Risk for Upgrade to Malignancy After Breast Core Needle Biopsy Diagnosis of Lobular Neoplasia: A Systematic Review and Meta-Analysis

PurposeLobular neoplasia (LN) detected on breast core needle biopsy is frequently managed with surgical excision because of concern for undersampled malignancy. The authors performed a systematic review and meta-analysis to estimate the risk for upgrade to malignancy in the setting of imaging-concordant classic LN diagnosed on core biopsy.MethodsPubMed and Embase were searched for original articles published from 1998 to 2020 that reported rates of upgrade to malignancy for classic LN, including atypical lobular hyperplasia (ALH) and classic lobular carcinoma in situ (LCIS). Two reviewers extracted study data and assessed the following quality criteria: exclusion of variant LCIS, exclusion of imaging-discordant lesions, and outcome reporting for ≥70% of lesions. For studies meeting all criteria, pooled risks for upgrade to any malignancy (invasive carcinoma or ductal carcinoma in situ) and invasive malignancy for all LN, ALH, and LCIS were estimated using random-effects models.ResultsFor 65 full-text articles included in the review, the risk for upgrade to any malignancy ranged from 0% to 45%. Among the 16 studies that met all quality criteria for the meta-analysis, pooled risks for upgrade to any malignancy were 3.1% (95% confidence interval [CI], 1.8%-5.2%) for all LN, 2.5% (95% CI, 1.6%-3.9%) for ALH, and 5.8% (95% CI, 2.9%-11.3%) for LCIS. Risks for upgrade to invasive malignancy were 1.3% (95% CI, 0.7%-2.4%) for all LN, 0.4% (95% CI, 0.0%-4.2%) for ALH, and 3.5% (95% CI, 2.0%-5.9%) for LCIS.ConclusionsThe risk for upgrade to malignancy for LN found on breast biopsy is low. Imaging surveillance can likely be offered as an alternative to surgical management for LN, particularly for ALH.     

De novo p.G696S mutation in COL4A1 causes intracranial calcification and late-onset cerebral hemorrhage: A case report and review of the literature

BackgroundThe collagen type IV alpha 1 chain (COL4A1) is an essential component of the basement membrane in small vessels. Pathogenic variants in COL4A1 cause perinatal cerebral hemorrhages in an autosomal-dominant fashion. However, little is known about the long-term outcomes of patients with mildly affecting COL4A1 mutations.Case reportWe report a 17-year-old boy, who presented with recurrent intracranial hemorrhages in the periventricular white matter. He had been followed-up as a child with cerebral palsy bearing intracranial calcifications, developmental delay and epilepsy. Screening tests in infancy provided negative results for intrauterine infections. Severe motor and cognitive deficits persisted after admission. Carbazochrome was introduced on day 19 of admission, which appeared to prevent extension and reactivation of cerebral hemorrhages for over 6 months after discharge.ResultsTargeted sequencing of NOTCH3 and TREX1 excluded causal mutations in these genes. The whole-exome sequencing revealed that he carried a de novo mutation in COL4A1 (p.Gly696Ser). An overview of the literature for 345 cases with COL4A1 mutations supported evidence that p.Gly696Ser is associated with the unique phenotype of late-onset hemorrhage among patients with COL4A1-associated cerebral angiopathy.ConclusionsThis case first demonstrates that infants with COL4A1-associated leukoencephalopathy and calcifications have a risk for developing the rupture of small vessels in the cerebral white matter after 10 years of age.     

Optimal combination of antiangiogenic therapy for hepatocellular carcinoma

The success of sorafenib in prolonging survival of patients with hepatocellular carcinoma (HCC) makes therapeutic inhibition of angiogenesis a component of treatment for HCC. To enhance therapeutic efficacy, overcome drug resistance and reduce toxicity, combination of antiangiogenic agents with chemotherapy, radiotherapy or other targeted agents were evaluated. Nevertheless, the use of antiangiogenic therapy remains suboptimal regarding dosage, schedule and duration of therapy. The issue is further complicated by combination antiangiogenesis to other cytotoxic or biologic agents. There is no way to determine which patients are most likely respond to a given form of antiangiogenic therapy. Activation of alternative pathways associated with disease progression in patients undergoing antiangiogenic therapy has also been recognized. There is increasing importance in identifying, validating and standardizing potential response biomarkers for antiangiogenesis therapy for HCC patients. In this review, biomarkers for antiangiogenesis therapy including systemic, circulating, tissue and imaging ones are summarized. The strength and deficit of circulating and imaging biomarkers were further demonstrated by a series of studies in HCC patients receiving radiotherapy with or without thalidomide.     

The Effect of Helicobacter pylori on Gastric Cancer Treated with Adjuvant Chemotherapy After Curative Resection

Helicobacter pylori has been associated with diverse pathologies of varying severity. We investigated the H. pylori infection status and its association with the pathologic features and clinical outcomes in stage III gastric cancer patients treated with adjuvant therapy after curative resection. Between 2004 and 2009, the records of 76 consecutive patients were retrospectively reviewed. H. pylori infection was confirmed by examination of pathological specimen. The relationship between H. pylori and the clinicopathological features was analyzed by Fisher exact test, Student’s t test, and Kaplan-Meier method. Of the 76 patients, 16 patients (21.1 %) were confirmed for H. pylori infection. The median age was 59 years. Twenty-three patients received chemotherapy and remainder received chemoradiotherapy. H. pylori status did not correlate with the clinicopathologic features. It was greater in non-neoplastic tissue than the tumor tissue (21.1 vs 7.9 %). Median follow-up was 21 months. During this period, 88.2 % patients had experienced tumor recurrence, and 85.5 % patients had died. Recurrence was observed in 87.5 % patients and in 88.3 % patients in H. pylori-positive and H. pylori-negative patients, respectively (P = 0.92). Disease-free survival was 28.4 ± 7.9 months and overall survival was 31.5 ± 7.4 months in H. pylori-positive patients compared with 28.3 ± 3.7 and 33.2 ± 3.4 months, respectively, in H. pylori-negative patients. H. pylori infection status did not have effect on the overall or disease-free survival (p = 0.85 and P = 0.86), respectively. H. pylori status might not be useful as a prognostic and predictive factor for clinical outcomes.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.