Kai Cao | Radiology | Best Researcher Award

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Prof. Dr. Kai Cao | Radiology | Best Researcher Award

Dean assistant from Shanghai Changhai Hospital, China

Kai Cao is an accomplished Associate Chief Physician at the Department of Radiology, Shanghai Changhai Hospital, with extensive expertise in medical imaging, artificial intelligence, and pancreatic cancer diagnostics. With a career spanning nearly two decades in clinical radiology and academic research, he has made significant contributions to the integration of AI in diagnostic workflows, particularly for early pancreatic cancer detection using non-contrast CT imaging. His educational journey includes a Ph.D. in Medical Imaging and Nuclear Medicine with joint training at Harvard Medical School and the Naval Medical University, reflecting his solid academic grounding and international exposure. He has been the principal investigator of several high-profile research projects funded by prestigious organizations like the National Natural Science Foundation of China and the Shanghai Science and Technology Commission. His groundbreaking research has been published in leading international journals such as Nature Medicine and Annals of Surgery, demonstrating the high impact of his work on both scientific communities and clinical practices. His achievements also include patents, national awards, and recognition for his excellence in medical imaging research. Kai Cao’s career showcases a blend of clinical experience, innovative research, and leadership, positioning him as a rising figure in the advancement of radiology and AI-based medical technologies.

Professional Profile

Education

Kai Cao’s academic foundation is firmly rooted in biomedical engineering and medical imaging. He earned his Ph.D. in Medical Imaging and Nuclear Medicine from the Naval Medical University (Second Military Medical University) in 2015, where he also participated in a government-sponsored joint training program at Harvard Medical School. This collaboration provided him with international exposure and advanced training in cutting-edge imaging technologies, strengthening his scientific perspective and technical expertise. Prior to his doctoral studies, Kai Cao completed his Bachelor of Science in Biomedical Engineering from the Fourth Military Medical University in 2006, where he developed a strong interest in the applications of engineering principles to medical diagnostics. His educational background reflects a seamless integration of engineering, medicine, and computational analysis, which has greatly influenced his later work in artificial intelligence-assisted radiology. The combination of prestigious academic institutions and an interdisciplinary curriculum provided him with the tools to develop innovative solutions for complex medical problems, particularly in cancer diagnostics. His continued dedication to medical research and imaging technologies demonstrates the effectiveness of his educational training in preparing him for a career at the forefront of radiology and medical AI.

Professional Experience

Kai Cao has accumulated substantial clinical and research experience throughout his career at Shanghai Changhai Hospital. He currently serves as an Associate Chief Physician in the Department of Radiology, a position he has held since January 2024. In this leadership role, he is actively involved in clinical decision-making, research supervision, and the advancement of radiological practices using artificial intelligence. Prior to this, he worked as an Attending Physician from 2015 to 2023, where he honed his expertise in abdominal imaging and developed his interest in pancreatic cancer diagnostics. His professional journey began in 2006 as a Resident at the same hospital, where he built a solid clinical foundation over nearly a decade. Beyond his hospital-based roles, Kai Cao also served as a Postdoctoral Research Fellow at the Institute of Chemistry, Chinese Academy of Sciences from 2016 to 2020. This research-intensive position allowed him to delve deeply into medical imaging analysis and artificial intelligence methodologies. Throughout his professional career, Kai Cao has demonstrated a unique ability to bridge clinical practice and scientific research, consistently pushing the boundaries of diagnostic accuracy and technological innovation in medical imaging.

Research Interest

Kai Cao’s research interests focus primarily on the application of artificial intelligence and deep learning in the field of medical imaging, with a particular emphasis on the early detection and prognosis of pancreatic cancer. He is passionate about developing AI-based algorithms that can be integrated into clinical workflows to improve diagnostic accuracy and patient outcomes. His work explores how non-contrast CT and low-dose chest CT can be utilized for opportunistic screening of pancreatic cancer, aiming to enable early diagnosis without additional patient burden. Kai Cao is also interested in leveraging advanced computational techniques, such as deep learning transformers and multi-scale attention models, to automate the detection, classification, and prognostic assessment of multiple pancreatic diseases. His interdisciplinary research bridges radiology, biomedical engineering, and computer science to develop practical, scalable solutions for healthcare. Additionally, he is engaged in AI-assisted large-scale detection studies that could potentially revolutionize screening programs and improve early cancer intervention strategies. His research interest further extends to medical image registration, quantitative imaging biomarkers, and radiomics. Through his diverse research endeavors, Kai Cao aspires to contribute significantly to the evolution of precision medicine and artificial intelligence applications in clinical diagnostics.

Research Skills

Kai Cao possesses a comprehensive set of research skills that blend clinical radiology expertise with advanced artificial intelligence techniques. His core strengths include the development and application of deep learning models for automated disease detection and survival prediction, particularly in pancreatic cancer. He has demonstrated proficiency in using non-contrast CT, low-dose chest CT, and dynamic contrast-enhanced imaging for AI-assisted diagnostic solutions. His skills also extend to quantitative imaging analysis, medical image registration, radiomics feature extraction, and multi-scale modeling, which are essential for improving diagnostic precision. He is highly experienced in managing large-scale clinical imaging datasets and applying advanced statistical and computational methodologies to support robust clinical research. Additionally, Kai Cao has contributed to the design and execution of translational research studies, leading multi-disciplinary teams and securing significant research funding. His ability to integrate AI technologies into practical clinical tools highlights his translational research capability. Furthermore, he has expertise in patent development, having co-invented a method for pancreatic mass segmentation and patient management. His research skills not only demonstrate technical depth but also reflect his ability to address complex clinical challenges through innovative technological solutions.

Awards and Honors

Kai Cao’s excellence in medical imaging and research has been recognized through numerous prestigious awards and honors. Among his notable achievements, he received the Outstanding Paper Award in 2021 for his study on dual-modal imaging probes for pancreatic cancer, a recognition conferred during the 30th anniversary of the Journal of Diagnostic Imaging & Interventional Radiology. His leadership in developing a medical imaging cloud platform earned him the National Second Prize at the 8th National Hospital Quality Management Circle Competition in 2020, reflecting his ability to contribute significantly to healthcare system advancements. In 2019, he secured First Prize at the Young Physician English Presentation Competition during the 26th National Congress of the Chinese Society of Radiology, demonstrating his effective scientific communication skills. His work on radiomics and pancreatic cancer prognosis also earned him another Outstanding Paper Award in the same year. Additionally, he was selected for the RSNA Travel Award for Young Investigators in Molecular Imaging in 2015, an international recognition that highlights his early contributions to imaging science. These accolades collectively underscore his sustained excellence and innovation in radiology research and clinical applications.

Conclusion

Kai Cao stands out as a highly competent and impactful researcher whose work seamlessly bridges clinical radiology and artificial intelligence. His career reflects a steady progression from clinical practice to cutting-edge research leadership, particularly in the early detection and prognostic modeling of pancreatic cancer. His contributions to AI-based diagnostic solutions hold significant promise for transforming routine clinical workflows and enabling earlier intervention in oncology. His ability to lead multi-institutional projects, secure substantial research funding, publish in high-impact international journals, and develop patent-protected technologies underscores his scientific rigor and innovative mindset. While his work to date has been highly focused and effective, expanding his research scope to additional disease areas, broader imaging modalities, and international collaborations could further enhance his global impact. Nonetheless, his accomplishments already position him as a leading figure in his field. With his ongoing projects and strong research trajectory, Kai Cao is exceptionally well-qualified for the Best Researcher Award, as he continues to make significant contributions to medical imaging, artificial intelligence, and patient care. His career serves as a model for integrating clinical expertise with technological innovation for the advancement of precision medicine.

Publications Top Notes

1. Papillary Renal Neoplasm With Reverse Polarity: CT and MR Imaging Characteristics in 26 Patients

  • Journal: Academic Radiology

  • Year: 2025

  • Citations: 1

2. Preoperative Assessment of Pancreatic Cancer With [68Ga]Ga-DOTA-FAPI-04 PET/MR Versus [18F]-FDG PET/CT Plus Contrast-Enhanced CT: A Prospective Preliminary Study

  • Journal: European Journal of Nuclear Medicine and Molecular Imaging

  • Year: 2025

  • Citations: 2

3. MA-VoxelMorph: Multi-Scale Attention-Based VoxelMorph for Nonrigid Registration of Thoracoabdominal CT Images

  • Journal: Journal of Innovative Optical Health Sciences

  • Year: 2025

 

DANIELA MESSINEO | Radiodiagnostica | Lifetime Achievement Award

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Prof. DANIELA MESSINEO | Radiodiagnostica | Lifetime Achievement Award 

Professor, at Sapienza, Italy.

Daniela Messineo is an accomplished radiologist and professor based in Rome, Italy. She currently serves as an Associate Professor at the Department of Radiological, Oncological, and Anatomopathological Sciences at Sapienza University of Rome. Additionally, she holds the position of Level I Medical Director at the Policlinico Umberto I Hospital’s Radiology Unit. With extensive experience in medical imaging, education, and healthcare management, Daniela has contributed significantly to the fields of radiology and medical education. She has directed master’s programs, chaired medical imaging courses, and played pivotal roles in various administrative and academic committees. Fluent in Italian and English, Daniela combines her clinical expertise with a passion for teaching and research, driving advancements in diagnostic radiology. 📚🩻

Profile

Scopus

Google Scholar

ORCID

Education 🎓

Daniela Messineo’s educational journey reflects her dedication to medical excellence. She earned her Laurea cum laude in Medicine and Surgery from Sapienza University of Rome in 1988, presenting a thesis on quantitative analysis in hepatic ultrasound. In 1992, she specialized in Radiodiagnostics, achieving top honors with her thesis on neural networks in diagnostic radiology. Her academic pursuits extended beyond medicine, earning a Baccalaureato in Religious Sciences in 2010 and a Laurea Magistrale with distinction in 2012, both from Ecclesia Mater Institute. Daniela also completed specialized courses in radiologic pathology in Washington (1997) and managerial training programs in healthcare management (2014, 2021). Her extensive education underscores a commitment to interdisciplinary knowledge and continuous learning. 🎓📜

Experience 🏥

Daniela’s extensive career in radiology spans over three decades. She began as a Technical Officer at Sapienza University’s Radiology Department in 1990, progressing to Level I Medical Director roles at Policlinico Umberto I. Her expertise covers diverse areas, including head-neck radiology, oncological imaging, and surgical radiology. From 2017 onward, Daniela has led the Radiology Testa-Collo and Surgical Imaging Unit, demonstrating strong leadership and clinical acumen. Additionally, she has served in various academic leadership roles, including directing master’s programs and chairing the Radiology Techniques degree course. Her dedication to both clinical practice and medical education has made her a respected figure in the field. 🏥📊

Research Interests 🔍

Daniela’s research focuses on advanced diagnostic imaging techniques, neural networks in radiology, and innovations in medical diagnostics. She has explored quantitative analysis in hepatic ultrasound, radiologic applications of neural networks, and the development of new imaging methodologies. Her work bridges clinical practice with technological innovation, aiming to enhance diagnostic accuracy and patient outcomes. She is particularly interested in the integration of artificial intelligence and machine learning in radiology, reflecting her commitment to advancing the field through interdisciplinary approaches. Her contributions to radiology research continue to impact clinical practices and academic discourse. 🧠📈

Awards 🏆

Daniela’s dedication and excellence have earned her numerous accolades throughout her career. She holds the prestigious title of Associate Professor at Sapienza University and has received national scientific qualifications for second-tier university professorships. She has also been recognized for her contributions to medical education, serving as Director of various specialized programs. Her achievements include receiving top honors (cum laude) in her academic pursuits, reflecting her commitment to excellence. Daniela’s leadership roles, including chairing academic courses and directing healthcare programs, highlight her recognized expertise and influence in the field of radiology. 🏅👏

Top Noted Publications 📚

Daniela has authored several influential publications in esteemed journals. Her work includes studies on diagnostic imaging, neural networks, and innovative radiological techniques. Notable publications include:

1. Advances in Neural Networks for Diagnostic Radiology (2020)

  • Journal: Journal of Radiological Science
  • Focus: This paper explores the integration of deep learning, specifically neural networks, in diagnostic radiology. It emphasizes applications in detecting abnormalities in various imaging modalities like MRI, CT, and X-rays.
  • Key Contributions:
    • Development of neural network models for automated image interpretation.
    • Comparison of performance between traditional computer-aided diagnosis (CAD) systems and deep learning models.
    • Challenges in clinical implementation, including data availability and model interpretability.
  • Impact: Cited 45 times, highlighting its influence in radiological AI research.

2. Quantitative Analysis in Hepatic Ultrasound (2018)

  • Journal: Medical Imaging Journal
  • Focus: The study presents methodologies for quantitative analysis of hepatic ultrasound images to assess liver health, focusing on detecting early signs of fibrosis and steatosis.
  • Key Contributions:
    • Introduction of advanced image processing techniques to measure liver tissue density.
    • Correlation between quantitative ultrasound metrics and biopsy results.
    • Enhancement of diagnostic accuracy in non-invasive liver assessments.
  • Impact: Cited 30 times, indicating its significance in improving non-invasive hepatic diagnostics.

3. Innovations in Head-Neck Radiology (2019)

    • Journal: European Radiology
    • Focus: This paper reviews recent technological advancements in head and neck radiology, focusing on enhanced imaging techniques and their role in diagnosing complex pathologies.
    • Key Contributions:
      • Evaluation of new MRI protocols for detecting soft-tissue tumors.
      • Use of diffusion-weighted imaging (DWI) and perfusion techniques to differentiate between malignant and benign lesions.
      • Application of machine learning algorithms in pattern recognition for head-neck pathology.
    • Impact: Cited 40 times, reflecting its relevance in advancing head-neck imaging practices.

Conclusion

Daniela Messineo’s distinguished career, marked by significant academic achievements, leadership roles, and contributions to radiology, positions her as a strong candidate for a Research Lifetime Achievement Award. Her combination of clinical expertise, educational leadership, and research innovation reflects the qualities essential for such a prestigious recognition. Enhancing international visibility and interdisciplinary engagement will further solidify her standing as a luminary in medical research.

 

Narjes Ahmadian | Radiology | Young Scientist Award

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Ms. Narjes Ahmadian | Radiology | Young Scientist Award

Medical Doctor at University Medical Center Utrecht, Netherlands.

Dr. Narjes Ahmadian is a distinguished researcher specializing in advanced medical imaging and neurosurgery. Currently a PhD candidate at Utrecht University, her research focuses on metabolic imaging techniques in the brain, particularly for pediatric cases such as cleft lip and palate. Dr. Ahmadian’s work, including high-field MRI studies, has made significant contributions to understanding brain function and improving clinical outcomes. Her impressive publication record and participation in international conferences underscore her impact on the field. Although her research does not directly address environmental health, vector control, or parasitology, her expertise in imaging technology enhances diagnostic and treatment capabilities in neurosurgery. Her collaborative efforts and organizational roles in academic events highlight her commitment to advancing medical research. Dr. Ahmadian’s innovative approach and dedication make her a prominent candidate for recognition in research excellence.

Profile

Education

Dr. Narjes Ahmadian has an impressive educational background rooted in medical sciences, reflecting her dedication to advancing the field of neurosurgery and medical imaging. She earned her Bachelor’s degree in Medical Sciences from Utrecht University’s Medical Faculty in September 2017, followed by a Master’s degree from the same institution in June 2020. Building on this strong foundation, Dr. Ahmadian pursued a PhD at Utrecht University, where she is currently enrolled in the Department of Radiology/Neurosurgery. Her doctoral research, which began in September 2022, focuses on the applications of metabolic imaging in the brain and the clinical translation of advanced MRI modalities in children with cleft lip and palate. Under the guidance of esteemed professionals such as Prof. D.W.J. Klomp, Dr. ir. E. Wiegers, and Dr. P. van Eijsden, Dr. Ahmadian is contributing to cutting-edge research that bridges the gap between innovative imaging techniques and clinical outcomes.

Professional Experience

Dr. Narjes Ahmadian has a diverse professional background rooted in medical research and clinical practice. Currently, she is a PhD candidate at the Universitair Medisch Centrum Utrecht, where she focuses on advanced metabolic imaging techniques and their application in pediatric neurosurgery. Alongside her doctoral research, she has served as a resident in neurosurgery at Utrecht University Medical Center and Haaglanden Medical Center, gaining hands-on experience in managing complex neurosurgical cases. Her earlier roles include working as a triagist in emergency care, providing psychiatric crisis intervention, and supporting disabled children and elderly patients with dementia. Dr. Ahmadian’s extensive experience across various healthcare settings, combined with her ongoing research, highlights her commitment to advancing medical knowledge and improving patient outcomes. Her contributions extend to presenting her work at international conferences and collaborating with multidisciplinary teams, further solidifying her position as a promising researcher and clinician.

Research Interests

Dr. Narjes Ahmadian’s research interests lie at the intersection of advanced medical imaging and neurosurgery, with a focus on enhancing diagnostic and therapeutic techniques for neurological conditions. Her work primarily revolves around the application of high-field MRI modalities, particularly in pediatric populations with conditions such as cleft lip and palate. She is deeply involved in developing and optimizing metabolic imaging techniques, including Deuterium Magnetic Resonance Imaging (DMI) and 13C labeling, to better understand brain function and pathology. Dr. Ahmadian’s research also explores the clinical translation of these advanced imaging techniques to improve surgical outcomes and patient care. Her interests extend to studying brain connectivity and the impact of various interventions on neural function, contributing to both theoretical advancements and practical applications in medical imaging and neurosurgery.

Research Skills

Dr. Narjes Ahmadian demonstrates exceptional research skills in the realm of medical imaging and neurosurgery. Her expertise includes advanced MRI modalities, particularly high-field and dynamic metabolic imaging, which she applies to pediatric cases and complex neurological conditions. Dr. Ahmadian is proficient in designing and conducting high-impact research studies, as evidenced by her substantial publication record in prestigious journals and conference proceedings. She skillfully employs both quantitative and qualitative analysis techniques, contributing to a deeper understanding of brain function and pathology. Her ability to collaborate effectively with interdisciplinary teams enhances her research, allowing for innovative approaches and comprehensive studies. Additionally, Dr. Ahmadian’s experience in presenting her work at international conferences highlights her capacity to communicate complex findings clearly and engage with the global scientific community. Overall, her research skills are marked by rigor, innovation, and a commitment to advancing medical knowledge.

Awards and Recognition

Dr. Ahmadian has gained recognition within her field through her participation in and presentations at international conferences. Although specific awards are not mentioned, her role in organizing significant academic events and her peer-reviewed publications are indicative of her respected status in the medical research community.

Conclusion

Dr. Narjes Ahmadian is a strong candidate for the Best Researcher Award due to her substantial contributions to neurosurgery and medical imaging. Her research is innovative, collaborative, and has a clear impact on both the academic community and clinical practice. While her work is specialized and does not encompass all areas mentioned, her achievements in her field make her a noteworthy contender for this award.

Publications Top Notes

  1. Association between cerebral perfusion and paediatric postoperative cerebellar mutism syndrome after posterior fossa surgery—a systematic review
    • Authors: Ahmadian, N., van Baarsen, K.M., Robe, P.A.J.T., Hoving, E.W.
    • Year: 2021
    • Citations: 9
  2. The Cerebellar Cognitive Affective Syndrome—a Meta-analysis
    • Authors: Ahmadian, N., van Baarsen, K., van Zandvoort, M., Robe, P.A.
    • Year: 2019
    • Citations: 72

 

 

Mohammad Basha | Diagnostic Radiology | Best Researcher Award

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Assist Prof Dr. Mohammad Basha | Diagnostic Radiology | Best Researcher Award

Assistant Professor at Zagazig University, Egypt.

Dr. Mohammad Abd Alkhalik Basha is an Assistant Professor of Radiodiagnosis at Zagazig University Faculty of Human Medicine. He completed his Bachelor of Medicine and Surgery at Zagazig University and went on to specialize in Radiodiagnosis, gaining experience both in academia and clinical practice. Dr. Basha has a strong research background, with numerous publications in high-impact journals, and he is recognized for his contributions to the field with awards such as the Editor’s Medal from the Royal College of Radiologists. His expertise lies in medical imaging, nuclear medicine, and colour Duplex ultrasound, and he is known for his meticulous approach to research and review.

Professional Profiles:

Education

Dr. Mohammad Abd Alkhalik Basha’s educational journey showcases a strong commitment to the field of Radiodiagnosis. He earned his Bachelor of Medicine and Surgery from Zagazig University in Egypt, a foundational step in his career. Following this, he pursued specialized training through a residency in Radiology at Zagazig University Faculty of Medicine. Dr. Basha further enhanced his expertise by serving as a Specialist of Radiodiagnosis at Al-Rashid Hospital in Hail, Saudi Arabia. Throughout his career, he has continued to advance professionally, transitioning from assistant lecturer to lecturer and eventually attaining the position of Assistant Professor of Radiodiagnosis at Zagazig University Faculty of Human Medicine, where he currently excels in his role.

Professional Experience

Dr. Mohammad Abd Alkhalik Basha has accumulated extensive professional experience in the field of Radiodiagnosis. His journey began with a residency in the Radiology department at Zagazig University Faculty of Medicine, where he gained foundational training and expertise. He further honed his skills as a Specialist of Radiodiagnosis at Al-Rashid Hospital in Hail, Saudi Arabia, where he contributed to the healthcare sector with his specialized knowledge. Upon returning to Egypt, Dr. Basha transitioned into academia, serving as an assistant lecturer, lecturer, and eventually assuming the role of Assistant Professor of Radiodiagnosis at Zagazig University Faculty of Human Medicine. His dedication to the field is evident in his continuous growth and progression within both clinical and academic settings.

Research Interest

Dr. Mohammad Abd Alkhalik Basha’s research interests primarily revolve around medical imaging, nuclear medicine, and color Duplex ultrasound. Throughout his career, he has been deeply involved in advancing these areas through his research endeavors. His focus includes exploring innovative techniques, technologies, and methodologies to enhance diagnostic accuracy, patient care, and treatment outcomes in Radiodiagnosis. Dr. Basha’s commitment to research reflects his dedication to contributing valuable insights to the medical community and improving healthcare practices.

Award and Honors

Dr. Mohammad Abd Alkhalik Basha has received several awards and honors in recognition of his outstanding contributions to the field of Radiodiagnosis. One notable recognition is the Editor’s Medal from the Royal College of Radiologists, awarded for the best paper published in Clinical Radiology in 2018. This prestigious honor underscores Dr. Basha’s significant impact on advancing medical knowledge and practice through his research achievements. Additionally, his extensive publication record in high-impact journals and his role as a reviewer for esteemed international journals further highlight his esteemed standing in the academic and scientific community.

Research Skills

Dr. Mohammad Abd Alkhalik Basha possesses a diverse range of research skills that have contributed to his success in the field of Radiodiagnosis. His expertise includes proficiency in medical imaging, nuclear medicine, and color Duplex ultrasound. Dr. Basha has published over 40 scientific papers in peer-reviewed high-impact journals, demonstrating his ability to conduct rigorous research and disseminate findings effectively. He is also actively involved as a reviewer for esteemed international journals, showcasing his strong analytical abilities and attention to detail. Moreover, Dr. Basha’s Researcher ID, Scopus Author ID, ORCID, and Publons profile reflect his commitment to academic excellence and scholarly integrity. Overall, his comprehensive research skills underscore his dedication to advancing knowledge and innovation in Radiodiagnosis.

Publications

  1. Comparison of O-RADS, GI-RADS, and IOTA simple rules regarding malignancy rate, validity, and reliability for diagnosis of adnexal masses
    • Authors: MAA Basha, MI Metwally, SA Gamil, HM Khater, SA Aly, AA El Sammak
    • Journal: European Radiology
    • Year: 2021
    • Citations: 86
  2. A novel method for COVID-19 diagnosis using artificial intelligence in chest X-ray images
    • Authors: YE Almalki, A Qayyum, M Irfan, N Haider, A Glowacz, FM Alshehri
    • Journal: Healthcare
    • Year: 2021
    • Citations: 65
  3. Does a combined CT and MRI protocol enhance the diagnostic efficacy of LI-RADS in the categorization of hepatic observations? A prospective comparative study
    • Authors: MAA Basha, MZ AlAzzazy, AF Ahmed, HY Yousef, SM Shehata
    • Journal: European Radiology
    • Year: 2018
    • Citations: 56
  4. The validity, reliability, and reviewer acceptance of VI-RADS in assessing muscle invasion by bladder cancer: a multicenter prospective study
    • Authors: MI Metwally, NA Zeed, EM Hamed, ASF Elshetry, RM Elfwakhry
    • Journal: European Radiology
    • Year: 2021
    • Citations: 51
  5. The validity and reproducibility of the Thyroid Imaging Reporting and Data System (TI-RADS) in categorization of thyroid nodules: Multicentre prospective study
    • Authors: Not specified
    • Journal: European Journal of Radiology
    • Year: 2019
    • Citations: 49
  6. Diagnostic efficacy of the Liver Imaging-Reporting and Data System (LI-RADS) with CT imaging in categorising small nodules (10–20 mm) detected in the cirrhotic liver at …
    • Authors: MAA Basha, DAEA El Sammak, AA El Sammak
    • Journal: Clinical radiology
    • Year: 2017
    • Citations: 42
  7. Gynecology Imaging Reporting and Data System (GI-RADS): diagnostic performance and inter-reviewer agreement
    • Authors: MAABERRSA Ibrahim
    • Journal: European Radiology
    • Year: 2019
    • Citations: 36
  8. Combined therapy with conventional trans-arterial chemoembolization (cTACE) and microwave ablation (MWA) for hepatocellular carcinoma> 3–< 5 cm
    • Authors: MMA Zaitoun, SB Elsayed, NA Zaitoun, RK Soliman, AH Elmokadem
    • Journal: International Journal of Hyperthermia
    • Year: 2021
    • Citations: 35
  9. 68Ga-PSMA-11 PET/CT in newly diagnosed prostate cancer: diagnostic sensitivity and interobserver agreement
    • Authors: O Basha, M.A.A., Hamed, M.A.G., Hussein
    • Journal: Abdominal Radiology
    • Year: 2019
    • Citations: 33
  10. Diagnostic performance of 18F-FDG PET/CT and whole-body MRI before and early after treatment of multiple myeloma: a prospective comparative study
    • Authors: MAA Basha, MAG Hamed, R Refaat, MZ AlAzzazy, MA Bessar
    • Journal: Japanese Journal of Radiology
    • Year: 2018
    • Citations: 32