Autoren Markus Moehler, Salah-Edin Al-Batran, Tilo Andus, Jann Arends, Dirk Arnold, Gustavo Baretton, Jan Bornschein, Wilfried Budach, Severin Daum, Christoph Dietrich, Matthias Ebert, Wolfgang Fischbach, Michael Flentje, Ines Gockel, Lars Grenacher, Jörg Haier, Stefan Höcht, Rolf Jakobs, Christian Jenssen, Barbara Kade, Stefan Kanzler, Jost Langhorst, Hartmut Link, Florian Lordick, Dietmar Lorenz, Sylvie Lorenzen, Manfred Lutz, Helmut Messmann, Hans-Joachim Meyer, Stefan Mönig, Katja Ott, Michael Quante, Christoph Röcken, Peter Schlattmann, Wolff-H. Schmiegel, Andreas Schreyer, Andrea Tannapfel, Peter Thuss-Patience, Arved Weimann, Susanne Unverzagt

/pdf/s3-leitlinie-magenkarzinom-diagnostik-und-therapie-der-16vwjei1rg.pdf

S3-Leitlinie Magenkarzinom – Diagnostik und Therapie der Adenokarzinome des Magens und des ösophagogastralen Übergangs – Langversion 2.0 – August 2019. AWMF-Registernummer: 032/009OL.

http://www.thelancet.com/article/S2589537022000785/pdf

A CT-based deep learning radiomics nomogram for predicting the response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer: A multicenter cohort study

https://doi.org/10.1016/j.compbiomed.2022.105466

Automatic detection of pneumonia in chest X-ray images using textural features

Objectives
To determine whether multiphasic dynamic CT can preoperatively predict lymphovascular invasion (LVI) in advanced gastric cancer (AGC).

Can lymphovascular invasion be predicted by preoperative multiphasic dynamic CT in patients with advanced gastric cancer

/pdf/review-of-ultrasonic-based-technology-for-oil-film-thickness-1bx0l12c.pdf

Review of ultrasonic-based technology for oil film thickness measurement in lubrication

PURPOSE To explore the radiomics features of triple negative breast cancer (TNBC) and non-triple negative breast cancer (non-TNBC) based on X-ray mammography, and to differentiate the two groups of cases. MATERIALS AND METHODS Preoperative mammograms of 120 patients with breast ductal carcinoma confirmed by surgical pathology were retrospectively analyzed, which include 30 TNBC and 90 non-TNBC patients. The manual segmentation of breast lesions was performed by ITK-SNAP software and 12 radiomics features were extracted by Omni-Kinetics software. The differences of these radiomics features between TNBC and non-TNBC groups were compared, and the receiver operating characteristic (ROC) curve was used to determine the optimal cutoff value of each radiomics parameter for differentiating TNBC from non-TNBC, and the corresponding area under the curve (AUC), sensitivity and specificity were obtained. RESULTS There were statistically significant differences for 4 radiomics features between TNBC and non-TNBC datasets (P < 0.05). They were the roundness, concavity, gray average and skewness of breast lesions. Compared with non-TNBC, TNBC cases have following characteristics of (1) more round with the roundness of 0.621 vs. 0.413 (P < 0.001), (2) more regular with the concavity of 0.087 vs. 0.141 (P < 0.01), (3) higher density or gray average (67.261 vs. 56.842, P < 0.05), and (4) lower skewness (- 0.837 vs.- 0.671, P = 0.034). AUCs of ROC curves computed using features of the roundness and concavity were both larger than 0.70. CONCLUSION Radiomics features based on X-ray mammography may be helpful to distinguish between TNBC and non-TNBC, which were associated with breast tumor histology.

A pilot study of radiomics technology based on X-ray mammography in patients with triple-negative breast cancer.

Can 3D pseudo-continuous arterial spin labeling perfusion imaging be applied to predict early response to chemoradiotherapy in patients with advanced nasopharyngeal carcinoma?

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A pilot study of radiomics technology based on X-ray mammography in patients with triple-negative breast cancer.

Can 3D pseudo-continuous arterial spin labeling perfusion imaging be applied to predict early response to chemoradiotherapy in patients with advanced nasopharyngeal carcinoma?