Article
Radiology, Nuclear Medicine & Medical Imaging
Eui Jin Hwang, Jin Mo Goo, Hyae Young Kim, Jaeyoun Yi, Soon Ho Yoon, Yeol Kim
Summary: Implementing CAD and semi-automated measurement for lung nodules in a nationwide lung cancer screening program resulted in a significant increase in the number of detected nodules and a reduction in variability in positive rates across institutions.
EUROPEAN RADIOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Eui Jin Hwang, Jin Mo Goo, Hyae Young Kim, Soon Ho Yoon, Gong Yong Jin, Jaeyoun Yi, Yeol Kim
Summary: This study evaluated the variability in computer-assisted interpretation of LDCTs among radiologists in a nationwide lung cancer screening program. The results showed significant differences in positive rates and variability between institutional readings and central reviews, indicating that the different usage of computer-assisted systems is a major factor in inter-institution variability.
EUROPEAN RADIOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Xiaoshuai Xu, Linlin Xi, Lili Wei, Luping Wu, Yuming Xu, Bailve Liu, Bo Li, Ke Liu, Gaigai Hou, Hao Lin, Zhe Shao, Kehua Su, Zhengjun Shang
Summary: A deep learning model was developed to accurately identify, locate, and distinguish lymph nodes in contrast-enhanced CT images of oral cancer patients, providing assistance in precise diagnosis and customized treatment planning.
EUROPEAN RADIOLOGY
(2023)
Article
Oncology
Yong Chen, Fei Yuan, Lingyun Wang, Elsie Li, Zhihan Xu, Michael Wels, Weiwu Yao, Huan Zhang
Summary: This study investigates the prognostic value of dual-energy CT based radiomics in predicting disease-free survival (DFS) and overall survival (OS) for patients with advanced gastric cancer (AGC) after neoadjuvant chemotherapy (NAC). The results show that the radiomics signature derived from pre-NAC images performs best in predicting DFS and OS. Compared with the clinical model, the radiomics model has higher predictive accuracy for DFS in the testing cohort, but no significant difference is found for OS. The combined Rad-clinical model shows improved performance in the testing cohort.
Article
Radiology, Nuclear Medicine & Medical Imaging
Cheng Dong, Ying-Mei Zheng, Jian Li, Zeng-Jie Wu, Zhi-Tao Yang, Xiao-Li Li, Wen-Jian Xu, Da-Peng Hao
Summary: A CECT-based radiomics nomogram was constructed and validated for preoperative differentiation between SCC and NHL in the palatine tonsil. The nomogram showed favorable predictive efficacy for distinguishing SCC from NHL, potentially aiding in clinical decision-making.
EUROPEAN RADIOLOGY
(2022)
Article
Urology & Nephrology
Nicolomaria Buffi, Alessandro Uleri, Marco Paciotti, Giovanni Lughezzani, Paolo Casale, Pietro Diana, Ruben DE Groote, Luca Sarchi, Angelo Mottaran, Carlo Bravi, Pieter DE Backer, Daniele Amparore, Cristian Fiori, Francesco Porpiglia, Alex Mottrie
Summary: This study reports the techniques and outcomes of robot-assisted partial nephrectomy (RAPN) for the treatment of multiple ipsilateral renal masses. The study included 61 patients treated with RAPN using the da Vinci Si or Xi surgical system and various technologies such as TilePro, indocyanine green fluorescence, and intraoperative ultrasound. The results showed that RAPN can achieve optimal outcomes by preserving healthy parenchyma while guaranteeing oncological radicality.
MINERVA UROLOGY AND NEPHROLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yura Ahn, Sang Min Lee, Hwa Jung Kim, Jooae Choe, Sang Young Oh, Kyung-Hyun Do, Joon Beom Seo
Summary: This study found that pulmonary vein injury after percutaneous transthoracic needle biopsy (PTNB) can be detected on CT and is associated with air embolism. Careful planning of the needle pathway on CT can reduce the risk of air embolism.
EUROPEAN RADIOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Gauthier Dot, Thomas Schouman, Guillaume Dubois, Philippe Rouch, Laurent Gajny
Summary: The study evaluated the performance of the nnU-Net open-source deep learning framework for automatic multi-task segmentation of craniomaxillofacial structures in CT scans, demonstrating its reliability in preoperative orthognathic CT scans.
EUROPEAN RADIOLOGY
(2022)
Review
Radiology, Nuclear Medicine & Medical Imaging
J. Abel van Stiphout, Jan Driessen, Lennart R. Koetzier, Lara B. Ruules, Martin J. Willemink, Jan W. T. Heemskerk, Aart J. van der Molen
Summary: There were no significant differences in CT values reconstructed by FBP, hybrid IR, and DLR in abdominal organs. DLR images showed a significantly higher SNR and CNR, compared to FBP and hybrid IR.
EUROPEAN RADIOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Simon Lennartz, Aileen O'Shea, Anushri Parakh, Thorsten Persigehl, Bettina Baessler, Avinash Kambadakone
Summary: The study found low robustness of radiomic features extracted from different DECT scanners in patients, with few robust features and limited reflection in phantom experiments. Future efforts should focus on improving the cross-platform generalizability of DECT-derived radiomics.
EUROPEAN RADIOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Sebastian Roehrich, Benedikt H. Heidinger, Florian Prayer, Michael Weber, Markus Krenn, Rui Zhang, Julie Sufana, Jakob Scheithe, Incifer Kanbur, Aida Korajac, Nina Poetsch, Marcus Raudner, Ali Al-Mukhtar, Barbara J. Fueger, Ruxandra-Iulia Milos, Martina Scharitzer, Georg Langs, Helmut Prosch
Summary: The study evaluated the impact of CBIRS on interpreting chest CT scans in patients with diffuse parenchymal lung disease, showing that CBIRS reduced reading time, increased radiologists' information search frequency, and trended towards improving overall diagnostic accuracy when available.
EUROPEAN RADIOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yuesheng Luo, Leilei Liu, Daihong Liu, Hesong Shen, Xiaoxia Wang, Chunbo Fan, Zhen Zeng, Jing Zhang, Yong Tan, Xiaoyue Zhang, Jiaxing Wu, Jiuquan Zhang
Summary: Equilibrium contrast-enhanced CT can be used to determine the ECV fraction in LARC patients after NCRT to predict the likelihood of pCR. The mixed model combining ECVpost and ECV delta has a higher predictive performance in distinguishing between pCR and non-pCR patients.
EUROPEAN RADIOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yang Peng, Guanglei Tang, Mengya Sun, Shuang Yu, Yanglei Cheng, Yu Wang, Weiwei Deng, Yanbing Li, Jian Guan
Summary: This study assessed the feasibility of using spectral CT-derived extracellular volume (ECV) to differentiate aldosterone-producing nodules (APN) from nonfunctioning adrenal nodules (NFN). The results showed that the ECV fraction can effectively differentiate APN from NFN.
EUROPEAN RADIOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Taeho Ha, Wooil Kim, Jaehyung Cha, Young Hen Lee, Hyung Suk Seo, So Young Park, Nan Hee Kim, Sung Ho Hwang, Hwan Seok Yong, Yu-Whan Oh, Eun-Young Kang, Cherry Kim
Summary: DECT parameters play an important role in distinguishing between metastatic and benign lung nodules in thyroid cancer. The study found that specific cutoff values for IC, NIC, lambda HU, NICPA, and Z(eff) can aid in diagnosing metastases.
EUROPEAN RADIOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Sohee Park, Hyunho Park, Sang Min Lee, Yura Ahn, Wooil Kim, Kyuhwan Jung, Joon Beom Seo
Summary: The study found that the use of CAD can slightly improve inter-reader agreement in Lung-RADS categorization while reducing measurement variability and substantial management change in cancer-positive cases.
EUROPEAN RADIOLOGY
(2022)
Editorial Material
Gastroenterology & Hepatology
Seung-Hun Chon, Eleonora Ramadori, Daniel Pinto dos Santos, Florian Lorenz, Hakan Alakus, Tobias Goeser, Christiane Josephine Bruns
Article
Pediatrics
Riwa Meshaka, Daniel Pinto Dos Santos, Owen J. Arthurs, Neil J. Sebire, Susan C. Shelmerdine
Summary: There has been a significant increase in artificial intelligence research in imaging in recent years, but early AI research reporting varies in detail. Inclusion checklists and AI-specific reporting guidelines are now available, but may be daunting for radiologists new to the field. Pediatric radiologists are expected to increasingly lead and contribute to AI imaging research.
PEDIATRIC RADIOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Kai Higashigaito, Gioia Fischer, Lisa Jungblut, Christian Bluthgen, Moritz Schwyzer, Matthias Eberhard, Daniel Pinto dos Santos, Bettina Baessler, Pieter Vuylsteke, Joris A. M. Soons, Thomas Frauenfelder
Summary: Residents in the emergency department may benefit from faster reading time without sacrificing lesion detection rate using AIO for trauma CT.
EUROPEAN RADIOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Simon Bernatz, Saif Afat, Ahmed E. Othman, Konstantin Nikolaou, Malte Sieren, Marwin-Jonathan Saehn, Daniel Pinto dos Santos, Tobias Penzkofer, Andreas Michael Bucher, Bernd Hamm, Thomas J. Vogl, Boris Bodelle
Summary: A survey was conducted among radiological inpatient and outpatient medical staff in Germany to assess their opinions on measures taken during the COVID-19 pandemic. The results showed that technicians were increasingly negatively affected, and there is a need for improvement in the financial support provided by authorities.
ROFO-FORTSCHRITTE AUF DEM GEBIET DER RONTGENSTRAHLEN UND DER BILDGEBENDEN VERFAHREN
(2022)
Review
Oncology
Laure Fournier, Lioe-Fee de Geus-Oei, Daniele Regge, Daniela-Elena Oprea-Lager, Melvin D'Anastasi, Luc Bidaut, Tobias Baeuerle, Egesta Lopci, Giovanni Cappello, Frederic Lecouvet, Marius Mayerhoefer, Wolfgang G. Kunz, Joost J. C. Verhoeff, Damiano Caruso, Marion Smits, Ralf-Thorsten Hoffmann, Sofia Gourtsoyianni, Regina Beets-Tan, Emanuele Neri, Nandita M. deSouza, Christophe M. Deroose, Caroline Caramella
Summary: RECIST is the reference standard for evaluating the efficacy of therapies in patients with solid tumors, but it has limitations and its reproducibility can be affected by various factors. Understanding the difficulties in interpreting treatment response is crucial.
FRONTIERS IN ONCOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Barbara D. Wichtmann, Felix N. Harder, Kilian Weiss, Stefan O. Schoenberg, Ulrike I. Attenberger, Hatem Alkadhi, Daniel Pinto dos Santos, Bettina Baessler
Summary: Before implementing radiomics in routine clinical practice, it is important to understand the repeatability and reproducibility of radiomic features. This study systematically investigates the influence of image processing parameters on radiomic features from MRI, including feature values and test-retest repeatability.
INVESTIGATIVE RADIOLOGY
(2023)
Article
Medicine, General & Internal
Melvin D'Anastasi, Simone Ebenberger, Abdulmajeed Alghamdi, Andreas Helck, Annika Herlemann, Christian Stief, Wael Khoder, Christoph G. Trumm, Robert Stahl
Summary: This study evaluated the technical outcome, clinical success, and safety of low-milliampere CT fluoroscopy-guided percutaneous drain placement in patients with lymphoceles following radical prostatectomy. The results showed high technical success rates, good clinical outcomes, rapid symptom relief, and low complication rates, indicating that this method is a safe and effective treatment option.
Review
Medicine, General & Internal
Burak Kocak, Renato Cuocolo, Daniel Pinto dos Santos, Arnaldo Stanzione, Lorenzo Ugga
Summary: In the field of computer science known as artificial intelligence, algorithms imitate reasoning tasks performed by humans. Machine learning, a subfield of AI, allows machines to learn and improve at tasks such as recognition and prediction. The number of AI and machine learning-related publications in clinical journals has grown exponentially. However, the lack of clinician involvement in data science teams creates barriers in clinical relevance and quality improvement of AI solutions.
BALKAN MEDICAL JOURNAL
(2023)
Article
Medicine, General & Internal
Leon David Gruenewald, Daniel H. H. Leitner, Vitali Koch, Simon S. S. Martin, Ibrahim Yel, Scherwin Mahmoudi, Simon Bernatz, Katrin Eichler, Tatjana Gruber-Rouh, Daniel Pinto Dos Santos, Tommaso DAngelo, Thomas J. J. Vogl, Christian Booz
Summary: This study utilized a dual energy CT post-processing algorithm to assess the integrity of the distal tibiofibular syndesmosis. The color-coded mapping of collagenous structures provided by the algorithm resulted in significantly higher diagnostic accuracy and confidence compared to grayscale CT. This application has the potential to expedite the diagnosis and treatment of distal tibiofibular syndesmosis injury in clinical practice.
Article
Radiology, Nuclear Medicine & Medical Imaging
Scherwin Mahmoudi, Vitali Koch, Daniel Pinto Dos Santos, Jorg Ackermann, Leon D. Gruenewald, Inga Weitkamp, Ibrahim Yel, Simon S. Martin, Moritz H. Albrecht, Jan-Erik Scholtz, Thomas J. Vogl, Simon Bernatz
Summary: The purpose of this study was to evaluate the potential of radiomic features compared to dual-energy CT material decomposition in objectively stratifying abdominal lymph node metastases. The results showed that radiomics models were superior to DECT material decomposition in stratifying abdominal lymph node metastases and may serve as a support tool for early diagnosis and treatment.
EUROPEAN JOURNAL OF RADIOLOGY OPEN
(2023)
Article
Medicine, General & Internal
Robert Stahl, Max Seidensticker, Giovanna Negrao de Figueiredo, Vera Pedersen, Alexander Crispin, Robert Forbrig, Yigit Ozpeynirci, Thomas Liebig, Melvin D'Anastasi, Danilo Hackner, Christoph G. Trumm
Summary: Purpose: To evaluate the technical and clinical effectiveness of CT fluoroscopy-guided drainage (CTD) for symptomatic deep pelvic fluid collections after colorectal surgery. Methods: A retrospective analysis of 43 CTD treatments in 40 patients from 2005 to 2020 was conducted. CTD achieved a technical success rate of 93.0% and clinical success rates of 83.3% for C-reactive Protein and 78.6% for Leukocytes. Conclusion: CTD is a safe and effective treatment option for deep pelvic fluid collections, with excellent technical and clinical outcomes.
Article
Radiology, Nuclear Medicine & Medical Imaging
Felix O. Hofmann, Volker Heinemann, Melvin D'Anastasi, Alena B. Gesenhues, Nina Hesse, Ludwig Fischer von Weikersthal, Thomas Decker, Alexander Kiani, Markus Moehler, Florian Kaiser, Tobias Heintges, Christoph Kahl, Frank Kullmann, Werner Scheithauer, Hartmut Link, Dominik P. Modest, Sebastian Stintzing, Julian W. Holch
Summary: This study aimed to improve the predictive accuracy of early tumor shrinkage (ETS) by using semi-automated volumetry instead of standard diametric measurements. The results showed that continuous diametric and volumetric ETS similarly predicted survival, and a threshold of 45% for volumetric ETS and 20% for diametric ETS accurately identified short-term survivors.
EUROPEAN RADIOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Nathania Bonanno, Dania Cioni, Damiano Caruso, Clemens C. Cyran, Julien Dinkel, Laure Fournier, Sofia Gourtsoyianni, Ralf-Thorsten Hoffmann, Andrea Laghi, Laura Martincich, Marius E. Mayerhoefer, Giulia A. Zamboni, Evis Sala, Heinz-Peter Schlemmer, Emanuele Neri, Melvin D'Anastasi
Summary: A survey of radiologists' opinions on the shift from in-person oncologic multidisciplinary team meetings (MDTMs) to online MDTMs showed that the majority viewed online meetings as a viable alternative, enabling high-quality care and coordination between specialties. The clinical standard of online MDTMs was reported to be comparable to in-person meetings, with no hindrance to interdisciplinary discussion and review of imaging data. Most participants favored a combination of online and in-person meetings.
EUROPEAN RADIOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Lukas Mueller, Aline Maehringer-Kunz, Timo Alexander Auer, Uli Fehrenbach, Bernhard Gebauer, Johannes Haubold, Jens M. Theysohn, Moon-Sung Kim, Jens Kleesiek, Thierno D. Diallo, Michel Eisenblaetter, Dominik Bettinger, Verena Steinle, Philipp Mayer, David Zopfs, Daniel Pinto dos Santos, Roman Kloeckner
Summary: Bone mineral density is an independent predictive factor for survival in patients with hepatocellular carcinoma undergoing transarterial chemoembolization, particularly in elderly patients. Integrating bone mineral density into scoring systems may improve the accuracy of survival prediction and clinical decision-making.
EUROPEAN RADIOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Lukas Mueller, Roman Kloeckner, Aline Maehringer-Kunz, Fabian Stoehr, Christoph Dueber, Gordon Arnhold, Simon Johannes Gairing, Friedrich Foerster, Arndt Weinmann, Peter Robert Galle, Jens Mittler, Daniel Pinto dos Santos, Felix Hahn
Summary: This study trained a deep-learning algorithm to assess spleen volume (SV) in patients with hepatocellular carcinoma (HCC) and investigated SV as a prognostic factor for patients undergoing transarterial chemoembolization (TACE). The results showed that automated SV assessments were superior to two-dimensional spleen size estimates in predicting survival and identifying patients at risk of hepatic decompensation.
EUROPEAN RADIOLOGY
(2022)