Detection of prostate cancer with MR spectroscopic imaging: An expanded paradigm incorporating polyamines Journal Article

Authors: Shukla-Dave, A.; Hricak, H.; Moskowitz, C.; Ishill, N.; Akin, O.; Kuroiwa, K.; Spector, J.; Kumar, M.; Reuter, V. E.; Koutcher, J. A.; Zakian, K. L.
Article Title: Detection of prostate cancer with MR spectroscopic imaging: An expanded paradigm incorporating polyamines
Abstract: Purpose: To characterize benign and malignant prostate peripheral zone (PZ) tissue retrospectively by using a commercial magnetic resonance (MR) spectroscopic imaging package and incorporating the choline plus creatine-to-citrate ratio ([Cho + Cr]/Cit) and polyamine (PA) information into a statistically based voxel classification procedure. Materials and Methods: The institutional review board approved this HIPAA-compliant study and waived the requirement for informed consent. Fifty men (median age, 60 years; range, 44-69 years) with untreated biopsy-proved prostate cancer underwent combined endorectal MR imaging and MR spectroscopic imaging. Commercial software was used to acquire and process MR spectroscopic imaging data. The (Cho + Cr)/Cit and the PA level were tabulated for each voxel. The PA level was scored on a scale of 0 (PA undetectable) to 2 (PA peak as high as or higher than Cho peak). Whole-mount step-section histopathologic analysis constituted the reference standard. Classification and regression tree analysis in a training set generated a decision-making tree (rule) for classifying voxels as malignant or benign, which was validated in a test set. Receiver operating characteristic and generalized estimating equation regression analyses were used to assess accuracy and sensitivity, respectively. Results: The median (Cho + Cr)/Cit was 0.55 (mean ± standard deviation, 0.59 ± 0.03) in benign and 0.77 (mean, 1.08 ± 0.20) in malignant PZ voxels (P = .027). A significantly higher percentage of benign (compared with malignant) voxels had higher PA than choline peaks (P < .001). In the 24-patient training set (584 voxels), the rule yielded 54% sensitivity and 91% specificity for cancer detection; in the 26-patient test set (667 voxels), it yielded 42% sensitivity and 85% specificity. The percentage of cancer in the voxel at histopathologic analysis correlated positively (P < .001) with the sensitivity of the classification and regression tree rule, which was 75% in voxels with more than 90% malignancy. Conclusion: The statistically based classification rule developed indicated that PAs have an important role in the detection of PZ prostate cancer. With commercial software, this method can be applied in clinical settings. © RSNA, 2007.
Keywords: adult; clinical article; aged; middle aged; histopathology; validation process; nuclear magnetic resonance imaging; magnetic resonance imaging; diagnostic accuracy; sensitivity and specificity; reproducibility of results; classification; tumor markers, biological; tumor biopsy; algorithms; prostate cancer; prostatic neoplasms; standard; correlation analysis; diagnostic value; device; magnetic resonance spectroscopy; choline; citric acid; creatine; rating scale; regression analysis; decision making; data analysis software; proton nuclear magnetic resonance; digital imaging and communications in medicine; receiver operating characteristic; diagnosis, computer-assisted; calculation; mathematical analysis; polyamine; polyamines; airway conductance; choline plus creatine to citrate ratio
Journal Title: Radiology
Volume: 245
Issue: 2
ISSN: 0033-8419
Publisher: Radiological Society of North America, Inc.  
Date Published: 2007-11-01
Start Page: 499
End Page: 506
Language: English
DOI: 10.1148/radiol.2452062201
PUBMED: 17890357
PROVIDER: scopus
Notes: --- - "Cited By (since 1996): 35" - "Export Date: 17 November 2011" - "CODEN: RADLA" - "Source: Scopus"
Altmetric Score
MSK Authors
  1. Kentaro Kuroiwa
    28 Kuroiwa
  2. Mahesh Kumar
    1 Kumar
  3. Chaya S. Moskowitz
    173 Moskowitz
  4. Hedvig Hricak
    333 Hricak
  5. Amita Dave
    80 Dave
  6. Kristen L Zakian
    74 Zakian
  7. Jason A Koutcher
    236 Koutcher
  8. Victor Reuter
    922 Reuter
  9. Oguz Akin
    179 Akin
  10. Nicole Marie Leoce
    86 Leoce