David Gruen

PURPOSE: To describe magnetic resonance (MR) imaging and MR cholangiopancreatography (MRCP) findings in gallbladder carcinoma, and to correlate these findings with available surgical and biopsy information. METHODS: Preoperative MR images (T1-weighted spin-echo, T2-weighted fast spin-echo, single shot fast spin-echo, and dynamic gadolinium-enhanced gradient echo) in 34 patients with gallbladder carcinoma were retrospectively reviewed for appearance of the primary neoplasm and for demonstration of hepatic, peritoneal, duodenal, and nodal involvement. Imaging findings were then compared with surgical findings (n = 19 patients) and histologic findings (n = 15 patients). RESULTS: Gallbladder carcinoma manifested at MR imaging as focal gallbladder wall thickening with an eccentric mass in 76% (26/34) of cases. The most common types of regional spread demonstrated were direct liver invasion in 91% (31/34), lymphadenopathy in 76% (26/34), and biliary tract invasion in 62% (21/34). Sensitivity for direct hepatic invasion was 100%, and was 92% for lymph node metastasis. CONCLUSION: MRI and MRCP can provide information relevant to preoperative staging of gallbladder carcinoma.

March 1997Intrahepatic splenosis mimicking hepatic adenoma.Authors: D R Gruen and M J GollubAuthor Info & AffiliationsVolume 168, Issue 3https://doi.org/10.2214/ajr.168.3.9057523 METRICS PDFotherformats

Early morning salivary 17 alpha-hydroxyprogesterone (17-OHP) determination differentiates patients with non-classical 21-hydroxylase deficiency (NC21OHD) from those who are not affected. Using this test, we have conducted a trial screening study for NC21OHD and have compared the study results with previously reported figures for the frequency of this disorder. Testing was performed on 258 subjects recruited from among the medical students and employees of the New York Hospital-Cornell Medical Center. In 2 of the 249 admissible subjects, the 0700-0900 h salivary 17-OHP level was within the range for NC21OHD patients (0.72-6.7 nmol/L; n = 8). These 2 individuals were subsequently confirmed to be affected by ACTH testing. Of the subjects with morning salivary 17-OHP levels below the cut-off point of 0.72 nmol/L, 29 were recalled for ACTH testing and were confirmed to be unaffected. Prevalence of NC21OHD in the test population was determined according to ethnic group. Our study gives a prevalence by screening of 1.14% among caucasians, which agrees with values of 0.81% and 1.06% obtained by different analytical methods. Further, both affected subjects were Ashkenazi Jews, and the prevalence of 3.23% among study members from this group concurs with increased rates of 3.64% and 4.97% already reported. On the basis of a small population sample, screening so far confirms the claim that NC21OHD is the most common autosomal recessive human disorder. Using values from ACTH-proven unaffected subjects (n = 47) and NC21OHD patients (n = 10), we establish preliminary normative data for morning salivary 17-OHP levels of 0.172 nmol/L for unaffected subjects (95% confidence interval, 0.05-0.54 nmol/L) and 1.76 nmol/L for NC21OHD-affected subjects (95% confidence interval, 0.42-7.32 nmol/L).

OBJECTIVE: The purpose of this report is to determine CT imaging findings in patients with Merkel cell carcinoma. MATERIALS AND METHODS: Fifty-three CT scans in 12 patients with biopsy-proven Merkel cell carcinoma were retrospectively reviewed with regard to size, location, and attenuation of primary skin lesions and visceral and lymph node metastases. Findings that were present in 12 patients form the basis of this report. RESULTS: Primary skin lesions were manifested on CT scans in four patients as cutaneous nodules that were hyper- or isodense in relation to muscle. Sites of metastases included regional lymph nodes (n = 6), distant lymph nodes (n = 11), the liver (n = 3), and subcutaneous fat (n = 4). We also found metastases in the mediastinum, the peritoneum, the adrenal gland, and the lung. Usually nodal and subcutaneous metastases were slightly hyperdense. Subcutaneous linear stranding was associated with the lesions. CONCLUSION: CT is useful in the staging of Merkel cell carcinoma.

Background Computational models based on artificial intelligence (AI) are increasingly used to diagnose malignant breast lesions. However, assessment from radiologic images of the specific pathologic lesion subtypes, as detailed in the results of biopsy procedures, remains a challenge. Purpose To develop an AI-based model to identify breast lesion subtypes with mammograms and linked electronic health records labeled with histopathologic information. Materials and Methods In this retrospective study, 26 569 images were collected in 9234 women who underwent digital mammography to pretrain the algorithms. The training data included individuals who had at least 1 year of clinical and imaging history followed by biopsy-based histopathologic diagnosis from March 2013 to November 2018. A model that combined convolutional neural networks with supervised learning algorithms was independently trained to make breast lesion predictions with data from 2120 women in Israel and 1642 women in the United States. Results were reported using the area under the receiver operating characteristic curve (AUC) with the 95% DeLong approach to estimate CIs. Significance was tested with bootstrapping. Results The Israeli model was validated in 456 women and tested in 441 women (mean age, 51 years ± 11 [SD]). The U.S. model was validated in 350 women and tested in 344 women (mean age, 60 years ± 12). For predicting malignancy in the test sets (consisting of 220 Israeli patient examinations and 126 U.S. patient examinations with ductal carcinoma in situ or invasive cancer), the algorithms obtained an AUC of 0.88 (95% CI: 0.85, 0.91) and 0.80 (95% CI: 0.74, 0.85) for Israeli and U.S. patients, respectively (P = .006). These results may not hold for other cohorts of patients, and generalizability across populations should be further investigated. Conclusion The results offer supporting evidence that artificial intelligence applied to clinical and mammographic images can identify breast lesion subtypes when the data are sufficiently large, which may help assess diagnostic workflow and reduce biopsy sampling errors. Published under a CC BY 4.0 license. Online supplemental material is available for this article.