This meta-analysis shows that BRAF mutational status correlates with recurrence of PTMCs, highlighting the potential utility of genotyping in preoperative and postoperative planning. BRAF mutation may be helpful in risk-stratifying patients with PTMC for surgical management versus observation.

ICG NIR fluorescent imaging was useful in detecting the parathyroid glands of dogs. By allowing detection of parathyroid glands, the current technique shows promise for use by endocrine surgeons performing thyroidectomies.

Tumor size, bilaterality, gross ETE, lymph node metastasis, and vascular invasion were associated with locoregional recurrence. Evaluation of these prognostic factors appears to help identify patients who require close monitoring.

4D CT proved helpful in localizing target parathyroid glands of primary HPT that were missed by traditional imaging.

Mammography plays an important role in screening breast cancer among females, and artificial intelligence has enabled the automated detection of diseases on medical images. This study aimed to develop a deep learning model detecting breast cancer in digital mammograms of various densities and to evaluate the model performance compared to previous studies. From 1501 subjects who underwent digital mammography between February 2007 and May 2015, craniocaudal and mediolateral view mammograms were included and concatenated for each breast, ultimately producing 3002 merged images. Two convolutional neural networks were trained to detect any malignant lesion on the merged images. The performances were tested using 301 merged images from 284 subjects and compared to a meta-analysis including 12 previous deep learning studies. The mean area under the receiver-operating characteristic curve (AUC) for detecting breast cancer in each merged mammogram was 0.952 ± 0.005 by DenseNet-169 and 0.954 ± 0.020 by EfficientNet-B5, respectively. The performance for malignancy detection decreased as breast density increased (density A, mean AUC = 0.984 vs. density D, mean AUC = 0.902 by DenseNet-169). When patients’ age was used as a covariate for malignancy detection, the performance showed little change (mean AUC, 0.953 ± 0.005). The mean sensitivity and specificity of the DenseNet-169 (87 and 88%, respectively) surpassed the mean values (81 and 82%, respectively) obtained in a meta-analysis. Deep learning would work efficiently in screening breast cancer in digital mammograms of various densities, which could be maximized in breasts with lower parenchyma density.

PurposeAn inflamed appendix can be removed either openly (open appendectomy [OA]) or laparoscopically (laparoscopic appendectomy [LA]). Surgical-site infection (SSI) is a representative healthcare-associated infection and can impose serious economic burdens on patients as well as affect morbidity and mortality rates. The aim of this study was to compare LA with OA in terms of SSI.MethodsThe medical records of 749 patients (420 males; mean age, 33 years) who underwent appendectomy (OA, 431; LA, 318) between September 1, 2008 and April 29, 2010 were retrospectively reviewed for demographic and pathologic characteristics, recovery of bowel movement, length of hospital stay, and postoperative complications.ResultsThe frequency of purulent/gangrenous or perforated appendicitis was not significantly different between LA and OA groups (83% [263/318 cases] vs. 83% [359/431 cases], P = 0.183). The time to first flatus after surgery was not significantly different between the two groups (1.38 ± 1.07 days for LA, 1.33 ± 0.90 days for OA, P = 0.444), but the length of hospital stay was significantly shorter in LA group than in OA group (3.37 ± 0.12 days vs. 3.83 ± 0.12 days, P = 0.006). The frequency of overall SSI was not significantly different between the two groups (2.8% for LA, 4.6% for OA, P = 0.204), but that of superficial incisional SSI was significantly lower in LA group (0.6% vs. 3.9%, P = 0.016).ConclusionThe results of this study suggest that LA may lead to a shorter length of hospital stay and may have a lower risk of superficial incisional SSI than OA.

No abstract

Methods of diagnosing malignant pheochromocytoma (PCC) or paraganglioma (PGL) are needed. However, there are no reliable histopathologic criteria to distinguish malignant PCC/PGLs. The recent genomic analysis of The Cancer Genome Atlas (TCGA) provides in-depth information enabling more accurate diagnosis of disease entities. Therefore, we investigated genomic expression differences and mutational differences of malignant PCC/PGLs with TCGA. As of December 2014, TCGA had acquired multigenomic analysis of 176 PCC/PGL samples. Clinical information, mutation status, and 20,531 gene messenger RNA (mRNA) expression dataset of normalized RNA-sequencing mRNA read counts were downloaded from TCGA, and integrated into a table. Of the 176 PCC/PGL samples in the dataset, 14 had metastasis and 162 exhibited no metastasis. mRNA expression and mutations were compared in these two groups. There were 76 males in the dataset of 176 TCGA samples. Mean age was 47.6 ± 15.2 years (19-83 years). There was no significant gender or race difference between metastatic and non-metastatic groups. mRNA expression of malignant PCC/PGLs was upregulated in five pathways of cell cycle (BUB1, BUB1B, CCNB2, CDC2, ESPL1), calcium signaling (CCNB2, CDC2, PRKCB1), regulation of actin cytoskeleton (DIAPH3, FGF18, IQGAP3), gap junction (CDC2, PRKCB1), and phosphatidylinositol (PRKCB1, TTK). Disease-free survival rates were significantly correlated with the presence or absence of mutations, such as RP11-798G7.5, HERC2, SETD2, TGDS, TRHDE, FKBP9, and BMS1. TCGA showed differences in mRNA expression and mutations between metastatic and non-metastatic PCC/PGLs. The improved recognition of genetic causes can help to achieve proper diagnosis and provide appropriate treatment of PCC/PGL.