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"Sinus maksilaris merupakan struktur kraniofasial yang dapat digunakan untuk perkiraan jenis kelamin berdasarkan pengukuran morfometriknya dari gambaran CT-scan. Pada penelitian-penelitian sebelumnya didapakan ukuran morfometrik berbeda-beda pada setiap populasi, karena dipengaruhi oleh faktor ras. Tujuan penelitian ini adalah mencari nilai diagnostik dari ukuran morfometrik panjang, lebar, tinggi dan volume sinus maksilaris terhadap perkiraan jenis kelamin berdasarkan gambaran CT-Scan Maksilofasial pada suatu populasi dewasa di Indonesia. Penelitian ini menggunakan desain potong lintang terhadap 420 sinus maksilaris yang didapatkan dari hasil randomisasi data CT-Scan Maksilofasial pada populasi usia 20-50 tahun di RSUPN Dr. Cipto Mangunkusumo, Jakarta. Analisis bivariat menggunakan uji t tidak berpasangan dan analisis multivariat menggunakan uji regresi logistik. Hasil penelitian ini didapatkan nilai rerata masing-masing laki-laki dan perempuan sebesar 3,90 ± 0,3 cm dan 3.74 ± 0,3 cm pada panjang; 3.42 ± 0,6 cm dan 3.32 ± 0.5 cm pada lebar; 4.29 ± 0,6 cm dan 3.78 ± 0,4 pada tinggi; dan 7.02 ± 1.8 cc dan 6.52 ± 1.3 cc pada volume. Berdasarkan ukuran panjang, lebar, dan tinggi, didapatkan rumus y = -10,760 + 1,319*(P) – 1,647*(L) + 2,796*(T); dengan nilai cut-off sebesar 0,0606 poin, yang memberikan nilai akurasi 79,2%. Berdasarkan ukuran volume didapatkan rumus y = -1,444 + 0,213*(Volume); dengan nilai cut-off sebesar 0,2845 poin, yang memberikan nilai akurasi 58,3%. Dari penelitian ini didapatkan pengukuran morfometrik panjang, lebar, tinggi, dan volume sinus maksilaris dari gambaran CT-Scan maksilofasial dapat digunakan untuk perkiraan jenis kelamin.

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Maxillary sinus is one of maxillofacial structure which can be used in sex estimation based on its morphometric measurement from CT image. Based on the previous studies, the morphometric of maxillary sinus were different in each population, because it was influenced by race. The aim of this study is to find diagnostic value from the morphometric of length, width, height and volume of maxillary sinus from maxillofacial CT image in Indonesian adult population to estimate sex. This study uses a cross-sectional design of 420 maxillary sinus obtained from randomized CT images data in population aged 20-50 years at Cipto Mangunkusumo Hospital, Jakarta. Bivariate analysis using independent T-test and multivariate analysis using logistic regression test. In this study, mean score for men and women is (3.90 ± 0.3) cm and (3.74 ± 0.3) cm on length; (3.42 ± 0.6) cm and (3.32 ± 0.5) cm on width; (4.29 ± 0.6) cm and (3.78 ± 0.4) on height; and (7.02 ± 1.8) cc and (6.52 ± 1.3) cc on volume, respectively. Based on length, width and height, estimation formula is y = -10.760 + 1.319*(L) – 1.647*(W) + 2.796*(H); with cut-off 0,0606 point, given accuracy score of 79,2%. Based on volume, estimation formula is y = -1.444 + 0.213*(volume); with cut-off point 0,2845 point, given accuracy score of 58,3%. The study showed that the morphometric measurement of maxillary sinus from CT image can be used to estimate sex."

"Contents : Head and neck -- The central nervous system -- The spinal column and its contents -- The thorax -- The abdomen -- The pelvis -- The upper limb -- The lower limb -- The breast."

"This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals"

"Summary: Known as the bible of biomedical engineering, The Biomedical Engineering Handbook, Fourth Edition, sets the standard against which all other references of this nature are measured. As such, it has served as a major resource for both skilled professionals and novices to biomedical engineering. Biomedical Signals, Imaging, and Informatics, the third volume of the handbook, presents material from respected scientists with diverse backgrounds in biosignal processing, medical imaging, infrared imaging, and medical informatics"

"Latar Belakang : Tingkat akurasi EUS FNA dalam diagnosis lesi pankreas diduga dipengaruhi oleh berbagai macam faktor. Penelitian mengenai faktor yang mempengaruhi keberhasilan EUS FNA belum pernah dilakukan di Indonesia. Penelitian ini dilakukan untuk mengetahui faktor-faktor yang mempengaruhi keberhasilan EUS FNA untuk diagnosis lesi pankreas pada populasi Indonesia.Metode : Penelitian ini merupakan studi potong lintang dari data rekam medis pada januari 2012-Juli 2022 atau total seluruh subjek yang dilakukan EUS FNA karena lesi pankreas di PESC RSCM. Pasien dengan data tidak lengkap dan lesi peripankreas tidak diikutkan. Karakteristik dasar subjek penelitian ditampilkan dalam bentuk tabel. Analisis bivariat menggunakan uji chi square dilakukan dengan masing-masing variabel bebas terhadap keberhasilan diagnostik EUS FNA untuk menghitung nilai odds ratio (OR). Variabel dengan nilai p< 0,25 pada analisa bivariat dimasukkan ke analisa multivariat dengan regresi logistik.Hasil : Sebanyak 201 pasien dengan lesi pankreas yang menjalani pemeriksaan EUS FNA diikutkan dalam penelitian. Angka keberhasilan diagnostik EUS FNA pada lesi pankreas adalah sebesar 77,11%. Ukuran lesi ³3 cm diasoasikan dengan peningkatan keberhasilan diagnosis EUS FNA berdasarkan analisis bivariat (OR 2,46; IK95 1,25-4,86; p= 0,008). Analisis multivariat menunjukan bahwa ukuran lesi ³3 cm (OR 18,95; IK95 4,77-75,29; p = 0,000),  lokasi lesi di korpus (OR 2.82; IK95 1.03-7.77; p= 0,04) dan ukuran jarum 22G (OR 7.49; IK95 1.87-29.97; p= 0.004) diasoasikan dengan peningkatan keberhasilan diagnosis. Kesimpulan : Ukuran lesi, lokasi lesi dan ukuran jarum, merupakan faktor yang mempengaruhi keberhasilan diagnostik EUS FNA pada lesi pankreas.

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Background: Diagnostic accuracy of EUS FNA in diagnosing pancreatic lesion are affected by several factors. Clinical study regarding these factors had not been done in Indonesia. This study aims to study factors affecting the diagnostic yield of EUS FNA in diagnosing pancreatic lesion in Indonesian population. 

Method: This study is a cross-sectional study of medical record data in January 2012-July 2022 or a total of all subjects who underwent EUS FNA due to pancreatic lesions at PESC RSCM. Patient with incomplete data and peripacreatic lesion was excluded. Clinical characteristics of sample is presented in a table. Bivariat analysis was conducted with chi square test between independent factors and diagnostic success of EUS FNA to obtained the odds ratio (OR). Factors with p-value above 0,25 are included for multivariat analysis using logistic regression.  

Result: A total of 201 patients underwent EUS FNA was included in this study. Success rate of diagnosing pancreatic lesion using EUS FNA was 77,11%. Lesion size ³3 cm increased the odds for diagnostic success based on bivariat analysis (OR 2,46; 95% CI 1,25-4,86; p = 0,008). Multivariate analysis showed that the lesion size ³ 3 cm (OR 18.95; CI95 4.77-75.29; p = 0.000), the location of the lesion in the corpus (OR 2.82; CI95 1.03-7.77; p = 0.04) and needle size 22G (OR 7.49; CI95 1.87-29.97; p= 0.004) was associated with an increase in diagnostic yield.

Conclusion: The size of the lesion, the location of the lesion and the size of the needle, are factors that influence the diagnostic yield of EUS FNA in pancreatic lesions"

"Radiology fundamentals is a concise introduction to the dynamic field of radiology for medical students, non-radiology house staff, physician assistants, nurse practitioners, radiology assistants, and other allied health professionals. The goal of the book is to provide readers with general examples and brief discussions of basic radiographic principles and to serve as a curriculum guide, supplementing a radiology education and providing a solid foundation for further learning. Introductory chapters provide readers with the fundamental scientific concepts underlying the medical use of imaging modalities and technology, including ultrasound, computed tomography, magnetic resonance imaging, and nuclear medicine. The main scope of the book is to present concise chapters organized by anatomic region and radiology sub-specialty that highlight the radiologist’s role in diagnosing and treating common diseases, disorders, and conditions. Highly illustrated with images and diagrams, each chapter in Radiology Fundamentals begins with learning objectives to aid readers in recognizing important points and connecting the basic radiology concepts that run throughout the text. It is the editors’ hope that this valuable, up-to-date resource will foster and further stimulate self-directed radiology learning—the process at the heart of medical education."