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Model-based Iterative Reconstruction in Low-radiation-dose Computed Tomography Colonography

Rationale and Objectives

To assess the effect of model-based iterative reconstruction (MBIR) on image quality and diagnostic performance of low-radiation-dose computed tomography colonography (CTC) in the preoperative assessment of colorectal cancer.

Materials and Methods

This study included 30 patients with colorectal cancer referred for surgical treatment. All patients underwent CTC with a standard dose (SD) protocol in the supine position and a low-dose (LD; radiation dose reduction of approximately 85%) protocol in the prone position. The SD protocol images were post-processed using filtered back projection (FBP), whereas the LD protocol images were post-processed using FBP and MBIR. Objective and subjective image quality parameters were compared among the three different methods. Preoperative evaluations, including site, length, and tumor and node staging were performed, and the findings were compared to the postsurgical findings.

Results

The mean image noise of SD-FBP, LD-FBP, and LD-MBIR images was 17.3 ± 3.2, 40.5 ± 10.9, and 11.2 ± 2.0 Hounsfield units, respectively. There were significant differences for all comparison combinations among the three methods ( P < .01). For image noise, the mean visual scores were significantly higher for SD-FBP and LD-MBIR than for LD-FBP, and the scores for SD-FBP and LD-MBIR were equivalent (3.9 ± 0.3 [SD-FBP], 2.0 ± 0.5 [LD-FBP], and 3.7 ± 0.3 [LD-MBIR]). Preoperative information was more accurate under SD-FBP and LD-MBIR than under LD-FBP, and the information was comparable between SD-FBP and LD-MBIR.

Conclusion

MBIR can yield significantly improved image quality on low-radiation-dose CTC and provide preoperative information equivalent to that of standard-radiation-dose protocol.

Introduction

Colorectal cancer (CRC) is a significant cause of cancer-related death globally, and early detection and appropriate treatment are critical . In patients with CRC, accurate preoperative staging is indispensable and can be generally performed using conventional colonoscopy, double-contrast barium enema, computed tomography (CT), magnetic resonance imaging, and positron emission tomography . More recently, it has been suggested that computed tomography colonography (CTC) is of value in the preoperative evaluation of patients known to have CRC . However, there has been some concern about ionizing radiation exposure associated with increased use of CT in medical practice . As patients with CRC frequently undergo repeated diagnostic and follow-up CT examinations, radiologists must consider radiation dose reduction techniques during CT examinations while maintaining image quality in accordance with the as low as reasonably achievable principle .

Iterative reconstruction (IR) for CT is currently widely used and helps to reduce the quantum noise associated with filtered back projection (FBP) reconstruction. Thus, with the introduction of IR, significant radiation dose reduction during CTC has become possible . Recently, the next generation of IR algorithms have been developed to focus on data restoration and noise reduction using a model-based process (model-based iterative reconstruction [MBIR]) . Previous investigations reported that the radiation dose in screening CTC using MBIR can be reduced by 47%–60% while maintaining diagnostic image quality . However, to the best of our knowledge, there have been no attempts to assess the feasibility of MBIR for radiation dose reduction at preoperative CTC in patients with CRC.

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Materials and Methods

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Study Population and Bowel Preparation

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Table 1

Patient Demographics

Sex (male/female) 18/12 Age (years) 67.7 ± 12 Body weight (kg) 60.3 ± 12.9 Body mass index (kg/m 2 ) 23.1 ± 4.1 Tumor size (mm) 40 ± 18 T stage and tumor size (n/mm) T1 3/34.3 ± 23.5 T2 6/15.7 ± 5.5 T3 11/43.2 ± 16.1 T4 10/49.8 ± 12.4 N stage (N0/N1/N2) 16/5/9 Tumor location (ascending colon/transverse colon/descending colon/sigmoid colon/rectum) 5/3/2/10/10

Data are presented as mean ± standard deviation or number.

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CTC Protocol and Image Reconstruction

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Table 2

Imaging Parameters for the Standard-dose and Low-dose Protocols

SD-FBP LD-FBP LD-FIRST Detector collimation (mm) 80 × 0.5 Tube voltage (kVp) 120 Tube current (mA) 3D automodulation \* Gantry rotation time (s) 0.5 Helical pitch 0.813 Scanning position Supine Prone Prone Image reconstruction FBP FBP FIRST Section thickness/interval (mm) 5.0/5.0 for routine axial and 0.5/0.5 for 3D image

FBP, filtered back projection; FIRST, Forward Projected Model-based Iterative Reconstruction Solution; LD, low dose; SD, standard dose.

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Radiation Dose Evaluation

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Quantitative Image Quality Analysis

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Qualitative Image Quality Analysis

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Preoperative Diagnostic Performance

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Statistical Analysis

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Results

Radiation Dose

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Figure 1, Comparison of median organ doses (mSv) for the LD and SD protocols. With the LD protocol, the organ doses are substantially reduced compared to those for the SD protocol. LD, low dose; SD, standard dose.

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Quantitative Image Quality Analysis

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Table 3

Quantitative Image Noise Assessment

SD-FBP LD-FBP LD-FIRST_P_ Value Splenic flexure (HU) 15.1 ± 2.6 33.5 ± 3.0 10.9 ± 2.6 <.01 \* , †,‡ Mid-descending colon (HU) 15.7 ± 2.5 34.6 ± 3.9 11.2 ± 2.0 <.01 \* , †,‡ Sigmoid-descending colon junction (HU) 19.4 ± 2.5 56.4 ± 9.1 11.4 ± 1.6 <.01 \* , †,‡ Rectum (HU) 19.0 ± 2.7 37.6 ± 5.1 11.3 ± 1.8 <.01 \* , †,‡ Total average (HU) 17.3 ± 3.2 40.5 ± 10.9 11.2 ± 2.0 <.01 \* , †,‡

FBP, filtered back projection; FIRST, Forward Projected Model-based Iterative Reconstruction Solution; HU, Hounsfield unit; LD, low dose; SD, standard dose.

Data are presented as mean ± standard deviation.

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Qualitative Image Quality Analysis

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Table 4

Qualitative Image Quality Score Assessment

SD-FBP LD-FBP LD-FIRST_P_ Value Mural surface nodularity 4.0 ± 0.2 2.0 ± 0.5 3.6 ± 0.6 <.01 \* , †,‡ Image noise 3.9 ± 0.3 2.0 ± 0.5 3.7 ± 0.3 <.01 \* , ‡

.06 † Depiction of the tumor 3.6 ± 0.6 2.6 ± 0.8 3.6 ± 0.6 <.01 \* , ‡

.97 † Overall image quality 4.0 ± 0.2 2.0 ± 0.5 3.6 ± 0.5 <.01 \* , †,‡

FBP,  filtered back projection; FIRST, Forward Projected Model-based Iterative Reconstruction Solution; LD, low dose; SD, standard dose.

Data are presented as mean ± standard deviation. A 4-point subjective scale was used (1 for unacceptable, 2 for limited diagnostic value, 3 for good, 4 for excellent).

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Preoperative Diagnostic Performance

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Table 5

Preoperative Diagnostic Performance

SD-FBP LD-FBP LD-FIRST Tumor location \* 1.00 1.00 1.00 Morphological types \* 1.00 0.73 1.00 Tumor length (long axis of the bowel) † 0.86 0.78 0.85 T staging \* 0.63 0.37 0.63 N staging \* 0.65 0.14 0.68

FBP, filtered back projection; FIRST, Forward Projected Model-based Iterative Reconstruction Solution; LD, low dose; SD, standard dose.

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Figure 2, A 44-year-old woman with type 2 rectal cancer (arrows) that invaded the muscularis propria (MP). 2D axial colonographic images and 3D endoluminal images acquired at a standard dose (SD) with filtered back projection (FBP) ( a, d ) in the supine position and at a low dose (LD) with FBP ( b, e ) and Forward Projected Model-based Iterative Reconstruction Solution (FIRST) ( c, f ) in the prone position. Image noise and streak artifacts are substantially lower in the images acquired under LD-FIRST than in the images acquired under LD-FBP. Preoperative diagnostic information was equivalent between LD-FIRST images and SD-FBP images.

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Discussion

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References

  • 1. Ferlay J., Steliarova-Foucher E., Lortet-Tieulent J., et. al.: Cancer incidence and mortality patterns in Europe: estimates for 40 countries in 2012. Eur J Cancer 2013; 49: pp. 1374-1403.

  • 2. Dewhurst C., Rosen M.P., Blake M.A., et. al.: ACR appropriateness criteria pretreatment staging of colorectal cancer. J Am Coll Radiol 2012; 9: pp. 775-781.

  • 3. Sali L., Falchini M., Taddei A., et. al.: Role of preoperative CT colonography in patients with colorectal cancer. World J Gastroenterol 2014; 20: pp. 3795-3803.

  • 4. Brenner D.J., Hall E.J.: Computed tomography—an increasing source of radiation exposure. N Engl J Med 2007; 357: pp. 2277-2284.

  • 5. Nagata K., Fujiwara M., Kanazawa H., et. al.: Evaluation of dose reduction and image quality in CT colonography: comparison of low-dose CT with iterative reconstruction and routine-dose CT with filtered back projection. Eur Radiol 2015; 25: pp. 221-229.

  • 6. Flicek K.T., Hara A.K., Silva A.C., et. al.: Reducing the radiation dose for CT colonography using adaptive statistical iterative reconstruction: a pilot study. AJR Am J Roentgenol 2010; 195: pp. 126-131.

  • 7. Lubner M.G., Pooler B.D., Kitchin D.R., et. al.: Sub-milliSievert (sub-mSv) CT colonography: a prospective comparison of image quality and polyp conspicuity at reduced-dose versus standard-dose imaging. Eur Radiol 2015; 25: pp. 2089-2102.

  • 8. Millerd P.J., Paden R.G., Lund J.T., et. al.: Reducing the radiation dose for computed tomography colonography using model-based iterative reconstruction. Abdom Imaging 2015; 40: pp. 1183-1189.

  • 9. Vardhanabhuti V., James J., Nensey R., et. al.: Model-based iterative reconstruction in low-dose CT colonography—feasibility study in 65 patients for symptomatic investigation. Acad Radiol 2015; 22: pp. 563-571.

  • 10. The 2007 Recommendations of the International Commission on Radiological Protection : ICRP publication 103. Ann ICRP 2007; 37: pp. 1-332.

  • 11. Wexner S.D., Cohen S.M., Ulrich A., et. al.: Laparoscopic colorectal surgery—are we being honest with our patients?. Dis Colon Rectum 1995; 38: pp. 723-727.

  • 12. Vignati P., Welch J.P., Cohen J.L.: Endoscopic localization of colon cancers. Surg Endosc 1994; 8: pp. 1085-1087.

  • 13. Piscatelli N., Hyman N., Osler T.: Localizing colorectal cancer by colonoscopy. Arch Surg 2005; 140: pp. 932-935.

  • 14. Cho Y.B., Lee W.Y., Yun H.R., et. al.: Tumor localization for laparoscopic colorectal surgery. World J Surg 2007; 31: pp. 1491-1495.

  • 15. Neri E., Turini F., Cerri F., et. al.: Comparison of CT colonography vs. conventional colonoscopy in mapping the segmental location of colon cancer before surgery. Abdom Imaging 2010; 35: pp. 589-595.

  • 16. Adloff M., Arnaud J.P., Bergamaschi R., et. al.: Synchronous carcinoma of the colon and rectum: prognostic and therapeutic implications. Am J Surg 1989; 157: pp. 299-302.

  • 17. Martin C.J., McAdams S.B., Abdul-Muhsin H., et. al.: The economic implications of a reusable flexible digital ureteroscope: a cost-benefit analysis. J Urol 2017; 197: pp. 730-735.

  • 18. Spada C., Stoker J., Alarcon O., et. al.: Clinical indications for computed tomographic colonography: European Society of Gastrointestinal Endoscopy (ESGE) and European Society of Gastrointestinal and Abdominal Radiology (ESGAR) Guideline. Eur Radiol 2015; 25: pp. 331-345.

  • 19. Taylor S.A., Halligan S., Burling D., et. al.: Intra-individual comparison of patient acceptability of multidetector-row CT colonography and double-contrast barium enema. Clin Radiol 2005; 60: pp. 207-214.

  • 20. Rockey D.C., Paulson E., Niedzwiecki D., et. al.: Analysis of air contrast barium enema, computed tomographic colonography, and colonoscopy: prospective comparison. Lancet 2005; 365: pp. 305-311.

  • 21. Johnson C.D., MacCarty R.L., Welch T.J., et. al.: Comparison of the relative sensitivity of CT colonography and double-contrast barium enema for screen detection of colorectal polyps. Clin Gastroenterol Hepatol 2004; 2: pp. 314-321.

  • 22. Filippone A., Ambrosini R., Fuschi M., et. al.: Preoperative T and N staging of colorectal cancer: accuracy of contrast-enhanced multi-detector row CT colonography—initial experience. Radiology 2004; 231: pp. 83-90.

  • 23. Patino M., Fuentes J.M., Singh S., et. al.: Iterative reconstruction techniques in abdominopelvic CT: technical concepts and clinical implementation. AJR Am J Roentgenol 2015; 205: pp. W19-W31.

  • 24. Nishiyama Y., Tada K., Nishiyama Y., et. al.: Effect of the forward-projected model-based iterative reconstruction solution algorithm on image quality and radiation dose in pediatric cardiac computed tomography. Pediatr Radiol 2016; 46: pp. 1663-1670.

  • 25. Yoon M.A., Kim S.H., Lee J.M., et. al.: Adaptive statistical iterative reconstruction and Veo: assessment of image quality and diagnostic performance in CT colonography at various radiation doses. J Comput Assist Tomogr 2012; 36: pp. 596-601.

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