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For:	O’Sullivan GJ, Carty FL, Cronin CG. Imaging of bone metastasis: An update. World J Radiol 2015; 7(8): 202-211 [PMID: 26339464 DOI: 10.4329/wjr.v7.i8.202] [Citation(s) in RCA: 199] [Impact Index Per Article: 19.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] Open

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Cited by Other Article(s)

Fu Y, Qin C, Li M, Zhang X, Gai Y, Ruan W, Lan X. Comparative Evaluation of 68Ga-FAPI-04 PET for Initial N and M Staging in Gastric Cancer: A Study Against Histopathology and Contrast-Enhanced CT. Clin Nucl Med 2025;50:394-403. [PMID: 40179292 DOI: 10.1097/rlu.0000000000005795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2024] [Accepted: 01/23/2025] [Indexed: 04/05/2025]

Abstract

PURPOSE

To evaluate the efficiency of 68Ga-FAPI-04 PET (PET/MRI or PET/CT) for N and M staging in gastric carcinoma and compare outcomes with histopathology and contrast-enhanced computed tomography (CECT).

PATIENTS AND METHODS

Patients with gastric carcinoma who had undergone 68Ga-FAPI-04 PET/MRI or PET/CT before treatment were retrospectively enrolled. Histopathology post lymphadenectomy was the gold standard for N staging, while histopathology and follow-up data were the reference for overall outcomes. The diagnostic efficiency of 68Ga-FAPI-04 PET for detecting regional lymph node involvement and distant metastases was compared to that of CECT.

RESULTS

Sixty-two patients were enrolled. In 18 patients who underwent 68Ga-FAPI-04 PET/MRI and lymphadenectomy, 532 lymph nodes were dissected. 68Ga-FAPI-04 PET/MRI showed similar sensitivity, specificity, and accuracy compared to CECT (28.3% vs. 23.2%, 99.8% vs. 99.3%, and 86.5% vs. 85.2%, all P > 0.05). Fifty-five patients had regional lymph node metastasis, 68Ga-FAPI-04 PET exhibited comparable diagnostic efficiency to CECT, with sensitivity of 83.6% versus 87.3%, specificity of 100% versus 85.7%, accuracy of 85.5% versus 87.1% (all P > 0.05). Excluding 3 patients with only abdominal CECT, 32 out of 59 patients had distant metastasis, with no significant differences in sensitivity, specificity, and accuracy between 68Ga-FAPI-04 PET and CECT based on patient (100% vs. 87.5%, 92.6% vs. 96.3%, and 96.6% vs. 91.5%, all P >0.05). Notably, 68Ga-FAPI-04 PET outperformed CECT in detecting peritoneal, distant lymph nodes, bone, liver, and ovarian metastases by visualizing more lesions or greater lesion extent.

CONCLUSIONS

68Ga-FAPI-04 PET exhibits comparable diagnostic performance to CECT for patient-based N staging and M staging of gastric cancer. However, it surpasses CECT in visualizing distant metastases.

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Kuhtić I, Mandić Paulić T, Kovačević L, Badovinac S, Jakopović M, Dobrenić M, Hrabak-Paar M. Clinical TNM Lung Cancer Staging: A Diagnostic Algorithm with a Pictorial Review. Diagnostics (Basel) 2025;15:908. [PMID: 40218258 PMCID: PMC11988785 DOI: 10.3390/diagnostics15070908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2025] [Revised: 03/13/2025] [Accepted: 03/29/2025] [Indexed: 04/14/2025] Open

Lam FC, Guru S, AbuReesh D, Hori YS, Chuang C, Liu L, Wang L, Gu X, Szalkowski GA, Wang Z, Wohlers C, Tayag A, Emrich SC, Ustrzynski L, Zygourakis CC, Desai A, Hayden Gephart M, Byun J, Pollom EL, Rahimy E, Soltys S, Park DJ, Chang SD. Use of Carbon Fiber Implants to Improve the Safety and Efficacy of Radiation Therapy for Spine Tumor Patients. Brain Sci 2025;15:199. [PMID: 40002531 PMCID: PMC11852773 DOI: 10.3390/brainsci15020199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2024] [Revised: 01/22/2025] [Accepted: 02/13/2025] [Indexed: 02/27/2025] Open

Affiliation(s)

Fred C. Lam Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (F.C.L.); (S.G.); (D.A.); (Y.S.H.); (A.T.); (S.C.E.); (L.U.); (A.D.); (M.H.G.); (D.J.P.)
Santosh Guru Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (F.C.L.); (S.G.); (D.A.); (Y.S.H.); (A.T.); (S.C.E.); (L.U.); (A.D.); (M.H.G.); (D.J.P.)
Deyaldeen AbuReesh Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (F.C.L.); (S.G.); (D.A.); (Y.S.H.); (A.T.); (S.C.E.); (L.U.); (A.D.); (M.H.G.); (D.J.P.)
Yusuke S. Hori Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (F.C.L.); (S.G.); (D.A.); (Y.S.H.); (A.T.); (S.C.E.); (L.U.); (A.D.); (M.H.G.); (D.J.P.)
Cynthia Chuang Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA; (C.C.); (L.L.); (L.W.); (X.G.); (G.A.S.); (Z.W.); (C.W.); (J.B.); (E.L.P.); (E.R.); (S.S.)
Lianli Liu Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA; (C.C.); (L.L.); (L.W.); (X.G.); (G.A.S.); (Z.W.); (C.W.); (J.B.); (E.L.P.); (E.R.); (S.S.)
Lei Wang Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA; (C.C.); (L.L.); (L.W.); (X.G.); (G.A.S.); (Z.W.); (C.W.); (J.B.); (E.L.P.); (E.R.); (S.S.)
Xuejun Gu Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA; (C.C.); (L.L.); (L.W.); (X.G.); (G.A.S.); (Z.W.); (C.W.); (J.B.); (E.L.P.); (E.R.); (S.S.)
Gregory A. Szalkowski Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA; (C.C.); (L.L.); (L.W.); (X.G.); (G.A.S.); (Z.W.); (C.W.); (J.B.); (E.L.P.); (E.R.); (S.S.)
Ziyi Wang Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA; (C.C.); (L.L.); (L.W.); (X.G.); (G.A.S.); (Z.W.); (C.W.); (J.B.); (E.L.P.); (E.R.); (S.S.)
Christopher Wohlers Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA; (C.C.); (L.L.); (L.W.); (X.G.); (G.A.S.); (Z.W.); (C.W.); (J.B.); (E.L.P.); (E.R.); (S.S.)
Armine Tayag Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (F.C.L.); (S.G.); (D.A.); (Y.S.H.); (A.T.); (S.C.E.); (L.U.); (A.D.); (M.H.G.); (D.J.P.)
Sara C. Emrich Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (F.C.L.); (S.G.); (D.A.); (Y.S.H.); (A.T.); (S.C.E.); (L.U.); (A.D.); (M.H.G.); (D.J.P.)
Louisa Ustrzynski Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (F.C.L.); (S.G.); (D.A.); (Y.S.H.); (A.T.); (S.C.E.); (L.U.); (A.D.); (M.H.G.); (D.J.P.)
Corinna C. Zygourakis Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (F.C.L.); (S.G.); (D.A.); (Y.S.H.); (A.T.); (S.C.E.); (L.U.); (A.D.); (M.H.G.); (D.J.P.)
Atman Desai Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (F.C.L.); (S.G.); (D.A.); (Y.S.H.); (A.T.); (S.C.E.); (L.U.); (A.D.); (M.H.G.); (D.J.P.)
Melanie Hayden Gephart Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (F.C.L.); (S.G.); (D.A.); (Y.S.H.); (A.T.); (S.C.E.); (L.U.); (A.D.); (M.H.G.); (D.J.P.)
John Byun Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA; (C.C.); (L.L.); (L.W.); (X.G.); (G.A.S.); (Z.W.); (C.W.); (J.B.); (E.L.P.); (E.R.); (S.S.)
Erqi Liu Pollom Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA; (C.C.); (L.L.); (L.W.); (X.G.); (G.A.S.); (Z.W.); (C.W.); (J.B.); (E.L.P.); (E.R.); (S.S.)
Elham Rahimy Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA; (C.C.); (L.L.); (L.W.); (X.G.); (G.A.S.); (Z.W.); (C.W.); (J.B.); (E.L.P.); (E.R.); (S.S.)
Scott Soltys Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA; (C.C.); (L.L.); (L.W.); (X.G.); (G.A.S.); (Z.W.); (C.W.); (J.B.); (E.L.P.); (E.R.); (S.S.)
David J. Park Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (F.C.L.); (S.G.); (D.A.); (Y.S.H.); (A.T.); (S.C.E.); (L.U.); (A.D.); (M.H.G.); (D.J.P.)
Steven D. Chang Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (F.C.L.); (S.G.); (D.A.); (Y.S.H.); (A.T.); (S.C.E.); (L.U.); (A.D.); (M.H.G.); (D.J.P.)

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Noebauer-Huhmann IM, Vanhoenacker FM, Vilanova JC, Tagliafico AS, Weber MA, Lalam RK, Grieser T, Nikodinovska VV, de Rooy JWJ, Papakonstantinou O, Mccarthy C, Sconfienza LM, Verstraete K, Martel-Villagrán J, Szomolanyi P, Lecouvet FE, Afonso D, Albtoush OM, Aringhieri G, Arkun R, Aström G, Bazzocchi A, Botchu R, Breitenseher M, Chaudhary S, Dalili D, Davies M, de Jonge MC, Mete BD, Fritz J, Gielen JLMA, Hide G, Isaac A, Ivanoski S, Mansour RM, Muntaner-Gimbernat L, Navas A, O Donnell P, Örgüç Ş, Rennie WJ, Resano S, Robinson P, Sanal HT, Ter Horst SAJ, van Langevelde K, Wörtler K, Koelz M, Panotopoulos J, Windhager R, Bloem JL. Soft tissue tumor imaging in adults: whole-body staging in sarcoma, non-malignant entities requiring special algorithms, pitfalls and special imaging aspects. Guidelines 2024 from the European Society of Musculoskeletal Radiology (ESSR). Eur Radiol 2025;35:351-359. [PMID: 39030374 PMCID: PMC11631817 DOI: 10.1007/s00330-024-10897-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 03/30/2024] [Accepted: 04/30/2024] [Indexed: 07/21/2024]

Abstract

OBJECTIVES

The revised European Society of Musculoskeletal Radiology (ESSR) consensus guidelines on soft tissue tumor imaging represent an update of 2015 after technical advancements, further insights into specific entities, and revised World Health Organization (2020) and AJCC (2017) classifications. This second of three papers covers algorithms once histology is confirmed: (1) standardized whole-body staging, (2) special algorithms for non-malignant entities, and (3) multiplicity, genetic tumor syndromes, and pitfalls.

MATERIALS AND METHODS

A validated Delphi method based on peer-reviewed literature was used to derive consensus among a panel of 46 specialized musculoskeletal radiologists from 12 European countries. Statements that had undergone interdisciplinary revision were scored online by the level of agreement (0 to 10) during two iterative rounds, that could result in 'group consensus', 'group agreement', or 'lack of agreement'.

RESULTS

The three sections contain 24 statements with comments. Group consensus was reached in 95.8% and group agreement in 4.2%. For whole-body staging, pulmonary MDCT should be performed in all high-grade sarcomas. Whole-body MRI is preferred for staging bone metastasis, with [18F]FDG-PET/CT as an alternative modality in PET-avid tumors. Patients with alveolar soft part sarcoma, clear cell sarcoma, and angiosarcoma should be screened for brain metastases. Special algorithms are recommended for entities such as rhabdomyosarcoma, extraskeletal Ewing sarcoma, myxoid liposarcoma, and neurofibromatosis type 1 associated malignant peripheral nerve sheath tumors. Satisfaction of search should be avoided in potential multiplicity.

CONCLUSION

Standardized whole-body staging includes pulmonary MDCT in all high-grade sarcomas; entity-dependent modifications and specific algorithms are recommended for sarcomas and non-malignant soft tissue tumors.

CLINICAL RELEVANCE STATEMENT

These updated ESSR soft tissue tumor imaging guidelines aim to provide support in decision-making, helping to avoid common pitfalls, by providing general and entity-specific algorithms, techniques, and reporting recommendations for whole-body staging in sarcoma and non-malignant soft tissue tumors.

KEY POINTS

An early, accurate, diagnosis is crucial for the prognosis of patients with soft tissue tumors. These updated guidelines provide best practice expert consensus for standardized imaging algorithms, techniques, and reporting. Standardization can improve the comparability examinations and provide databases for large data analysis.

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Affiliation(s)

Iris-Melanie Noebauer-Huhmann Department of Biomedical Imaging and Image Guided Therapy, Division of Neuroradiology and Musculoskeletal Radiology, Medical University of Vienna, Vienna, Austria.
Filip M Vanhoenacker Department of Radiology, AZ Sint Maarten Mechelen University (Hospital) Antwerp, Antwerp, Belgium Faculty of Medicine and Health Sciences, University of Ghent, Ghent, Belgium
Joan C Vilanova Department of Radiology, Clínica Girona, Institute of Diagnostic Imaging (IDI) Girona, University of Girona, Girona, Spain
Alberto S Tagliafico Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy Department of Radiology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
Marc-André Weber Institute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, University Medical Center Rostock, Rostock, Germany
Radhesh K Lalam Department of Radiology, Robert Jones and Agnes Hunt Orthopaedic Hospital, Oswestry, UK
Thomas Grieser Department for Diagnostic and Interventional Radiology, University Hospital Augsburg, Augsburg, Germany
Violeta Vasilevska Nikodinovska Medical Faculty, Ss. Cyril and Methodius University, Skopje, Macedonia Department of Radiology, University Surgical Clinic "St. Naum Ohridski", Skopje, Macedonia
Jacky W J de Rooy Department of Imaging, Radiology, Radboud University Medical Center, Nijmegen, The Netherlands
Olympia Papakonstantinou 2nd Department of Radiology, Attikon Hospital, National and Kapodistrian University of Athens, Athens, Greece
Catherine Mccarthy Oxford Musculoskeletal Radiology and Oxford University Hospitals, Oxford, UK
Luca Maria Sconfienza IRCCS Istituto Ortopedico Galeazzi, Milan, Italy Dipartimento Di Scienze Biomediche Per La Salute, Università Degli Studi Di Milano, Milan, Italy
Koenraad Verstraete Department of Radiology, Ghent University Hospital, Ghent, Belgium
José Martel-Villagrán Radiology Department, Hospital Universitario Fundación Alcorcón, Madrid, Spain
Pavol Szomolanyi High Field MR Center, Department of Biomedical Imaging and Image‑Guided Therapy, Medical University Vienna, Vienna, Austria Department of Imaging Methods, Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
Frédéric E Lecouvet Department of Radiology and Medical Imaging, Cliniques Universitaires Saint Luc, Institut de Recherche Expérimentale et Clinique (IREC), Institut du Cancer Roi Albert II (IRA2), Université Catholique de Louvain (UCLouvain), Brussels, Belgium
Diana Afonso Hospital Particular da Madeira and Hospital da Luz Lisboa, Lisbon, Portugal
Omar M Albtoush Department of Radiology, University of Jordan, Ammam, Jordan
Giacomo Aringhieri Academic Radiology, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
Remide Arkun Ege University Medical School (Emeritus), Izmir, Türkiye Star Imaging Center, Izmir, Türkiye
Gunnar Aström Department of Immunology, Genetics and Pathology (Oncology) and Department of Surgical Sciences (Radiology), Uppsala University, Uppsala, Sweden
Alberto Bazzocchi Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
Rajesh Botchu Department of Musculoskeletal Radiology, Royal Orthopedic Hospital, Birmingham, UK
Martin Breitenseher Sigmund Freud Privatuniversität, Vienna, Austria
Snehansh Chaudhary Oxford University Hospitals NHS Foundation Trust, Oxford, UK
Danoob Dalili Academic Surgical Unit, South West London Elective Orthopaedic Centre (SWLEOC), London, UK
Mark Davies Department of Musculoskeletal Radiology, Royal Orthopedic Hospital, Birmingham, UK
Milko C de Jonge Department of Radiology, St. Antonius Hospital, Utrecht, The Netherlands
Berna D Mete Department of Radiology School of Medicine, Izmir Demokrasi University, Izmir, Türkiye
Jan Fritz Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, University Hospital Tuebingen, Tübingen, Germany
Jan L M A Gielen Department of Radiology, Jessa Ziekenhuis, Campus Virga Jesse, Hasselt, Belgium
Geoff Hide Department of Radiology, Freeman Hospital, Newcastle Upon Tyne, UK
Amanda Isaac School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
Slavcho Ivanoski St. Erasmo Hospital for Orthopaedic Surgery and Traumatology Ohrid, Ohrid, Macedonia
Ramy M Mansour Oxford University Hospitals, Oxford, UK
Lorenzo Muntaner-Gimbernat Hospital Univeritario Son Espases Balearic Islands University, Palma, Spain
Ana Navas Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
Paul O Donnell Royal National Orthopaedic Hospital, Stanmore, UK
Şebnem Örgüç Manisa Celal Bayar University, Manisa, Türkiye
Winston J Rennie Clinical MSK Radiology, Loughborough University, Leicester Royal Infirmary, Leicester, UK
Santiago Resano Hospital Universitario Ramón y Cajal, Madrid, Spain
Philip Robinson Musculoskeletal Radiology Department Chapel Allerton Hospital, Leeds Teaching Hospitals NHS Trust, Leeds, UK NIHR Leeds Biomedical Research Centre, Leeds, UK
Hatice T Sanal Radiology Department, University of Health Sciences, Gülhane Training and Research Hospital, Ankara, Türkiye
Simone A J Ter Horst Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands Department of Radiology and Nuclear Medicine, University Medical Centre Utrecht, Utrecht, The Netherlands
Kirsten van Langevelde Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
Klaus Wörtler Musculoskeletal Radiology Section, Klinikum Rechts der Isar, Technical University of Munich ‑ TUM School of Medicine, Munich, Germany
Marita Koelz Clinical Institute of Pathology, Medical University of Vienna, Vienna, Austria
Joannis Panotopoulos Departement of Orthopaedics and Traumatology, Division of Orthopaedics, Medical University of Vienna, Vienna, Austria
Reinhard Windhager Departement of Orthopaedics and Traumatology, Medical University of Vienna, Vienna, Austria
Johan L Bloem Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands

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Ulusoy OL, Server S, Yesilova M, İnan N. Whole-body PET/MRI to detect bone metastases: comparison of the diagnostic performance of the sequences. Radiol Oncol 2024;58:494-500. [PMID: 39608007 PMCID: PMC11604270 DOI: 10.2478/raon-2024-0062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2024] [Accepted: 10/24/2024] [Indexed: 11/30/2024] Open

Guruvayurappan GK, Frankenbach-Désor T, Laubach M, Klein A, von Bergwelt-Baildon M, Cusan M, Aszodi A, Holzapfel BM, Böcker W, Mayer-Wagner S. Clinical challenges in prostate cancer management: Metastatic bone-tropism and the role of circulating tumor cells. Cancer Lett 2024;606:217310. [PMID: 39486571 DOI: 10.1016/j.canlet.2024.217310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2024] [Revised: 10/18/2024] [Accepted: 10/29/2024] [Indexed: 11/04/2024]

Dong X, Chen G, Zhu Y, Ma B, Ban X, Wu N, Ming Y. Artificial intelligence in skeletal metastasis imaging. Comput Struct Biotechnol J 2024;23:157-164. [PMID: 38144945 PMCID: PMC10749216 DOI: 10.1016/j.csbj.2023.11.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 11/02/2023] [Accepted: 11/02/2023] [Indexed: 12/26/2023] Open

Affiliation(s)

Xiying Dong Department of Orthopedic Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China Key Laboratory of Big Data for Spinal Deformities, Chinese Academy of Medical Sciences, Beijing 100730, China Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021 Beijing, China
Guilin Chen Department of Orthopedic Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China Key Laboratory of Big Data for Spinal Deformities, Chinese Academy of Medical Sciences, Beijing 100730, China Graduate School of Peking Union Medical College, Beijing 100730, China
Yuanpeng Zhu Department of Orthopedic Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China Key Laboratory of Big Data for Spinal Deformities, Chinese Academy of Medical Sciences, Beijing 100730, China Graduate School of Peking Union Medical College, Beijing 100730, China
Boyuan Ma School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China
Xiaojuan Ban School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China
Nan Wu Department of Orthopedic Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China Key Laboratory of Big Data for Spinal Deformities, Chinese Academy of Medical Sciences, Beijing 100730, China Beijing Key Laboratory for Genetic Research of Skeletal Deformity, Beijing 100730, China
Yue Ming Department of Nuclear Medicine (PET-CT Center), National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China

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Csikos C, Barna S, Kovács Á, Czina P, Budai Á, Szoliková M, Nagy IG, Husztik B, Kiszler G, Garai I. AI-Based Noise-Reduction Filter for Whole-Body Planar Bone Scintigraphy Reliably Improves Low-Count Images. Diagnostics (Basel) 2024;14:2686. [PMID: 39682594 DOI: 10.3390/diagnostics14232686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2024] [Revised: 11/25/2024] [Accepted: 11/27/2024] [Indexed: 12/18/2024] Open

Abstract

Background/Objectives: Artificial intelligence (AI) is a promising tool for the enhancement of physician workflow and serves to further improve the efficiency of their diagnostic evaluations. This study aimed to assess the performance of an AI-based bone scan noise-reduction filter on noisy, low-count images in a routine clinical environment. Methods: The performance of the AI bone-scan filter (BS-AI filter) in question was retrospectively evaluated on 47 different patients' 99mTc-MDP bone scintigraphy image pairs (anterior- and posterior-view images), which were obtained in such a manner as to represent the diverse characteristics of the general patient population. The BS-AI filter was tested on artificially degraded noisy images-75, 50, and 25% of total counts-which were generated by binominal sampling. The AI-filtered and unfiltered images were concurrently appraised for image quality and contrast by three nuclear medicine physicians. It was also determined whether there was any difference between the lesions seen on the unfiltered and filtered images. For quantitative analysis, an automatic lesion detector (BS-AI annotator) was utilized as a segmentation algorithm. The total number of lesions and their locations as detected by the BS-AI annotator in the BS-AI-filtered low-count images was compared to the total-count filtered images. The total number of pixels labeled as lesions in the filtered low-count images in relation to the number of pixels in the total-count filtered images was also compared to ensure the filtering process did not change lesion sizes significantly. The comparison of pixel numbers was performed using the reduced-count filtered images that contained only those lesions that were detected in the total-count images. Results: Based on visual assessment, observers agreed that image contrast and quality were better in the BS-AI-filtered images, increasing their diagnostic confidence. Similarities in lesion numbers and sites detected by the BS-AI annotator compared to filtered total-count images were 89%, 83%, and 75% for images degraded to counts of 75%, 50%, and 25%, respectively. No significant difference was found in the number of annotated pixels between filtered images with different counts (p > 0.05). Conclusions: Our findings indicate that the BS-AI noise-reduction filter enhances image quality and contrast without loss of vital information. The implementation of this filter in routine diagnostic procedures reliably improves diagnostic confidence in low-count images and elicits a reduction in the administered dose or acquisition time by a minimum of 50% relative to the original dose or acquisition time.

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Chang Y, Gu Y, Ruan S, Xu S, Sun J, Jiang Z, Yao G, Wang Z, Zhao H. [¹⁸F]FDG PET/CT performs better than CT in determining the bone biopsy site : randomized controlled clinical trial. Cancer Imaging 2024;24:160. [PMID: 39582078 PMCID: PMC11587546 DOI: 10.1186/s40644-024-00804-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2024] [Accepted: 11/11/2024] [Indexed: 11/26/2024] Open

Costa F, Restelli F, Innocenti N, Zileli M, Vaishya S, Zygourakis C, Pojskic M, Yaman O, Sharif S. Incidence, epidemiology, radiology, and classification of metastatic spine tumors: WFNS Spine Committee recommendations. Neurosurg Rev 2024;47:853. [PMID: 39549161 DOI: 10.1007/s10143-024-03095-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2024] [Revised: 08/13/2024] [Accepted: 11/11/2024] [Indexed: 11/18/2024]

Magdy O, Elaziz MA, Dahou A, Ewees AA, Elgarayhi A, Sallah M. Bone scintigraphy based on deep learning model and modified growth optimizer. Sci Rep 2024;14:25627. [PMID: 39465262 PMCID: PMC11514163 DOI: 10.1038/s41598-024-73991-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Accepted: 09/23/2024] [Indexed: 10/29/2024] Open

Chua WM, Tang CYL, Loke KSH, Lam WWC, Yang SP, Lee MS, Hou W, Lim MYS, Lim KC, Chen RC. Differentiated Thyroid Cancer after Thyroidectomy. Radiographics 2024;44:e240021. [PMID: 39235963 DOI: 10.1148/rg.240021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/07/2024]

Affiliation(s)

Wei Ming Chua From the Department of Nuclear Medicine and Molecular Imaging, Division of Radiological Sciences, Singapore General Hospital, Outram Rd, Singapore 169608 (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L.); Department of Neuroradiology, Singapore General Hospital, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Radiological Sciences Academic Clinical Program, SingHealth Duke-NUS Academic Medical Centre, Singapore (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); National Neuroscience Institute, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Department of Medicine, Division of Endocrinology, National University Hospital, Singapore (S.P.Y.); and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (S.P.Y.)
Charlene Yu Lin Tang From the Department of Nuclear Medicine and Molecular Imaging, Division of Radiological Sciences, Singapore General Hospital, Outram Rd, Singapore 169608 (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L.); Department of Neuroradiology, Singapore General Hospital, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Radiological Sciences Academic Clinical Program, SingHealth Duke-NUS Academic Medical Centre, Singapore (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); National Neuroscience Institute, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Department of Medicine, Division of Endocrinology, National University Hospital, Singapore (S.P.Y.); and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (S.P.Y.)
Kelvin S H Loke From the Department of Nuclear Medicine and Molecular Imaging, Division of Radiological Sciences, Singapore General Hospital, Outram Rd, Singapore 169608 (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L.); Department of Neuroradiology, Singapore General Hospital, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Radiological Sciences Academic Clinical Program, SingHealth Duke-NUS Academic Medical Centre, Singapore (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); National Neuroscience Institute, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Department of Medicine, Division of Endocrinology, National University Hospital, Singapore (S.P.Y.); and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (S.P.Y.)
Winnie Wing-Chuen Lam From the Department of Nuclear Medicine and Molecular Imaging, Division of Radiological Sciences, Singapore General Hospital, Outram Rd, Singapore 169608 (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L.); Department of Neuroradiology, Singapore General Hospital, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Radiological Sciences Academic Clinical Program, SingHealth Duke-NUS Academic Medical Centre, Singapore (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); National Neuroscience Institute, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Department of Medicine, Division of Endocrinology, National University Hospital, Singapore (S.P.Y.); and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (S.P.Y.)
Samantha Peiling Yang From the Department of Nuclear Medicine and Molecular Imaging, Division of Radiological Sciences, Singapore General Hospital, Outram Rd, Singapore 169608 (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L.); Department of Neuroradiology, Singapore General Hospital, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Radiological Sciences Academic Clinical Program, SingHealth Duke-NUS Academic Medical Centre, Singapore (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); National Neuroscience Institute, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Department of Medicine, Division of Endocrinology, National University Hospital, Singapore (S.P.Y.); and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (S.P.Y.)
Melissa Shuhui Lee From the Department of Nuclear Medicine and Molecular Imaging, Division of Radiological Sciences, Singapore General Hospital, Outram Rd, Singapore 169608 (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L.); Department of Neuroradiology, Singapore General Hospital, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Radiological Sciences Academic Clinical Program, SingHealth Duke-NUS Academic Medical Centre, Singapore (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); National Neuroscience Institute, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Department of Medicine, Division of Endocrinology, National University Hospital, Singapore (S.P.Y.); and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (S.P.Y.)
Wenlu Hou From the Department of Nuclear Medicine and Molecular Imaging, Division of Radiological Sciences, Singapore General Hospital, Outram Rd, Singapore 169608 (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L.); Department of Neuroradiology, Singapore General Hospital, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Radiological Sciences Academic Clinical Program, SingHealth Duke-NUS Academic Medical Centre, Singapore (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); National Neuroscience Institute, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Department of Medicine, Division of Endocrinology, National University Hospital, Singapore (S.P.Y.); and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (S.P.Y.)
May Yi Shan Lim From the Department of Nuclear Medicine and Molecular Imaging, Division of Radiological Sciences, Singapore General Hospital, Outram Rd, Singapore 169608 (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L.); Department of Neuroradiology, Singapore General Hospital, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Radiological Sciences Academic Clinical Program, SingHealth Duke-NUS Academic Medical Centre, Singapore (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); National Neuroscience Institute, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Department of Medicine, Division of Endocrinology, National University Hospital, Singapore (S.P.Y.); and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (S.P.Y.)
Kheng Choon Lim From the Department of Nuclear Medicine and Molecular Imaging, Division of Radiological Sciences, Singapore General Hospital, Outram Rd, Singapore 169608 (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L.); Department of Neuroradiology, Singapore General Hospital, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Radiological Sciences Academic Clinical Program, SingHealth Duke-NUS Academic Medical Centre, Singapore (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); National Neuroscience Institute, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Department of Medicine, Division of Endocrinology, National University Hospital, Singapore (S.P.Y.); and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (S.P.Y.)
Robert Chun Chen From the Department of Nuclear Medicine and Molecular Imaging, Division of Radiological Sciences, Singapore General Hospital, Outram Rd, Singapore 169608 (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L.); Department of Neuroradiology, Singapore General Hospital, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Radiological Sciences Academic Clinical Program, SingHealth Duke-NUS Academic Medical Centre, Singapore (W.M.C., C.Y.L.T., K.S.H.L., W.W.C.L., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); National Neuroscience Institute, Singapore (W.M.C., M.S.L., W.H., M.Y.S.L., K.C.L., R.C.C.); Department of Medicine, Division of Endocrinology, National University Hospital, Singapore (S.P.Y.); and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (S.P.Y.)

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Sabeghi P, Kinkar KK, Castaneda GDR, Eibschutz LS, Fields BKK, Varghese BA, Patel DB, Gholamrezanezhad A. Artificial intelligence and machine learning applications for the imaging of bone and soft tissue tumors. FRONTIERS IN RADIOLOGY 2024;4:1332535. [PMID: 39301168 PMCID: PMC11410694 DOI: 10.3389/fradi.2024.1332535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 08/01/2024] [Indexed: 09/22/2024]

Vijayakumar G, Jones CM, Supple S, Blank AT, Meyer JR. Novel MRI scoring system to assess osseous malignancy in soft tissue sarcoma patients following radiotherapy. Eur J Radiol 2024;178:111634. [PMID: 39084030 DOI: 10.1016/j.ejrad.2024.111634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 06/29/2024] [Accepted: 07/15/2024] [Indexed: 08/02/2024]

Kasat PR, Kashikar SV, Parihar P, Sachani P, Shrivastava P, Mapari SA, Pradeep U, Bedi GN, Bhangale PN. Advances in Imaging for Metastatic Epidural Spinal Cord Compression: A Comprehensive Review of Detection, Diagnosis, and Treatment Planning. Cureus 2024;16:e70110. [PMID: 39449880 PMCID: PMC11501474 DOI: 10.7759/cureus.70110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2024] [Accepted: 09/24/2024] [Indexed: 10/26/2024] Open

Lee JO, Kim DH, Chae HD, Lee E, Kang JH, Lee JH, Kim HJ, Seo J, Chai JW. Assessing visibility and bone changes of spinal metastases in CT scans: a comprehensive analysis across diverse cancer types. Skeletal Radiol 2024;53:1553-1561. [PMID: 38407627 DOI: 10.1007/s00256-024-04623-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 02/09/2024] [Accepted: 02/12/2024] [Indexed: 02/27/2024]

Cattabriga A, Renzetti B, Galuppi F, Bartalena L, Gaudiano C, Brocchi S, Rossi A, Schiavina R, Bianchi L, Brunocilla E, Spinozzi L, Catanzaro C, Castellucci P, Farolfi A, Fanti S, Tunariu N, Mosconi C. Multiparametric Whole-Body MRI: A Game Changer in Metastatic Prostate Cancer. Cancers (Basel) 2024;16:2531. [PMID: 39061171 PMCID: PMC11274871 DOI: 10.3390/cancers16142531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Revised: 06/24/2024] [Accepted: 07/07/2024] [Indexed: 07/28/2024] Open

Affiliation(s)

Arrigo Cattabriga Department of Radiology, IRCCS Azienda Ospedaliero Universitaria di Bologna, 40138 Bologna, Italy; (B.R.); (F.G.); (L.B.); (C.G.); (S.B.); (C.M.) Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40136 Bologna, Italy; (R.S.); (L.B.); (E.B.); (L.S.); (C.C.); (S.F.)
Benedetta Renzetti Department of Radiology, IRCCS Azienda Ospedaliero Universitaria di Bologna, 40138 Bologna, Italy; (B.R.); (F.G.); (L.B.); (C.G.); (S.B.); (C.M.) Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40136 Bologna, Italy; (R.S.); (L.B.); (E.B.); (L.S.); (C.C.); (S.F.)
Francesco Galuppi Department of Radiology, IRCCS Azienda Ospedaliero Universitaria di Bologna, 40138 Bologna, Italy; (B.R.); (F.G.); (L.B.); (C.G.); (S.B.); (C.M.) Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40136 Bologna, Italy; (R.S.); (L.B.); (E.B.); (L.S.); (C.C.); (S.F.)
Laura Bartalena Department of Radiology, IRCCS Azienda Ospedaliero Universitaria di Bologna, 40138 Bologna, Italy; (B.R.); (F.G.); (L.B.); (C.G.); (S.B.); (C.M.)
Caterina Gaudiano Department of Radiology, IRCCS Azienda Ospedaliero Universitaria di Bologna, 40138 Bologna, Italy; (B.R.); (F.G.); (L.B.); (C.G.); (S.B.); (C.M.)
Stefano Brocchi Department of Radiology, IRCCS Azienda Ospedaliero Universitaria di Bologna, 40138 Bologna, Italy; (B.R.); (F.G.); (L.B.); (C.G.); (S.B.); (C.M.)
Alice Rossi Radiology Unit, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, 47014 Meldola, Italy;
Riccardo Schiavina Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40136 Bologna, Italy; (R.S.); (L.B.); (E.B.); (L.S.); (C.C.); (S.F.) Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, 40138 Bologna, Italy
Lorenzo Bianchi Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40136 Bologna, Italy; (R.S.); (L.B.); (E.B.); (L.S.); (C.C.); (S.F.) Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, 40138 Bologna, Italy
Eugenio Brunocilla Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40136 Bologna, Italy; (R.S.); (L.B.); (E.B.); (L.S.); (C.C.); (S.F.) Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, 40138 Bologna, Italy
Luca Spinozzi Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40136 Bologna, Italy; (R.S.); (L.B.); (E.B.); (L.S.); (C.C.); (S.F.) Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, 40138 Bologna, Italy
Calogero Catanzaro Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40136 Bologna, Italy; (R.S.); (L.B.); (E.B.); (L.S.); (C.C.); (S.F.) Division of Urology, IRCCS Azienda Ospedaliero Universitaria di Bologna, 40138 Bologna, Italy
Paolo Castellucci Nuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy; (P.C.); (A.F.)
Andrea Farolfi Nuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy; (P.C.); (A.F.)
Stefano Fanti Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40136 Bologna, Italy; (R.S.); (L.B.); (E.B.); (L.S.); (C.C.); (S.F.) Nuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy; (P.C.); (A.F.)
Nina Tunariu Clinical Radiology, Royal Marsden Hospital & Institute of Cancer Research, London SW3 6JJ, UK;
Cristina Mosconi Department of Radiology, IRCCS Azienda Ospedaliero Universitaria di Bologna, 40138 Bologna, Italy; (B.R.); (F.G.); (L.B.); (C.G.); (S.B.); (C.M.) Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40136 Bologna, Italy; (R.S.); (L.B.); (E.B.); (L.S.); (C.C.); (S.F.)

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Putro YAP, Aryandono T, Widodo I, Magetsari R, Pramono D, Johan MP, Abidin MA, Wikantyasa A, Huwaidi AF, Saraswati PA. Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study. F1000Res 2024;13:333. [PMID: 39583211 PMCID: PMC11584451 DOI: 10.12688/f1000research.146118.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/13/2024] [Indexed: 11/26/2024] Open

Affiliation(s)

Yuni Artha Prabowo Putro Doctoral Program in Medicine and Health Sciences, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, D.I. Yogyakarta, 55281, Indonesia Orthopedics and Traumatology, RSUP Dr. Sardjito Hospital, Jl. Kesehatan Sendowo, , Sleman, D.I. Yogyakarta, 55281, Indonesia
Teguh Aryandono Doctoral Program in Medicine and Health Sciences, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, D.I. Yogyakarta, 55281, Indonesia
Irianiwati Widodo Doctoral Program in Medicine and Health Sciences, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, D.I. Yogyakarta, 55281, Indonesia
Rahadyan Magetsari Doctoral Program in Medicine and Health Sciences, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, D.I. Yogyakarta, 55281, Indonesia Orthopedics and Traumatology, RSUP Dr. Sardjito Hospital, Jl. Kesehatan Sendowo, , Sleman, D.I. Yogyakarta, 55281, Indonesia
Dibyo Pramono Doctoral Program in Medicine and Health Sciences, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, D.I. Yogyakarta, 55281, Indonesia Faculty of Dentistry, Universitas Gadjah Mada, Yogyakarta, D.I. Yogyakarta, 55281, Indonesia
Muhammad Phetrus Johan Orthopaedic and Traumatology, RSUP Dr. Wahidin Sudirohusodo, Sulawesi Selatan, 90245, Indonesia Faculty of Medicine, Universitas Hasanuddin, Makassar, Sulawesi Selatan, 90245, Indonesia
Moh Asri Abidin Faculty of Medicine and Health Sciences, Universitas Muhammadiyah Makassar, Makassar, Sulawesi Selatan, 90221, Indonesia
Ardanariswara Wikantyasa Orthopedics and Traumatology, RSUP Dr. Sardjito Hospital, Jl. Kesehatan Sendowo, , Sleman, D.I. Yogyakarta, 55281, Indonesia
A Faiz Huwaidi Orthopedics and Traumatology, RSUP Dr. Sardjito Hospital, Jl. Kesehatan Sendowo, , Sleman, D.I. Yogyakarta, 55281, Indonesia
Paramita Ayu Saraswati Orthopedics and Traumatology, RSUP Dr. Sardjito Hospital, Jl. Kesehatan Sendowo, , Sleman, D.I. Yogyakarta, 55281, Indonesia

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Hesami M, Blake M, Anderson MA, Asmundo L, Kilcoyne A, Najmi Z, Caravan PD, Catana C, Czawlytko C, Esfahani SA, Kambadakone AR, Samir A, McDermott S, Domachevsky L, Ursprung S, Catalano OA. Diagnostic Anatomic Imaging for Neuroendocrine Neoplasms: Maximizing Strengths and Mitigating Weaknesses. J Comput Assist Tomogr 2024;48:521-532. [PMID: 38657156 PMCID: PMC11245376 DOI: 10.1097/rct.0000000000001615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]

Brown LJ, Ahn J, Gao B, Gee H, Nagrial A, Hau E, da Silva IP. Site-Specific Response and Resistance Patterns in Patients with Advanced Non-Small-Cell Lung Cancer Treated with First-Line Systemic Therapy. Cancers (Basel) 2024;16:2136. [PMID: 38893255 PMCID: PMC11172392 DOI: 10.3390/cancers16112136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 05/26/2024] [Accepted: 05/27/2024] [Indexed: 06/21/2024] Open

Affiliation(s)

Lauren Julia Brown Department of Medical Oncology, Westmead Hospital, Sydney, NSW 2145, Australia (A.N.); (I.P.d.S.) Blacktown Cancer and Haematology Centre, Blacktown Hospital, Sydney, NSW 2148, Australia Faculty of Medicine and Health, University of Sydney, Camperdown, NSW 2050, Australia Westmead Institute for Medical Research, Westmead, NSW 2145, Australia
Julie Ahn Blacktown Cancer and Haematology Centre, Blacktown Hospital, Sydney, NSW 2148, Australia Sydney West Radiation Oncology Network (SWRON), Sydney, NSW 2145, Australia
Bo Gao Department of Medical Oncology, Westmead Hospital, Sydney, NSW 2145, Australia (A.N.); (I.P.d.S.) Blacktown Cancer and Haematology Centre, Blacktown Hospital, Sydney, NSW 2148, Australia Faculty of Medicine and Health, University of Sydney, Camperdown, NSW 2050, Australia
Harriet Gee Faculty of Medicine and Health, University of Sydney, Camperdown, NSW 2050, Australia Westmead Institute for Medical Research, Westmead, NSW 2145, Australia Sydney West Radiation Oncology Network (SWRON), Sydney, NSW 2145, Australia Children’s Medical Research Institute, Westmead, NSW 2145, Australia
Adnan Nagrial Department of Medical Oncology, Westmead Hospital, Sydney, NSW 2145, Australia (A.N.); (I.P.d.S.) Blacktown Cancer and Haematology Centre, Blacktown Hospital, Sydney, NSW 2148, Australia Faculty of Medicine and Health, University of Sydney, Camperdown, NSW 2050, Australia
Eric Hau Blacktown Cancer and Haematology Centre, Blacktown Hospital, Sydney, NSW 2148, Australia Faculty of Medicine and Health, University of Sydney, Camperdown, NSW 2050, Australia Westmead Institute for Medical Research, Westmead, NSW 2145, Australia Sydney West Radiation Oncology Network (SWRON), Sydney, NSW 2145, Australia
Inês Pires da Silva Department of Medical Oncology, Westmead Hospital, Sydney, NSW 2145, Australia (A.N.); (I.P.d.S.) Blacktown Cancer and Haematology Centre, Blacktown Hospital, Sydney, NSW 2148, Australia Faculty of Medicine and Health, University of Sydney, Camperdown, NSW 2050, Australia Melanoma Institute Australia, Wollstonecraft, NSW 2065, Australia

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Vettori E, Borella A, Costantinides F, Rizzo R, Maglione M. Mandibular metastasis of pulmonary adenocarcinoma: How unexpected could it be? Gerodontology 2024;41:283-288. [PMID: 37496280 DOI: 10.1111/ger.12707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/16/2023] [Indexed: 07/28/2023]

Expósito D, Martel J, Alvarez de Sierra B, Bueno A, Vilanova C, Vilanova JC. Neoplastic and Non-neoplastic Bone Lesions of the Knee. Semin Musculoskelet Radiol 2024;28:225-247. [PMID: 38768589 DOI: 10.1055/s-0044-1781471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]

Yoon SM, Bazan JG. Navigating Breast Cancer Oligometastasis and Oligoprogression: Current Landscape and Future Directions. Curr Oncol Rep 2024;26:647-664. [PMID: 38652425 PMCID: PMC11168988 DOI: 10.1007/s11912-024-01529-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/25/2024] [Indexed: 04/25/2024]

Arakil N, Akhund SA, Elaasser B, Mohammad KS. Intersecting Paths: Unraveling the Complex Journey of Cancer to Bone Metastasis. Biomedicines 2024;12:1075. [PMID: 38791037 PMCID: PMC11117796 DOI: 10.3390/biomedicines12051075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Revised: 04/27/2024] [Accepted: 05/10/2024] [Indexed: 05/26/2024] Open

Abstract

The phenomenon of bone metastases presents a significant challenge within the context of advanced cancer treatments, particularly pertaining to breast, prostate, and lung cancers. These metastatic occurrences stem from the dissemination of cancerous cells into the bone, thereby interrupting the equilibrium between osteoblasts and osteoclasts. Such disruption results in skeletal complications, adversely affecting patient morbidity and quality of life. This review discusses the intricate interplay between cancer cells and the bone microenvironment, positing the bone not merely as a passive recipient of metastatic cells but as an active contributor to cancer progression through its distinctive biochemical and cellular makeup. A thorough examination of bone structure and the dynamics of bone remodeling is undertaken, elucidating how metastatic cancer cells exploit these processes. This review explores the genetic and molecular pathways that underpin the onset and development of bone metastases. Particular emphasis is placed on the roles of cytokines and growth factors in facilitating osteoclastogenesis and influencing osteoblast activity. Additionally, this paper offers a meticulous critique of current diagnostic methodologies, ranging from conventional radiography to advanced molecular imaging techniques, and discusses the implications of a nuanced understanding of bone metastasis biology for therapeutic intervention. This includes the development of targeted therapies and strategies for managing bone pain and other skeletal-related events. Moreover, this review underscores the imperative of ongoing research efforts aimed at identifying novel therapeutic targets and refining management approaches for bone metastases. It advocates for a multidisciplinary strategy that integrates advancements in medical oncology and radiology with insights derived from molecular biology and genetics, to enhance prognostic outcomes and the quality of life for patients afflicted by this debilitating condition. In summary, bone metastases constitute a complex issue that demands a comprehensive and informed approach to treatment. This article contributes to the ongoing discourse by consolidating existing knowledge and identifying avenues for future investigation, with the overarching objective of ameliorating patient care in the domain of oncology.

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Hajianfar G, Sabouri M, Salimi Y, Amini M, Bagheri S, Jenabi E, Hekmat S, Maghsudi M, Mansouri Z, Khateri M, Hosein Jamshidi M, Jafari E, Bitarafan Rajabi A, Assadi M, Oveisi M, Shiri I, Zaidi H. Artificial intelligence-based analysis of whole-body bone scintigraphy: The quest for the optimal deep learning algorithm and comparison with human observer performance. Z Med Phys 2024;34:242-257. [PMID: 36932023 PMCID: PMC11156776 DOI: 10.1016/j.zemedi.2023.01.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 12/22/2022] [Accepted: 01/18/2023] [Indexed: 03/17/2023]

Abstract

PURPOSE

Whole-body bone scintigraphy (WBS) is one of the most widely used modalities in diagnosing malignant bone diseases during the early stages. However, the procedure is time-consuming and requires vigour and experience. Moreover, interpretation of WBS scans in the early stages of the disorders might be challenging because the patterns often reflect normal appearance that is prone to subjective interpretation. To simplify the gruelling, subjective, and prone-to-error task of interpreting WBS scans, we developed deep learning (DL) models to automate two major analyses, namely (i) classification of scans into normal and abnormal and (ii) discrimination between malignant and non-neoplastic bone diseases, and compared their performance with human observers.

MATERIALS AND METHODS

After applying our exclusion criteria on 7188 patients from three different centers, 3772 and 2248 patients were enrolled for the first and second analyses, respectively. Data were split into two parts, including training and testing, while a fraction of training data were considered for validation. Ten different CNN models were applied to single- and dual-view input (posterior and anterior views) modes to find the optimal model for each analysis. In addition, three different methods, including squeeze-and-excitation (SE), spatial pyramid pooling (SPP), and attention-augmented (AA), were used to aggregate the features for dual-view input models. Model performance was reported through area under the receiver operating characteristic (ROC) curve (AUC), accuracy, sensitivity, and specificity and was compared with the DeLong test applied to ROC curves. The test dataset was evaluated by three nuclear medicine physicians (NMPs) with different levels of experience to compare the performance of AI and human observers.

RESULTS

DenseNet121_AA (DensNet121, with dual-view input aggregated by AA) and InceptionResNetV2_SPP achieved the highest performance (AUC = 0.72) for the first and second analyses, respectively. Moreover, on average, in the first analysis, Inception V3 and InceptionResNetV2 CNN models and dual-view input with AA aggregating method had superior performance. In addition, in the second analysis, DenseNet121 and InceptionResNetV2 as CNN methods and dual-view input with AA aggregating method achieved the best results. Conversely, the performance of AI models was significantly higher than human observers for the first analysis, whereas their performance was comparable in the second analysis, although the AI model assessed the scans in a drastically lower time.

CONCLUSION

Using the models designed in this study, a positive step can be taken toward improving and optimizing WBS interpretation. By training DL models with larger and more diverse cohorts, AI could potentially be used to assist physicians in the assessment of WBS images.

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Affiliation(s)

Ghasem Hajianfar Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva 4, Switzerland
Maziar Sabouri Department of Medical Physics, School of Medicine, Iran University of Medical Science, Tehran, Iran; Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
Yazdan Salimi Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva 4, Switzerland
Mehdi Amini Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva 4, Switzerland
Soroush Bagheri Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
Elnaz Jenabi Research Center for Nuclear Medicine, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
Sepideh Hekmat Hasheminejad Hospital, Iran University of Medical Sciences, Tehran, Iran
Mehdi Maghsudi Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
Zahra Mansouri Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva 4, Switzerland
Maziar Khateri Department of Medical Radiation Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Mohammad Hosein Jamshidi Department of Medical Imaging and Radiation Sciences, School of Allied Medical Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
Esmail Jafari The Persian Gulf Nuclear Medicine Research Center, Department of Molecular Imaging and Radionuclide Therapy, Bushehr Medical University Hospital, School of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran
Ahmad Bitarafan Rajabi Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
Majid Assadi The Persian Gulf Nuclear Medicine Research Center, Department of Molecular Imaging and Radionuclide Therapy, Bushehr Medical University Hospital, School of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran
Mehrdad Oveisi Department of Computer Science, University of British Columbia, Vancouver, BC, Canada
Isaac Shiri Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva 4, Switzerland
Habib Zaidi Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva 4, Switzerland; Geneva University Neurocenter, Geneva University, Geneva, Switzerland; Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Nuclear Medicine, University of Southern Denmark, Odense, Denmark.

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Wang AQ, Karaman BK, Kim H, Rosenthal J, Saluja R, Young SI, Sabuncu MR. A Framework for Interpretability in Machine Learning for Medical Imaging. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2024;12:53277-53292. [PMID: 39421804 PMCID: PMC11486155 DOI: 10.1109/access.2024.3387702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2024]

Motohashi M, Funauchi Y, Adachi T, Fujioka T, Otaka N, Kamiko Y, Okada T, Tateishi U, Okawa A, Yoshii T, Sato S. A New Deep Learning Algorithm for Detecting Spinal Metastases on Computed Tomography Images. Spine (Phila Pa 1976) 2024;49:390-397. [PMID: 38084012 PMCID: PMC10898548 DOI: 10.1097/brs.0000000000004889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 11/18/2023] [Indexed: 02/29/2024]

Abstract

STUDY DESIGN

Retrospective diagnostic study.

OBJECTIVE

To automatically detect osteolytic bone metastasis lesions in the thoracolumbar region using conventional computed tomography (CT) scans, we developed a new deep learning (DL)-based computer-aided detection model.

SUMMARY OF BACKGROUND DATA

Radiographic detection of bone metastasis is often difficult, even for orthopedic surgeons and diagnostic radiologists, with a consequent risk for pathologic fracture or spinal cord injury. If we can improve detection rates, we will be able to prevent the deterioration of patients' quality of life at the end stage of cancer.

MATERIALS AND METHODS

This study included CT scans acquired at Tokyo Medical and Dental University (TMDU) Hospital between 2016 and 2022. A total of 263 positive CT scans that included at least one osteolytic bone metastasis lesion in the thoracolumbar spine and 172 negative CT scans without bone metastasis were collected for the datasets to train and validate the DL algorithm. As a test data set, 20 positive and 20 negative CT scans were separately collected from the training and validation datasets. To evaluate the performance of the established artificial intelligence (AI) model, sensitivity, precision, F1-score, and specificity were calculated. The clinical utility of our AI model was also evaluated through observer studies involving six orthopaedic surgeons and six radiologists.

RESULTS

Our AI model showed a sensitivity, precision, and F1-score of 0.78, 0.68, and 0.72 (per slice) and 0.75, 0.36, and 0.48 (per lesion), respectively. The observer studies revealed that our AI model had comparable sensitivity to orthopaedic or radiology experts and improved the sensitivity and F1-score of residents.

CONCLUSION

We developed a novel DL-based AI model for detecting osteolytic bone metastases in the thoracolumbar spine. Although further improvement in accuracy is needed, the current AI model may be applied to current clinical practice.

LEVEL OF EVIDENCE

Level III.

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Cao C, Fang Y, Yu B, Xu Y, Qiang M, Tao C, Huang S, Chen X. Use of 18F-FDG PET/MRI as an Initial Staging Procedure for Nasopharyngeal Carcinoma. J Magn Reson Imaging 2024;59:922-928. [PMID: 37256732 DOI: 10.1002/jmri.28842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 05/20/2023] [Accepted: 05/22/2023] [Indexed: 06/02/2023] Open

Abstract

BACKGROUND

Compared with the conventional work-up (CWU) including computed tomography (CT) of the chest and abdomen, MRI of the head and neck, and skeletal scintigraphy, positron emission tomography (PET)/MRI might improve diagnostic accuracy, shorten the work-up time, and reduce false-positive (FP) findings in patients with nasopharyngeal carcinoma (NPC). However, evidence of cost-effectiveness is needed for the adoption of PET/MRI for the initial staging in NPC.

PURPOSE

To evaluate the cost-effectiveness and clinical value of PET/MRI as an initial staging procedure for NPC.

STUDY TYPE

Retrospective cohort cost effectiveness study.

SUBJECTS

Three hundred forty-three patients with a median age of 51 (13-81) years underwent PET/MRI before treatment (the PET/MRI group) and the remaining 677 patients with a median age of 55 (15-95) years only underwent CWU (the CWU group). There were 80 (23.3%) females and 193 (28.5%) females in the PET/MRI and CWU groups, respectively.

FIELD STRENGTH/SEQUENCE

3-T integrated PET/MRI system, diffusion-weighted echo-planar imaging (b = 0 and 1000 s/mm2 ) and [18F] fluorodeoxyglucose PET.

ASSESSMENT

The primary end point was the FP rate. Costs were determined as issued in 2021 by the Medical Insurance Administration Bureau of Zhejiang, China.

STATISTICAL TESTS

Incremental cost effectiveness ratio (ICER) measured cost of using PET/MRI per percent of patients who avoided a FP. A P-value <0.05 was considered statistically significant.

RESULTS

For the whole group, the de novo metastatic disease rate was 5.2% (53/1020). A total of 187 patients with FP results were observed. Significantly more patients with FP results were observed in the CWU group compared to the PET/MRI group (25.6% vs. 4.1%). The ICER was $54 for each percent of patients avoiding a FP finding.

DATA CONCLUSION

Compared with CWU, PET/MRI may reduce the FP risk. Furthermore, PET/MRI may be cost-effective as an initial staging procedure for NPC.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 6.

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Affiliation(s)

Caineng Cao Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Key Laboratory of Head & Neck Cancer Translational Research of Zhejiang Province, Hangzhou, Zhejiang, China
Yuting Fang Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Key Laboratory of Head & Neck Cancer Translational Research of Zhejiang Province, Hangzhou, Zhejiang, China
Bocheng Yu School of Information Technology, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
Yuanfan Xu Hangzhou Universal Medical Imagine Diagnostion Center, Hangzhou, Zhejiang, China
Mengyun Qiang Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Key Laboratory of Head & Neck Cancer Translational Research of Zhejiang Province, Hangzhou, Zhejiang, China
Changjuan Tao Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Key Laboratory of Head & Neck Cancer Translational Research of Zhejiang Province, Hangzhou, Zhejiang, China
Shuang Huang Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Key Laboratory of Head & Neck Cancer Translational Research of Zhejiang Province, Hangzhou, Zhejiang, China
Xiaozhong Chen Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Key Laboratory of Head & Neck Cancer Translational Research of Zhejiang Province, Hangzhou, Zhejiang, China

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Elaasser B, Arakil N, Mohammad KS. Bridging the Gap in Understanding Bone Metastasis: A Multifaceted Perspective. Int J Mol Sci 2024;25:2846. [PMID: 38474093 PMCID: PMC10932255 DOI: 10.3390/ijms25052846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 02/19/2024] [Accepted: 02/26/2024] [Indexed: 03/14/2024] Open

Jimah BB, Amoako E, Ofori EO, Akakpo PK, Aniakwo LA, Ulzen‐Appiah K, Imbeah EG, Morna MT, Koggoh P, Akligoh H, Tackie R, Manu A, Paemka L, Sarkodie BD, Offei AK, Hutchful D, Ngoi J, Bediako Y, Rahman GA. Radiologic patterns of distant organ metastasis in advanced breast cancer patients: Prospective review of computed tomography images. Cancer Rep (Hoboken) 2024;7:e1988. [PMID: 38351553 PMCID: PMC10864737 DOI: 10.1002/cnr2.1988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 01/11/2024] [Accepted: 01/15/2024] [Indexed: 02/16/2024] Open

Sunny SS, Oommen R, Hephzibah J, Shanthly N, Mathew D, Eapen A. Analysis of discordant PET and CT findings in 18F-FDG PET-CT scans in the management of oncology patients. Indian J Cancer 2024;61:43-50. [PMID: 38090959 DOI: 10.4103/ijc.ijc_1202_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 01/24/2021] [Indexed: 12/05/2024]

Raoufinia R, Afrasiabi P, Dehghanpour A, Memarpour S, Hosseinian SHS, Saburi E, Naghipoor K, Rezaei S, Haghmoradi M, Keyhanvar N, Rostami M, Fakoor F, Kazemi MI, Moghbeli M, Rahimi HR. The Landscape of microRNAs in Bone Tumor: A Comprehensive Review in Recent Studies. Microrna 2024;13:175-201. [PMID: 39005129 DOI: 10.2174/0122115366298799240625115843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 04/11/2024] [Accepted: 05/23/2024] [Indexed: 07/16/2024]

Affiliation(s)

Ramin Raoufinia Noncommunicable Diseases Research Center, Neyshabur University of Medical Sciences, Neyshabur, Iran Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
Parisa Afrasiabi Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
Amir Dehghanpour Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
Sara Memarpour Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
Sayyed Hadi Sayyed Hosseinian Orthopedic Research Center, Shahid Kamyab Hospital, Mashhad University of Medical Sciences, Mashhad, Iran
Ehsan Saburi Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
Karim Naghipoor Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
Samaneh Rezaei Vascular and Endovascular Surgery Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
Meisam Haghmoradi Orthopedic Research Center, Shahid Kamyab Hospital, Mashhad University of Medical Sciences, Mashhad, Iran
Neda Keyhanvar Department of Biochemistry & Biophysics, University of California San Francisco, San Francisco, CA, 94107, USA
Mehdi Rostami Department of Clinical Biochemistry, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
Farhad Fakoor Department of Paramedical Sciences, Iran University of Medical Sciences, Tehran, Iran
Mohammadali Izadpanah Kazemi Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
Meysam Moghbeli Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
Hamid Reza Rahimi Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran Vascular and Endovascular Surgery Research Center, Mashhad University of Medical Sciences, Mashhad, Iran

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Park SY, Yoon MA, Lee MH, Lee SH, Chung HW. [Imaging Findings of Spinal Metastases with Differential Diagnosis: Focusing on Solitary Spinal Lesion in Older Patients]. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2024;85:77-94. [PMID: 38362381 PMCID: PMC10864150 DOI: 10.3348/jksr.2023.0156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/06/2024] [Accepted: 01/18/2024] [Indexed: 02/17/2024]

Poon D, Tang C, Vijayanathan S, Mak D. The use of MRI for the imaging of metastatic bone lesions. THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING : OFFICIAL PUBLICATION OF THE ITALIAN ASSOCIATION OF NUCLEAR MEDICINE (AIMN) [AND] THE INTERNATIONAL ASSOCIATION OF RADIOPHARMACOLOGY (IAR), [AND] SECTION OF THE SOCIETY OF... 2023;67:271-279. [PMID: 38054411 DOI: 10.23736/s1824-4785.23.03538-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]

Moretti R, Meffe G, Annunziata S, Capotosti A. Innovations in imaging modalities: a comparative review of MRI, long-axial field-of-view PET, and full-ring CZT-SPECT in detecting bone metastases. THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING : OFFICIAL PUBLICATION OF THE ITALIAN ASSOCIATION OF NUCLEAR MEDICINE (AIMN) [AND] THE INTERNATIONAL ASSOCIATION OF RADIOPHARMACOLOGY (IAR), [AND] SECTION OF THE SOCIETY OF... 2023;67:259-270. [PMID: 37870526 DOI: 10.23736/s1824-4785.23.03537-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/24/2023]

Wang H, Qiu J, Xie J, Lu W, Pan Y, Ma J, Jia M. Radiomics‑Clinical model based on ^99mTc-MDP SPECT/CT for distinguishing between bone metastasis and benign bone disease in tumor patients. J Cancer Res Clin Oncol 2023;149:13353-13361. [PMID: 37491635 DOI: 10.1007/s00432-023-05162-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 07/09/2023] [Indexed: 07/27/2023]

Montoya-Bordón J, Elvira-Ruiz P, Carriazo-Jiménez B, Robles-Blanco C, Pereiro-Montbrun F, Rodríguez-Fernández C. Imaging diagnosis of vertebral metastasis. Rev Esp Cir Ortop Traumatol (Engl Ed) 2023;67:511-522. [PMID: 37209915 DOI: 10.1016/j.recot.2023.05.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 05/02/2023] [Accepted: 05/12/2023] [Indexed: 05/22/2023] Open

Montoya-Bordón J, Elvira-Ruiz P, Carriazo-Jiménez B, Robles-Blanco C, Pereiro-Montbrun F, Rodríguez-Fernández C. [Translated article] Imaging diagnosis of vertebral metastasis. Rev Esp Cir Ortop Traumatol (Engl Ed) 2023;67:S511-S522. [PMID: 37541345 DOI: 10.1016/j.recot.2023.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 05/12/2023] [Indexed: 08/06/2023] Open

Hardcastle N, Liu Y, Siva S, David S. [¹⁸F]NaF PET/CT imaging of response to single fraction SABR to bone metastases from breast cancer. FRONTIERS IN NUCLEAR MEDICINE (LAUSANNE, SWITZERLAND) 2023;3:1197397. [PMID: 39380960 PMCID: PMC11460292 DOI: 10.3389/fnume.2023.1197397] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 09/15/2023] [Indexed: 10/10/2024]

Yang J, Deng J, Fan D, Chen G, Lu Z, Liu H, Mok GSP, Chen Y. Biodistribution and Internal Dosimetry of 68 Ga-DOTA-IBA PET Imaging for Patients With Bone Metastases. Clin Nucl Med 2023;48:847-852. [PMID: 37418288 DOI: 10.1097/rlu.0000000000004757] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/08/2023]

Chen YY, Yu PN, Lai YC, Hsieh TC, Cheng DC. Bone Metastases Lesion Segmentation on Breast Cancer Bone Scan Images with Negative Sample Training. Diagnostics (Basel) 2023;13:3042. [PMID: 37835785 PMCID: PMC10572884 DOI: 10.3390/diagnostics13193042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 09/18/2023] [Accepted: 09/22/2023] [Indexed: 10/15/2023] Open

Ashique S, Faiyazuddin M, Afzal O, Gowri S, Hussain A, Mishra N, Garg A, Maqsood S, Akhtar MS, Altamimi AS. Advanced nanoparticles, the hallmark of targeted drug delivery for osteosarcoma-an updated review. J Drug Deliv Sci Technol 2023;87:104753. [DOI: 10.1016/j.jddst.2023.104753] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2025]

Sood A, Kashikar SV, Mishra GV, Parihar P, Khandelwal S, Suryadevara M, Manuja N, Saboo K, Batra N, Ahuja A. The Spectrum of Shoulder Pathologies on Magnetic Resonance Imaging: A Pictorial Review. Cureus 2023;15:e44801. [PMID: 37809114 PMCID: PMC10558894 DOI: 10.7759/cureus.44801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 09/06/2023] [Indexed: 10/10/2023] Open

Wilson DS, Mohammad S, Hussain A. A Novel Report of Suspected Prostate Adenocarcinoma to Orbital Roof Meningioma Metastasis. Ophthalmic Plast Reconstr Surg 2023;39:e166-e168. [PMID: 37326486 DOI: 10.1097/iop.0000000000002423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]

Schlaeger S, Drummer K, El Husseini M, Kofler F, Sollmann N, Schramm S, Zimmer C, Wiestler B, Kirschke JS. Synthetic T2-weighted fat sat based on a generative adversarial network shows potential for scan time reduction in spine imaging in a multicenter test dataset. Eur Radiol 2023;33:5882-5893. [PMID: 36928566 PMCID: PMC10326102 DOI: 10.1007/s00330-023-09512-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 11/17/2022] [Accepted: 02/03/2023] [Indexed: 03/18/2023]

Abstract

OBJECTIVES

T2-weighted (w) fat sat (fs) sequences, which are important in spine MRI, require a significant amount of scan time. Generative adversarial networks (GANs) can generate synthetic T2-w fs images. We evaluated the potential of synthetic T2-w fs images by comparing them to their true counterpart regarding image and fat saturation quality, and diagnostic agreement in a heterogenous, multicenter dataset.

METHODS

A GAN was used to synthesize T2-w fs from T1- and non-fs T2-w. The training dataset comprised scans of 73 patients from two scanners, and the test dataset, scans of 101 patients from 38 multicenter scanners. Apparent signal- and contrast-to-noise ratios (aSNR/aCNR) were measured in true and synthetic T2-w fs. Two neuroradiologists graded image (5-point scale) and fat saturation quality (3-point scale). To evaluate whether the T2-w fs images are indistinguishable, a Turing test was performed by eleven neuroradiologists. Six pathologies were graded on the synthetic protocol (with synthetic T2-w fs) and the original protocol (with true T2-w fs) by the two neuroradiologists.

RESULTS

aSNR and aCNR were not significantly different between the synthetic and true T2-w fs images. Subjective image quality was graded higher for synthetic T2-w fs (p = 0.023). In the Turing test, synthetic and true T2-w fs could not be distinguished from each other. The intermethod agreement between synthetic and original protocol ranged from substantial to almost perfect agreement for the evaluated pathologies.

DISCUSSION

The synthetic T2-w fs might replace a physical T2-w fs. Our approach validated on a challenging, multicenter dataset is highly generalizable and allows for shorter scan protocols.

KEY POINTS

• Generative adversarial networks can be used to generate synthetic T2-weighted fat sat images from T1- and non-fat sat T2-weighted images of the spine. • The synthetic T2-weighted fat sat images might replace a physically acquired T2-weighted fat sat showing a better image quality and excellent diagnostic agreement with the true T2-weighted fat images. • The present approach validated on a challenging, multicenter dataset is highly generalizable and allows for significantly shorter scan protocols.

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Affiliation(s)

Sarah Schlaeger Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Katharina Drummer Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
Malek El Husseini Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
Florian Kofler Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany Department of Informatics, Technical University of Munich, Munich, Germany TranslaTUM - Central Institute for Translational Cancer Research, Technical University of Munich, Munich, Germany Helmholtz AI, Helmholtz Zentrum München, Munich, Germany
Nico Sollmann Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany TUM-NeuroImaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
Severin Schramm Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
Claus Zimmer Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany TUM-NeuroImaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
Benedikt Wiestler Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
Jan S Kirschke Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany TUM-NeuroImaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

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Yu PN, Lai YC, Chen YY, Cheng DC. Skeleton Segmentation on Bone Scintigraphy for BSI Computation. Diagnostics (Basel) 2023;13:2302. [PMID: 37443695 DOI: 10.3390/diagnostics13132302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 07/02/2023] [Accepted: 07/05/2023] [Indexed: 07/15/2023] Open

Khojasteh E, Dehdashti F, Shokeen M. Molecular imaging of bone metastasis. J Bone Oncol 2023;40:100477. [PMID: 37193117 PMCID: PMC10182320 DOI: 10.1016/j.jbo.2023.100477] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 03/27/2023] [Accepted: 03/31/2023] [Indexed: 05/18/2023] Open

Fang Y, Chen S, Xu Y, Qiang M, Tao C, Huang S, Wang L, Chen X, Cao C. Assessment of bone lesions with 18 F-FDG PET/MRI in patients with nasopharyngeal carcinoma. Nucl Med Commun 2023;44:457-462. [PMID: 36897049 DOI: 10.1097/mnm.0000000000001682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]

Affiliation(s)

Yuting Fang Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences; Key Laboratory of Head and Neck Cancer Translational Research of Zhejiang Province Graduate school, Wenzhou Medical University, Wenzhou, Zhejiang, China
Shoucong Chen Department of Nuclear Medicine, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences
Yuanfan Xu Hangzhou Universal Medical Imagine Diagnostion Center, Hangzhou, Zhejiang, China
Mengyun Qiang Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences; Key Laboratory of Head and Neck Cancer Translational Research of Zhejiang Province
Changjuan Tao Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences; Key Laboratory of Head and Neck Cancer Translational Research of Zhejiang Province
Shuang Huang Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences; Key Laboratory of Head and Neck Cancer Translational Research of Zhejiang Province
Lei Wang Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences; Key Laboratory of Head and Neck Cancer Translational Research of Zhejiang Province
Xiaozhong Chen Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences; Key Laboratory of Head and Neck Cancer Translational Research of Zhejiang Province
Caineng Cao Department of Radiation Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences; Key Laboratory of Head and Neck Cancer Translational Research of Zhejiang Province

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Wogram E, Schlunk F, Shah MJ, Prinz M, Urbach H, Erny D, Taschner CA. Freiburg Neuropathology Case Conference : A 51-year-old Patient Presenting with Epistaxis and Occasional Headaches 16 Years after Diagnosis of a Grade 1 Chondrosarcoma of the Left Petrous Apex. Clin Neuroradiol 2023;33:569-575. [PMID: 37171609 DOI: 10.1007/s00062-023-01294-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/17/2023] [Indexed: 05/13/2023]

Nigam R, Field M, Harris G, Barton M, Carolan M, Metcalfe P, Holloway L. Automated detection, delineation and quantification of whole-body bone metastasis using FDG-PET/CT images. Phys Eng Sci Med 2023;46:851-863. [PMID: 37126152 DOI: 10.1007/s13246-023-01258-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 04/11/2023] [Indexed: 05/02/2023]

Abstract

Non-small cell lung cancer (NSCLC) patients with the metastatic spread of disease to the bone have high morbidity and mortality. Stereotactic ablative body radiotherapy increases the progression free survival and overall survival of these patients with oligometastases. FDG-PET/CT, a functional imaging technique combining positron emission tomography (PET) with 18 F-fluorodeoxyglucose (FDG) and computer tomography (CT) provides improved staging and identification of treatment response. It is also associated with reduction in size of the radiotherapy tumour volume delineation compared with CT based contouring in radiotherapy, thus allowing for dose escalation to the target volume with lower doses to the surrounding organs at risk. FDG-PET/CT is increasingly being used for the clinical management of NSCLC patients undergoing radiotherapy and has shown high sensitivity and specificity for the detection of bone metastases in these patients. Here, we present a software tool for detection, delineation and quantification of bone metastases using FDG-PET/CT images. The tool extracts standardised uptake values (SUV) from FDG-PET images for auto-segmentation of bone lesions and calculates volume of each lesion and associated mean and maximum SUV. The tool also allows automatic statistical validation of the auto-segmented bone lesions against the manual contours of a radiation oncologist. A retrospective review of FDG-PET/CT scans of more than 30 candidate NSCLC patients was performed and nine patients with one or more metastatic bone lesions were selected for the present study. The SUV threshold prediction model was designed by splitting the cohort of patients into a subset of 'development' and 'validation' cohorts. The development cohort yielded an optimum SUV threshold of 3.0 for automatic detection of bone metastases using FDG-PET/CT images. The validity of the derived optimum SUV threshold on the validation cohort demonstrated that auto-segmented and manually contoured bone lesions showed strong concordance for volume of bone lesion (r = 0.993) and number of detected lesions (r = 0.996). The tool has various applications in radiotherapy, including but not limited to studies determining optimum SUV threshold for accurate and standardised delineation of bone lesions and in scientific studies utilising large patient populations for instance for investigation of the number of metastatic lesions that can be treated safety with an ablative dose of radiotherapy without exceeding the normal tissue toxicity.

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