Spectral CT in Oncology

Abstract

Background Spectral CT is gaining increasing clinical importance with multiple potential applications, including oncological imaging. Spectral CT-specific image data offers multiple advantages over conventional CT image data through various post-processing algorithms, which will be highlighted in the following review.

Methodology The purpose of this review article is to provide an overview of potential useful oncologic applications of spectral CT and to highlight specific spectral CT pitfalls. The technical background, clinical advantages of primary and follow-up spectral CT exams in oncology, and the application of appropriate spectral tools will be highlighted.

Results/Conclusions Spectral CT imaging offers multiple advantages over conventional CT imaging, particularly in the field of oncology. The combination of virtual native and low monoenergetic images leads to improved detection and characterization of oncologic lesions. Iodine-map images may provide a potential imaging biomarker for assessing treatment response.

Key Points:

• The most important spectral CT reconstructions for oncology imaging are virtual unenhanced, iodine map, and virtual monochromatic reconstructions.

• The combination of virtual unenhanced and low monoenergetic reconstructions leads to better detection and characterization of the vascularization of solid tumors.

• Iodine maps can be a surrogate parameter for tumor perfusion and potentially used as a therapy monitoring parameter.

• For radiotherapy planning, the relative electron density and the effective atomic number of a tissue can be calculated.

Citation Format

• Sauerbeck J, Adam G, Meyer M. Onkologische Bildgebung mittels Spektral-CT. Fortschr Röntgenstr 2023; 195: 21 – 29

Key words

therapy planning - oncology imaging - lesion detection - review - CT - spectral CT

Publikationsverlauf

Eingereicht: 26. Oktober 2021

Angenommen: 03. Juli 2022

Artikel online veröffentlicht:
27. September 2022

• References

• 1 Rajiah P, Parakh A, Kay F. et al. Update on Multienergy CT: Physics, Principles, and Applications. Radiographics 2020; 40: 1284-1308 DOI: 10.1148/rg.2020200038.
• 2 Agrawal MD, Pinho DF, Kulkarni NM. et al. Oncologic applications of dual-energy CT in the abdomen. Radiographics 2014; 34: 589-612 DOI: 10.1148/rg.343135041.
• 3 Odisio EG, Truong MT, Duran C. et al. Role of Dual-Energy Computed Tomography in Thoracic Oncology. Radiol Clin North Am 2018; 56: 535-548 DOI: 10.1016/j.rcl.2018.03.011.
• 4 Meyer M, Hohenberger P, Overhoff D. et al. Dual-Energy CT Vital Iodine Tumor Burden for Response Assessment in Patients With Metastatic GIST Undergoing TKI Therapy: Comparison to Standard CT and FDG PET/CT Criteria. Am J Roentgenol 2021; DOI: 10.2214/Am J Roentgenol.21.26636.
• 5 Gordic S, Puippe GD, Krauss B. et al. Correlation between Dual-Energy and Perfusion CT in Patients with Hepatocellular Carcinoma. Radiology 2016; 280: 78-87 DOI: 10.1148/radiol.2015151560.
• 6 Krauss B. Dual-Energy Computed Tomography: Technology and Challenges. Radiol Clin North Am 2018; 56: 497-506 DOI: 10.1016/j.rcl.2018.03.008.
• 7 McCollough CH, Leng S, Yu L. et al. Dual- and Multi-Energy CT: Principles, Technical Approaches, and Clinical Applications. Radiology 2015; 276: 637-653 DOI: 10.1148/radiol.2015142631.
• 8 Almeida IP, Schyns LE, Ollers MC. et al. Dual-energy CT quantitative imaging: a comparison study between twin-beam and dual-source CT scanners. Med Phys 2017; 44: 171-179 DOI: 10.1002/mp.12000.
• 9 Marin D, Davis D, Roy Choudhury K. et al. Characterization of Small Focal Renal Lesions: Diagnostic Accuracy with Single-Phase Contrast-enhanced Dual-Energy CT with Material Attenuation Analysis Compared with Conventional Attenuation Measurements. Radiology 2017; 284: 737-747 DOI: 10.1148/radiol.2017161872.
• 10 Botsikas D, Triponez F, Boudabbous S. et al. Incidental adrenal lesions detected on enhanced abdominal dual-energy CT: can the diagnostic workup be shortened by the implementation of virtual unenhanced images?. Eur J Radiol 2014; 83: 1746-1751 DOI: 10.1016/j.ejrad.2014.06.017.
• 11 Meyer M, Nelson RC, Vernuccio F. et al. Virtual Unenhanced Images at Dual-Energy CT: Influence on Renal Lesion Characterization. Radiology 2019; 291: 381-390 DOI: 10.1148/radiol.2019181100.
• 12 Van Hedent S, Hokamp NG, Laukamp KR. et al. Differentiation of Hemorrhage from Iodine Using Spectral Detector CT: A Phantom Study. AJNR Am J Neuroradiol 2018; 39: 2205-2210 DOI: 10.3174/ajnr.A5872.
• 13 Slebocki K, Kraus B, Chang DH. et al. Incidental Findings in Abdominal Dual-Energy Computed Tomography: Correlation Between True Noncontrast and Virtual Noncontrast Images Considering Renal and Liver Cysts and Adrenal Masses. J Comput Assist Tomogr 2017; 41: 294-297 DOI: 10.1097/RCT.0000000000000503.
• 14 Fabritius G, Brix G, Nekolla E. et al. Cumulative radiation exposure from imaging procedures and associated lifetime cancer risk for patients with lymphoma. Sci Rep 2016; 6: 35181 DOI: 10.1038/srep35181.
• 15 Kosmala A, Weng AM, Heidemeier A. et al. Multiple Myeloma and Dual-Energy CT: Diagnostic Accuracy of Virtual Noncalcium Technique for Detection of Bone Marrow Infiltration of the Spine and Pelvis. Radiology 2018; 286: 205-213 DOI: 10.1148/radiol.2017170281.
• 16 Kosmala A, Weng AM, Krauss B. et al. Dual-energy CT of the bone marrow in multiple myeloma: diagnostic accuracy for quantitative differentiation of infiltration patterns. Eur Radiol 2018; 28: 5083-5090 DOI: 10.1007/s00330-018-5537-5.
• 17 Huang X, Gao S, Ma Y. et al. The optimal monoenergetic spectral image level of coronary computed tomography (CT) angiography on a dual-layer spectral detector CT with half-dose contrast media. Quant Imaging Med Surg 2020; 10: 592-603 DOI: 10.21037/qims.2020.02.17.
• 18 Grosse Hokamp N, Hoink AJ, Doerner J. et al. Assessment of arterially hyper-enhancing liver lesions using virtual monoenergetic images from spectral detector CT: phantom and patient experience. Abdom Radiol (NY) 2018; 43: 2066-2074 DOI: 10.1007/s00261-017-1411-1.
• 19 Mohammadinejad P, Baffour FI, Adkins MC. et al. Benefits of iterative metal artifact reduction and dual-energy CT towards mitigating artifact in the setting of total shoulder prostheses. Skeletal Radiol 2021; 50: 51-58 DOI: 10.1007/s00256-020-03528-3.
• 20 Eichler M, May M, Wiesmueller M. et al. Single source split filter dual energy: Image quality and liver lesion detection in abdominal CT. Eur J Radiol 2020; 126: 108913 DOI: 10.1016/j.ejrad.2020.108913.
• 21 DʼAngelo T, Cicero G, Mazziotti S. et al. Dual energy computed tomography virtual monoenergetic imaging: technique and clinical applications. Br J Radiol 2019; 92: 20180546 DOI: 10.1259/bjr.20180546.
• 22 Schabel C, Patel B, Harring S. et al. Renal Lesion Characterization with Spectral CT: Determining the Optimal Energy for Virtual Monoenergetic Reconstruction. Radiology 2018; 287: 874-883 DOI: 10.1148/radiol.2018171657.
• 23 Noda Y, Tochigi T, Parakh A. et al. Low keV portal venous phase as a surrogate for pancreatic phase in a pancreatic protocol dual-energy CT: feasibility, image quality, and lesion conspicuity. Eur Radiol 2021; 31: 6898-6908 DOI: 10.1007/s00330-021-07744-w.
• 24 Amato C, Klein L, Wehrse E. et al. Potenzial of contrast agents based on high-Z elements for contrast-enhanced photon-counting computed tomography. Med Phys 2020; 47: 6179-6190 DOI: 10.1002/mp.14519.
• 25 Konstantinides SV, Meyer G, Becattini C. et al. 2019 ESC Guidelines for the diagnosis and management of acute pulmonary embolism developed in collaboration with the European Respiratory Society (ERS). Eur Heart J 2020; 41: 543-603 DOI: 10.1093/eurheartj/ehz405.
• 26 Gladish GW, Choe DH, Marom EM. et al. Incidental pulmonary emboli in oncology patients: prevalence, CT evaluation, and natural history. Radiology 2006; 240: 246-255 DOI: 10.1148/radiol.2401051129.
• 27 Uhrig M, Simons D, Schlemmer HP. Incidental pulmonary emboli in stage IV melanoma patients: Prevalence in CT staging examinations and improved detection with vessel reconstructions based on dual energy CT. PLoS One 2018; 13: e0199458 DOI: 10.1371/journal.pone.0199458.
• 28 Patel BN, Rosenberg M, Vernuccio F. et al. Characterization of Small Incidental Indeterminate Hypoattenuating Hepatic Lesions: Added Value of Single-Phase Contrast-Enhanced Dual-Energy CT Material Attenuation Analysis. Am J Roentgenol 2018; 211: 571-579 DOI: 10.2214/Am J Roentgenol.17.19170.
• 29 Herts BR, Silverman SG, Hindman NM. et al. Management of the Incidental Renal Mass on CT: A White Paper of the ACR Incidental Findings Committee. J Am Coll Radiol 2018; 15: 264-273 DOI: 10.1016/j.jacr.2017.04.028.
• 30 Zarzour JG, Milner D, Valentin R. et al. Quantitative iodine content threshold for discrimination of renal cell carcinomas using rapid kV-switching dual-energy CT. Abdom Radiol (NY) 2017; 42: 727-734 DOI: 10.1007/s00261-016-0967-5.
• 31 Meyer M, Nelson RC, Vernuccio F. et al. Comparison of Iodine Quantification and Conventional Attenuation Measurements for Differentiating Small, Truly Enhancing Renal Masses From High-Attenuation Nonenhancing Renal Lesions With Dual-Energy CT. Am J Roentgenol 2019; 213: W26-W37 DOI: 10.2214/Am J Roentgenol.18.20547.
• 32 Jacobsen MC, Schellingerhout D, Wood CA. et al. Intermanufacturer Comparison of Dual-Energy CT Iodine Quantification and Monochromatic Attenuation: A Phantom Study. Radiology 2018; 287: 224-234 DOI: 10.1148/radiol.2017170896.
• 33 Nagayama Y, Inoue T, Oda S. et al. Adrenal Adenomas versus Metastases: Diagnostic Performance of Dual-Energy Spectral CT Virtual Noncontrast Imaging and Iodine Maps. Radiology 2020; 296: 324-332 DOI: 10.1148/radiol.2020192227.
• 34 Albrecht MH, Vogl TJ, Martin SS. et al. Review of Clinical Applications for Virtual Monoenergetic Dual-Energy CT. Radiology 2019; 293: 260-271 DOI: 10.1148/radiol.2019182297.
• 35 Albrecht MH, Scholtz JE, Kraft J. et al. Assessment of an Advanced Monoenergetic Reconstruction Technique in Dual-Energy Computed Tomography of Head and Neck Cancer. Eur Radiol 2015; 25: 2493-2501 DOI: 10.1007/s00330-015-3627-1.
• 36 Husarik DB, Gordic S, Desbiolles L. et al. Advanced virtual monoenergetic computed tomography of hyperattenuating and hypoattenuating liver lesions: ex-vivo and patient experience in various body sizes. Invest Radiol 2015; 50: 695-702 DOI: 10.1097/RLI.0000000000000171.
• 37 Kovacs DG, Rechner LA, Appelt AL. et al. Metal artefact reduction for accurate tumour delineation in radiotherapy. Radiother Oncol 2018; 126: 479-486 DOI: 10.1016/j.radonc.2017.09.029.
• 38 Bar E, Lalonde A, Royle G. et al. The potential of dual-energy CT to reduce proton beam range uncertainties. Med Phys 2017; 44: 2332-2344 DOI: 10.1002/mp.12215.
• 39 Kornberg A, Schernhammer M, Friess H. (18)F-FDG-PET for Assessing Biological Viability and Prognosis in Liver Transplant Patients with Hepatocellular Carcinoma. J Clin Transl Hepatol 2017; 5: 224-234 DOI: 10.14218/JCTH.2017.00014.
• 40 Gupta R, Phan CM, Leidecker C. et al. Evaluation of dual-energy CT for differentiating intracerebral hemorrhage from iodinated contrast material staining. Radiology 2010; 257: 205-211 DOI: 10.1148/radiol.10091806.
• 41 Apfaltrer P, Meyer M, Meier C. et al. Contrast-enhanced dual-energy CT of gastrointestinal stromal tumors: is iodine-related attenuation a potential indicator of tumor response?. Invest Radiol 2012; 47: 65-70 DOI: 10.1097/RLI.0b013e31823003d2.
• 42 Reimer RP, Hokamp NG, Niehoff J. et al. Value of spectral detector computed tomography for the early assessment of technique efficacy after microwave ablation of hepatocellular carcinoma. PLoS One 2021; 16: e0252678 DOI: 10.1371/journal.pone.0252678.
• 43 Bolus D, Morgan D, Berland L. Effective use of the Hounsfield unit in the age of variable energy CT. Abdom Radiol (NY) 2017; 42: 766-771 DOI: 10.1007/s00261-017-1052-4.
• 44 De Cecco CN, Muscogiuri G, Schoepf UJ. et al. Virtual unenhanced imaging of the liver with third-generation dual-source dual-energy CT and advanced modeled iterative reconstruction. Eur J Radiol 2016; 85: 1257-1264 DOI: 10.1016/j.ejrad.2016.04.012.
• 45 Faby S, Kuchenbecker S, Sawall S. et al. Performance of todayʼs dual energy CT and future multi energy CT in virtual non-contrast imaging and in iodine quantification: A simulation study. Med Phys 2015; 42: 4349-4366 DOI: 10.1118/1.4922654.
• 46 Graser A, Johnson TR, Hecht EM. et al. Dual-energy CT in patients suspected of having renal masses: can virtual nonenhanced images replace true nonenhanced images?. Radiology 2009; 252: 433-440 DOI: 10.1148/radiol.2522080557.
• 47 Ho LM, Marin D, Neville AM. et al. Characterization of adrenal nodules with dual-energy CT: can virtual unenhanced attenuation values replace true unenhanced attenuation values?. Am J Roentgenol 2012; 198: 840-845 DOI: 10.2214/Am J Roentgenol.11.7316.
• 48 Lee HA, Lee YH, Yoon KH. et al. Comparison of Virtual Unenhanced Images Derived From Dual-Energy CT With True Unenhanced Images in Evaluation of Gallstone Disease. Am J Roentgenol 2016; 206: 74-80 DOI: 10.2214/Am J Roentgenol.15.14570.
• 49 Tian SF, Liu AL, Wang HQ. et al. Virtual non-contrast computer tomography (CT) with spectral CT as an alternative to conventional unenhanced CT in the assessment of gastric cancer. Asian Pac J Cancer Prev 2015; 16: 2521-2526
• 50 Borhani AA, Kulzer M, Iranpour N. et al. Comparison of true unenhanced and virtual unenhanced (VUE) attenuation values in abdominopelvic single-source rapid kilovoltage-switching spectral CT. Abdom Radiol (NY) 2017; 42: 710-717 DOI: 10.1007/s00261-016-0991-5.
• 51 Olivia Popnoe D, Ng CS, Zhou S. et al. Comparison of enhancement quantification from virtual unenhanced images to true unenhanced images in multiphase renal Dual-Energy computed tomography: A phantom study. J Appl Clin Med Phys 2019; 20: 171-179 DOI: 10.1002/acm2.12685.
• 52 Popnoe DO, Ng CS, Zhou S. et al. Comparison of virtual to true unenhanced abdominal computed tomography images acquired using rapid kV-switching dual energy imaging. PLoS One 2020; 15: e0238582 DOI: 10.1371/journal.pone.0238582.
• 53 Kordbacheh H, Baliyan V, Singh P. et al. Rapid kVp switching dual-energy CT in the assessment of urolithiasis in patients with large body habitus: preliminary observations on image quality and stone characterization. Abdom Radiol (NY) 2019; 44: 1019-1026 DOI: 10.1007/s00261-018-1808-5.
• 54 Xiao JM, Hippe DS, Zecevic M. et al. Virtual Unenhanced Dual-Energy CT Images Obtained with a Multimaterial Decomposition Algorithm: Diagnostic Value for Renal Mass and Urinary Stone Evaluation. Radiology 2021; 298: 611-619 DOI: 10.1148/radiol.2021192448.