Detection and characterization of renal stones by using photon-counting-based CT

Research output: Contribution to journalArticle

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Abstract

Purpose: To compare a research photon-counting-detector (PCD) CT scanner to a dual-source, dual-energy CT scanner for the detection and characterization of renal stones in human participants with known stones. Materials and Methods: Thirty study participants (median age, 61 years; 10 women) underwent a clinical renal stone characterization scan by using dual-energy CT and a subsequent research PCD CT scan by using the same radiation dose (as represented by volumetric CT dose index). Two radiologists were tasked with detection of stones, which were later characterized as uric acid or non-uric acid by using a commercial dual-energy CT analysis package. Stone size and contrast-to-noise ratio were additionally calculated. McNemar odds ratios and Cohen κ were calculated separately for all stones and small stones (≤ 3 mm). Results: One-hundred sixty renal stones (91 stones that were ≤ 3 mm in axial length) were visually detected. Compared with 1-mm-thick routine images from dual-energy CT, the odds of detecting a stone at PCD CT were 1.29 (95% confidence interval: 0.48, 3.45) for all stones. Stone segmentation and characterization were successful at PCD CT in 70.0% (112 of 160) of stones versus 54.4% (87 of 160) at dual-energy CT, and was superior for stones 3 mm or smaller at PCD CT (45 vs 25 stones, respectively; P =.002). Stone characterization agreement between scanners for stones of all sizes was substantial (κ = 0.65). Conclusion: Photon-counting-detector CT is similar to dual-energy CT for helping to detect renal stones and is better able to help characterize small renal stones.

Original languageEnglish (US)
Pages (from-to)436-442
Number of pages7
JournalRadiology
Volume289
Issue number2
DOIs
StatePublished - Nov 1 2018

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Photons
Kidney
Cone-Beam Computed Tomography
Uric Acid
Research
Noise
Odds Ratio
Confidence Intervals
Radiation
Acids

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

Detection and characterization of renal stones by using photon-counting-based CT. / Marcus, Roy P.; Fletcher, Joel Garland; Ferrero, Andrea; Leng, Shuai; Halaweish, Ahmed F.; Gutjahr, Ralf; Vrtiska, Terri J; Wells, Michael; Enders, Felicity T; McCollough, Cynthia H.

In: Radiology, Vol. 289, No. 2, 01.11.2018, p. 436-442.

Research output: Contribution to journalArticle

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abstract = "Purpose: To compare a research photon-counting-detector (PCD) CT scanner to a dual-source, dual-energy CT scanner for the detection and characterization of renal stones in human participants with known stones. Materials and Methods: Thirty study participants (median age, 61 years; 10 women) underwent a clinical renal stone characterization scan by using dual-energy CT and a subsequent research PCD CT scan by using the same radiation dose (as represented by volumetric CT dose index). Two radiologists were tasked with detection of stones, which were later characterized as uric acid or non-uric acid by using a commercial dual-energy CT analysis package. Stone size and contrast-to-noise ratio were additionally calculated. McNemar odds ratios and Cohen κ were calculated separately for all stones and small stones (≤ 3 mm). Results: One-hundred sixty renal stones (91 stones that were ≤ 3 mm in axial length) were visually detected. Compared with 1-mm-thick routine images from dual-energy CT, the odds of detecting a stone at PCD CT were 1.29 (95{\%} confidence interval: 0.48, 3.45) for all stones. Stone segmentation and characterization were successful at PCD CT in 70.0{\%} (112 of 160) of stones versus 54.4{\%} (87 of 160) at dual-energy CT, and was superior for stones 3 mm or smaller at PCD CT (45 vs 25 stones, respectively; P =.002). Stone characterization agreement between scanners for stones of all sizes was substantial (κ = 0.65). Conclusion: Photon-counting-detector CT is similar to dual-energy CT for helping to detect renal stones and is better able to help characterize small renal stones.",
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AU - Marcus, Roy P.

AU - Fletcher, Joel Garland

AU - Ferrero, Andrea

AU - Leng, Shuai

AU - Halaweish, Ahmed F.

AU - Gutjahr, Ralf

AU - Vrtiska, Terri J

AU - Wells, Michael

AU - Enders, Felicity T

AU - McCollough, Cynthia H

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N2 - Purpose: To compare a research photon-counting-detector (PCD) CT scanner to a dual-source, dual-energy CT scanner for the detection and characterization of renal stones in human participants with known stones. Materials and Methods: Thirty study participants (median age, 61 years; 10 women) underwent a clinical renal stone characterization scan by using dual-energy CT and a subsequent research PCD CT scan by using the same radiation dose (as represented by volumetric CT dose index). Two radiologists were tasked with detection of stones, which were later characterized as uric acid or non-uric acid by using a commercial dual-energy CT analysis package. Stone size and contrast-to-noise ratio were additionally calculated. McNemar odds ratios and Cohen κ were calculated separately for all stones and small stones (≤ 3 mm). Results: One-hundred sixty renal stones (91 stones that were ≤ 3 mm in axial length) were visually detected. Compared with 1-mm-thick routine images from dual-energy CT, the odds of detecting a stone at PCD CT were 1.29 (95% confidence interval: 0.48, 3.45) for all stones. Stone segmentation and characterization were successful at PCD CT in 70.0% (112 of 160) of stones versus 54.4% (87 of 160) at dual-energy CT, and was superior for stones 3 mm or smaller at PCD CT (45 vs 25 stones, respectively; P =.002). Stone characterization agreement between scanners for stones of all sizes was substantial (κ = 0.65). Conclusion: Photon-counting-detector CT is similar to dual-energy CT for helping to detect renal stones and is better able to help characterize small renal stones.

AB - Purpose: To compare a research photon-counting-detector (PCD) CT scanner to a dual-source, dual-energy CT scanner for the detection and characterization of renal stones in human participants with known stones. Materials and Methods: Thirty study participants (median age, 61 years; 10 women) underwent a clinical renal stone characterization scan by using dual-energy CT and a subsequent research PCD CT scan by using the same radiation dose (as represented by volumetric CT dose index). Two radiologists were tasked with detection of stones, which were later characterized as uric acid or non-uric acid by using a commercial dual-energy CT analysis package. Stone size and contrast-to-noise ratio were additionally calculated. McNemar odds ratios and Cohen κ were calculated separately for all stones and small stones (≤ 3 mm). Results: One-hundred sixty renal stones (91 stones that were ≤ 3 mm in axial length) were visually detected. Compared with 1-mm-thick routine images from dual-energy CT, the odds of detecting a stone at PCD CT were 1.29 (95% confidence interval: 0.48, 3.45) for all stones. Stone segmentation and characterization were successful at PCD CT in 70.0% (112 of 160) of stones versus 54.4% (87 of 160) at dual-energy CT, and was superior for stones 3 mm or smaller at PCD CT (45 vs 25 stones, respectively; P =.002). Stone characterization agreement between scanners for stones of all sizes was substantial (κ = 0.65). Conclusion: Photon-counting-detector CT is similar to dual-energy CT for helping to detect renal stones and is better able to help characterize small renal stones.

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