1219 Fig. 1 Procedure for creating a digital phantom for CT (a) Step 1. Agar phantoms adjusted to give CT values of 0 HU and 20 HU were allowed to har

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1 1218 原著 Code Nos CT-Perfusion 大村知己豊嶋英仁佐藤祐一郎石田嵩人緒言 Computed tomography CT 320 multi-detector row CT 320MDCT 160 mm 1 CT CT-perfusion: CTP CT angiography 4D-CTA 1, 2 CTP mean transist time: MTT cerebral blood volume: CBV cerebral blood flow: CBF arterial input function: AIF time-density curve: TDC CTP Reduction of Radiation Exposure during Computed Tomography Perfusion Using an Iterative Reconstruction Method Tomomi Ohmura, Hideto Toyoshima, Yuichiro Sato, and Takato Ishida Department of Radiology, Research Institute for Brain and Blood Vessels-Akita Received June 4, 2013; Revision accepted September 13, 2013 Code Nos. 251, 883 Summary The purpose of this study was to evaluate the image noise reduction effect of iterative reconstruction (IR) when used to reduce radiation exposure during computed tomography (CT) We scanned a contrast phantom using various radiation doses. Image reconstruction was via filtered back projection (FBP) and IR (adaptive iterative dose reduction 3D: AIDR3D). AIDR3D provided four levels of noise reduction (weak, mild, standard, and strong). We examined the accuracy of CTP map (cerebral blood volume: CBV, mean transist time: MTT, cerebral blood flow: CBF) low-dose IR images to create a digital perfusion phantom that simulates the dynamic curve of ischemic cases using reconstructed images. The optimal filter type of IR was evaluated in the low-frequency area of the NPS at low doses. We were able to obtain the optimal filter type of IR in the low-frequency area of the NPS that was equivalent to that of the reference (150 ma, FBP). The CTP map created using the optimal filter type of IR allowed dose reduction to 80 ma, much lower than the reference. We conclude that it is possible to reduce the dose to 46% of the reference level by using the NPS for dose reduction and IR. IR thus has the potential to contribute to reduction of radiation exposure during CT Key words: computed tomography (CT) perfusion, radiation exposure, iterative reconstruction, noise power spectrum *Proceeding author

1219 Fig. 1 Procedure for creating a digital phantom for CT (a) Step 1. Agar phantoms adjusted to give CT values of 0 HU and 20 HU were allowed to harden and were left unattended for one week.

2 1219 Fig. 1 Procedure for creating a digital phantom for CT (a) Step 1. Agar phantoms adjusted to give CT values of 0 HU and 20 HU were allowed to harden and were left unattended for one week. A contrast phantom that changed continually from 0 20 HU resulted. (b) Step 2. Forty images of uniform images with a CT value of 0 20 HU were acquired by scanning the contrast phantom. (c) Step 3. The 40 images were sorted along the TDC, and a perfusion digital phantom comprising one set of 30 images was created. CTP MDCT 1 TDC 20 HU 8 CTP 9 CT iterative reconstruction: IR 3D-CTA CT 10, 11 CTP CTP noise power spectrum NPS IR IR 1. 方法 1-1 Fig mm HU CT 1 2 CT 0 20 HU Fig. 1a 10 mm 1-2 CT 0 20 HU 40 Fig. 1b CTP CT 7 mm 30 Fig. 1c CTP 15 O PET 3 TDC 3 Vol. 69 No. 11 Nov 2013

3 1220 a b Fig. 2 TDC used for the perfusion digital phantom. The TDC was the average of values obtained from three patients with cerebrovascular disease. (a) AIF and VOF values for two TDCs (b) Normal and ischemic perfusion at brain tissue for two TDCs Fig. 2 ImageJ CT Aquilion ONE 80 kv 1.0 s/rot 160 mm 5 mm display field of view DFOV 240 mm GuLACTIC ma ma ma filtered back projection: FBP IR Adaptive Iterative Dose Reduction AIDR 3D AIDR3D 25 weak 50 mild 75 standard 75 strong 4 CTA FC42 ziostation2 block-circulant singular value decomposition b-svd 17 CBF CBV MTT 1-3 IR CT standard deviation: SD NPS CTP CT HU 18, 19 NPS Fig. 1b 40 mm 3 NPS Mathematica radial frequency 13, NPS NPS CT NPS 0.2 cycles/mm IR NPS 0.2 cycles/mm± ma FBP 0.2 cycles/mm±10 IR 1-4 IR CBV MTT CBF 150 ma FBP 20 mmφ

1221 Fig. 3 Position of ten regions of interest measuring ø 20 mm on the perfusion map. 10 Fig. 3 Box plot Mann-Whitney s U Fig. 4 Comparison between scan dosage and mean of NPS 0.

4 1221 Fig. 3 Position of ten regions of interest measuring ø 20 mm on the perfusion map. 10 Fig. 3 Box plot Mann-Whitney s U Fig. 4 Comparison between scan dosage and mean of NPS 0.2 cycles/mm with ±10% variation in image processing. 120 ma IR weak, 100 ma IR mild, 80 ma IR standard and 60 ma IR strong which were nearest to the dotted line were judged to be optimal. 2. 結果 2-1 IR NPS 0.2 cycles/mm±10 NPS Fig. 4 NPS 150 ma FBP NPS IR weak mild standard strong NPS 150 ma FBP NPS IR 120 ma weak 100 ma mild 80 ma standard 60 ma strong 40 ma IR NPS Fig cycles/mm±10 NPS IR 60 ma strong NPS 2-2 IR Fig. 6 IR Fig. 5 NPS of the optimized IR filter type. Fig. 7 9 CBV MTT 120 ma weak 100 ma mild 80 ma standard 60 ma strong CBV MTT CBF Vol. 69 No. 11 Nov 2013

1222 Fig. 6 The digital phantom and perfusion map which were processed using an optimized IR method filter type. The images of the digital phantom were at the peaks of the TDC. Fig. 7 An evaluation of CBV computed using the digital phantom which simulated normal and ischemic Fig.

5 1222 Fig. 6 The digital phantom and perfusion map which were processed using an optimized IR method filter type. The images of the digital phantom were at the peaks of the TDC. Fig. 7 An evaluation of CBV computed using the digital phantom which simulated normal and ischemic Fig. 8 An evaluation of MTT computed using the digital phantom which simulated normal and ischemic 日本放射線技術学会雑誌

6 1223 Fig. 9 An evaluation of CBF computed using the digital phantom which simulated normal and ischemic 3. 考察 IR CTP IR 40 9 IR CT PV PV 1/ mas 19 NPS Fig. 4 IR NPS 0.2 cycles/mm±10 NPS Fig. 5 IR 80 ma standard NPS CT CTP IR 21 CTP b-svd 60 ma strong CBV MTT AIF IR AIF IR IR NPS strong Fig. 5 NPS TDC TDC IR AIF AIF IR 60 ma strong 80 ma standard 60 ma strong CBF CBV MTT CBF CTP CTP Vol. 69 No. 11 Nov 2013

7 1224 IR 結語 IR CTP IR IR standard 80 ma 46 謝辞参考文献 CT CT Perfusion Dynamic CTA M CT 2012 BOOK 2012; 44(8): CT 2010; 9(2): Mayer TE, Hamann GF, Baranczyk J, et al. Dynamic CT perfusion imaging of acute stroke. Am J Neuroradiol 2000; 21(8): CT CT Perfusion 2003; 59(12): CT-perfusion 2003; 59(12): CT Brain Perfusion Scans Safety Investigation: Initial Notification. U.S. Food and Drug Administration Wintermark M, Smith WS, Ko NU, et al. Dynamic perfusion CT: optimizing the temporal resolution and contrast volume for calculation of perfusion CT parameters in stroke patients. AJNR Am J Neuroradiol 2004; 25(5): Okumura M, Ota T, Tsukagoshi S, et al. New Method of Evaluating Edge-preserving Adaptive Filters for Computed Tomography (CT): Digital Phantom Method. 2006; 62(7): CT 2004; 60(12): CT 2012; 68(12): CT 2012; 68(12): Hanson KM. Detectability in computed tomographic images. Med Phys 1979; 6(5): Kijewski MF, Judy PF. The noise power spectrum of CT images. Phys Med Biol 1987; 32(5): Boedeker KL, Cooper VN, McNitt-Gray MF. Application of the noise power spectrum in modern diagnostic MDCT: part I. Measurement of noise power spectra and noise equivalent quanta. Phys Med Biol 2007; 52(14): Abramoff MD, Magalhaes PJ, Ram SJ. Image Processing with ImageJ. Biophotonics Int 2004; 11(7): CT perfusion X CT GuLACTIC 2010: Kudo K, Sasaki M, Ogasawara K, et al. Difference in tracer delay-induced effect among deconvolution algorithms in CT perfusion analysis: quantitative evaluation with digital phantoms. Radiology 2009; 251(1): CT MRI 2010: CT 2011; 20(1): X CT 2009: CT 2012; 68(6): ; 68(4):

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05_学術1_フィルタ.indd Arts and Sciences CT The noise reduction effect of the picture which used the quantum noise rejection filter for the filtered back projection in low dose CT photography 1 39496 1 18285 1 56588 1 551 1