading Ease score was increased from a mean of 10.32 (95% CI, 8.69-11.96) to 61.32 (95% CI, 60.80-61.84; t = -63.19; P < .001) by chatbot 1 and 70.80 (95% CI, 70.32-71.28; t = -74.61; P < .001) by chatbot 2. Chatbot 1 interpreted 993 reports (87.57%) correctly, 102 (8.99%) partially correctly, and 39 (3.44%) incorrectly; chatbot 2 interpreted 1105 reports (97.44%) correctly, 24 (2.12%) partially correctly, and 5 (0.44%) incorrectly. Chatbot 1 had 32 instances of hallucinations (2.82%), while chatbot 2 had 3 (0.26%). Conclusions and Relevance: The findings of this cross-sectional study suggest that artificial intelligence chatbots were able to simplify pathology reports. However, some inaccuracies and hallucinations occurred. Simplified reports should be reviewed by clinicians before distribution to patients.