Eosinophilic gastroenteritis (EG) is a rare condition that most commonly affects the stomach and intestine. Large bowel involvement has also been described. We report a case of EG presenting with colitis and cholangitis. This is the first case of associated cholangitis demonstrated radiologically and histologically. Simultaneous biliary and gastrointestinal tract involvement suggest a common link between EG and hypereosinophilic syndrome (HES). However, HES requires high peripheral hypereosinophilia and several organs including gastrointestinal tract, lung, heart, infiltrated with eosinophils. The patient's condition improved with corticosteroids.

We report an 11-year follow-up of a case of granulomatous slack skin. The patient was first treated surgically followed by a rapid relapse. Then he was treated by α-interferon during 15 months. When this treatment was stopped, the disease relapsed again. Extensive surgery was undertaken. Recently, a new relapse has occurred which was again treated by extensive surgery. No other manifestation of a lymphoproliferative disorder appeared. The clinical, histological, immunohistochemical, ultrastructural, molecular biological and genetic studies with a review of 39 other cases described in the literature are presented.

The distinction between hepatobiliary cystadenoma or cystadenocarcinoma and simple hepatic cyst complicated by intracystic hemorrhage may prove difficult to determine on the sole basis of clinical and radiological features because of the presence of intracystic structures and septations well‐demonstrated by ultrasound examination in both situations. We investigated four patients with various types of hepatic cysts, in whom diagnostic difficulties led to further investigations. In this small group, CA 19–9 serum levels were abnormal only in the two patients with cystadenoma or cystadenocarcinoma. Cystic fluid CA 19–9 values were also five times higher in cystadenoma and cystadenocarcinoma than in other benign lesions. Our data thus suggest that the determination of serum and cyst fluid CA 19–9 may be of help in distinguishing between hemorrhagic simple cyst and cystadenoma or cystadenocarcinoma.

Histopathological assessment of ductal carcinoma in situ (DCIS), a non-obligate precursor of invasive breast cancer, is characterized by considerable inter-observer variability. Previously, post hoc dichotomization of multi-categorical variables was used to determine the 'ideal' cut-offs for dichotomous assessment. The present international multi-center study evaluated inter-observer variability among 39 pathologists who performed upfront dichotomous evaluation of 149 consecutive DCIS.All pathologists independently assessed nuclear atypia, necrosis, solid DCIS architecture, calcifications, stromal architecture and lobular cancerization in one digital slide per lesion. Stromal inflammation was assessed semi-quantitatively. Tumor-infiltrating lymphocytes (TILs) were quantified as percentages and dichotomously assessed with a cut-off at 50%. Krippendorff's alpha (KA), Cohen's kappa and intraclass correlation coefficient were calculated for the appropriate variables.Lobular cancerization (KA = 0,396), nuclear atypia (KA = 0,422) and stromal architecture (KA = 0,450) showed the highest inter-observer variability. Stromal inflammation (KA = 0,564), dichotomously assessed TILs (KA = 0,520) and comedonecrosis (KA = 0,539) showed slightly lower inter-observer disagreement. Solid DCIS architecture (KA = 0,602) and calcifications (KA = 0,676) presented with the lowest inter-observer variability. Semi-quantitative assessment of stromal inflammation resulted in a slightly higher inter-observer concordance than upfront dichotomous TILs assessment (KA = 0,564 versus KA = 0,520). High stromal inflammation corresponded best with dichotomously assessed TILs when the cut-off was set at 10% (kappa = 0,881). Nevertheless, a post hoc TILs cut-off set at 20% resulted in the highest inter-observer agreement (KA = 0,669).Despite upfront dichotomous evaluation, the inter-observer variability remains considerable and is at most acceptable, although it varies among the different histopathological features. Future studies should investigate its impact on DCIS prognostication. Forthcoming machine learning algorithms may be useful to tackle this substantial diagnostic challenge.