Semi-automatic artifact quantification in thermal ablation probe and algorithms for the evaluation of metal artifact reduction

被引:0
|
作者
Do, T. D. [1 ,6 ]
Haas, A. [1 ]
Vollherbst, D. F. [2 ]
Pan, F. [1 ,3 ]
Melzig, C. [1 ]
Jesser, J. [2 ]
Pereira, P. L. [4 ]
Kauczor, H. U. [1 ]
Skornitzke, S. [1 ]
Sommer, C. M. [1 ,5 ]
机构
[1] Univ Hosp Heidelberg, Clin Diagnost & Intervent Radiol, Heidelberg, Germany
[2] Univ Hosp Heidelberg, Dept Neuroradiol, Heidelberg, Germany
[3] Huazhong Univ Sci & Technol, Union Hosp, Tongji Med Coll, Dept Radiol, Wuhan, Peoples R China
[4] SLK Kliniken Heilbronn GmbH, Ctr Radiol Minimally Invas Therapies & Nucl Med, Heilbronn, Germany
[5] Univ Hosp Heidelberg, Dept Nucl Med, Heidelberg, Germany
[6] Heidelberg Univ Hosp, Clin Diagnost & Intervent Radiol, Neuenheimer Feld 420, D-69120 Heidelberg, Germany
关键词
Metal artifact reduction; computed tomography; image quality; microwave ablation; radiofrequency ablation; cryoablation; CT-guidance; LIVER-LESIONS; HEPATOCELLULAR-CARCINOMA; MICROWAVE ABLATION; CT ANGIOGRAPHY; RADIOFREQUENCY; PROGRESSION; METASTASES; IMAGES;
D O I
10.1080/02656736.2023.2205071
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Objectives To compare metal artifacts and evaluation of metal artifact reduction algorithms during probe positioning in computed tomography (CT)-guided microwave ablation (MWA), cryoablation (CRYO), and radiofrequency ablation (RFA). Materials and methods Using CT guidance, individual MWA, CRYO, and RFA ablation probes were placed into the livers of 15 pigs. CT imaging was then performed to determine the probe's position within the test subject's liver. Filtered back projection (B30f) and iterative reconstructions (I30-1) were both used with and without dedicated iterative metal artifact reduction (iMAR) to generate images from the initial data sets. Semi-automatic segmentation-based quantitative evaluation was conducted to estimate artifact percentage within the liver, while qualitative evaluation of metal artifact extent and overall image quality was performed by two observers using a 5-point Likert scale: 1-none, 2-mild, 3-moderate, 4-severe, 5-non-diagnostic. Results Among MWA, RFA, and CRYO, compared with non-iMAR in B30f reconstruction, the largest extent of artifact volume percentages were observed for CRYO (11.5-17.9%), followed by MWA (4.7-6.6%) and lastly in RFA (5.5-6.2%). iMAR significantly reduces metal artifacts for CRYO and MWA quantitatively (p = 0.0020; p = 0.0036, respectively) and qualitatively (p = 0.0001, p = 0.0005), but not for RFA. No significant reduction in metal artifact percentage was seen after applying iterative reconstructions (p > 0.05). Noise, contrast-to-noise-ratio, or overall image quality did not differ between probe types, irrespective of the application of iterative reconstruction and iMAR. Conclusion A dedicated metal artifact algorithm may decrease metal artifacts and improves image quality significantly for MWA and CRYO probes. Their application alongside with dedicated metal artifact algorithm should be considered during CT-guided positioning.
引用
收藏
页数:9
相关论文
共 50 条
  • [31] A Comparison and Evaluation of Two Commercially Available Metal Artifact Reduction Applications
    Osawa, Mitsuharu
    Fujita, Naotoshi
    Koyama, Shuji
    Kaneda, Naoki
    Miyachi, Shigeru
    JOURNAL OF NEUROENDOVASCULAR THERAPY, 2024, 18 (08) : 213 - 218
  • [32] Semi-automatic artifact rejection procedure based on kurtosis, renyi's entropy and independent component scalp maps
    Greco, A
    Mammone, N
    Morabito, FC
    Versaci, M
    ENFORMATIKA, VOL 7: IEC 2005 PROCEEDINGS, 2005, : 22 - 26
  • [33] Semi-Automatic Artifact Rejection Procedure based on Kurtosis, Renyi's Entropy and Independent Component Scalp Maps
    Greco, Antonino
    Mammone, Nadia
    Morabito, Francesco Carlo
    Versaci, Mario
    PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 7, 2005, 7 : 22 - 26
  • [34] Simple Approach for Quantification of Metal Artifact Reduction Capabalities of Dual-Energy CT
    Lamichhane, N.
    Padgett, K.
    Li, X.
    Mihaylov, I.
    MEDICAL PHYSICS, 2016, 43 (06) : 3423 - 3423
  • [35] A Task-Based Framework for Assessing the Performance of CT Metal Artifact Reduction Algorithms
    Vaishnav, J. Y.
    Jiang, L.
    Zeng, R.
    Myers, K. J.
    MEDICAL PHYSICS, 2017, 44 (06) : 3177 - 3177
  • [36] A comparative study of 2D metal artifact reduction algorithms in medical CT
    Watzke, O
    Kachelriess, M
    Kalender, WA
    RADIOLOGY, 2000, 217 : 313 - 313
  • [37] A Method for Assessing the Effect of Metal Artifact Reduction Algorithms on Quantitative Characteristics of CT Images
    Yu. A. Vasilev
    D. S. Semenov
    E. S. Akhmad
    O. Yu. Panina
    K. A. Sergunova
    A. V. Petraikin
    Biomedical Engineering, 2020, 54 : 285 - 288
  • [38] A Method for Assessing the Effect of Metal Artifact Reduction Algorithms on Quantitative Characteristics of CT Images
    Vasilev, Yu A.
    Semenov, D. S.
    Akhmad, E. S.
    Panina, O. Yu
    Sergunova, K. A.
    Petraikin, A., V
    BIOMEDICAL ENGINEERING-MEDITSINSKAYA TEKNIKA, 2020, 54 (04): : 285 - 288
  • [39] Metal Artifact Reduction Algorithms for CT in the Trauma Setting: Do They Take Too Long?
    Rose, S.
    Lipford, M.
    Stabo, N.
    Bartels, C.
    Lubner, M.
    Szczykutowicz, T.
    MEDICAL PHYSICS, 2020, 47 (06) : E543 - E543
  • [40] IMPACT OF NOVEL RECONSTRUCTION AND METAL ARTIFACT REDUCTION ALGORITHMS ON METAL ELECTRON DENSITY CURVE FOR KVCT SIMULATOR
    Stodilka, Robert
    Disher, Brandon
    Mulligan, Matt
    Mosalaei, Homeira
    Mehrez, Hatem
    Gaede, Stewart
    RADIOTHERAPY AND ONCOLOGY, 2023, 186 : S121 - S121