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Genitourinary Imaging |
1 From the Departments of Radiology (F.V.C., J.K., Y.L., M.G.S.), Pathology (K.D.J.), and Urology (P.R.C.), University of California San Francisco, Box 0628, L-308, 505 Parnassus Ave, San Francisco, CA 94143-0628; Department of Radiology, University of British Columbia, Vancouver Hospital and Health Sciences Center, Vancouver, British Columbia, Canada (S.D.C.); and Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (H.H.). From the 2000 RSNA scientific assembly. Received March 7, 2001; revision requested April 12; final revision received September 26; accepted October 9. Supported by grants IRGICA76423-0IRI and P30 CA82103-01 from the National Institutes of Health. Address correspondence to F.V.C. (e-mail: fergus.coakley@radiology.ucsf.edu).
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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MATERIALS AND METHODS: Endorectal MR and 3D MR spectroscopic imaging were performed in 37 patients before radical prostatectomy. Two independent readers recorded peripheral zone tumor nodule location and volume. Results were analyzed with step-section histopathologic tumor localization and volume measurement as the standard. Accuracy of tumor volume measurement was assessed with the Pearson correlation coefficient. P values were calculated with a random effects model. Bland-Altman regression analysis was used to evaluate systematic bias between tumor volumes measured with MR imaging and true tumor volumes. Analyses were performed for all nodules and nodules greater than 0.50 cm3.
RESULTS: Mean volume of peripheral zone tumor nodules (n = 51) was 0.79 cm3 (range, 0.02–3.70 cm3). Two readers detected 20 (65%) and 23 (74%) of 31 peripheral zone tumor nodules greater than 0.50 cm3. For these nodules, measurements of tumor volume with MR imaging, 3D MR spectroscopic imaging, and a combination of both were all positively correlated with histopathologic volume (Pearson correlation coefficients of 0.49, 0.59, and 0.55, respectively); only measurements with 3D MR spectroscopic imaging and a combination of MR and 3D MR spectroscopic imaging demonstrated statistical significance (P < .05). Tumor volume estimation with all three methods was more accurate for higher tumor volumes.
CONCLUSION: Addition of 3D MR spectroscopic imaging to MR imaging increases overall accuracy of prostate cancer tumor volume measurement, although measurement variability limits consistent quantitative tumor volume estimation, particularly for small tumors.
© RSNA, 2002
Index terms: Magnetic resonance (MR), spectroscopy, three-dimensional, 844.12145 • Prostate neoplasms, 844.32 • Prostate neoplasms, MR, 844.121411, 844.12145
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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In one study (4), multivariate analysis showed that tumor volume, but not pathologic stage or baseline PSA level, was independently predictive of disease recurrence after radical prostatectomy. Such observations suggest that radiologic measurement of prostate cancer tumor volume might contribute to prediction of prognosis and provide information on tumor extent, in addition to the evaluation of extracapsular tumor extension. In clinical practice, we have noted an increasing demand from patients and referring physicians for measurement of tumor volume. However, previous studies (6–8) in which the measurement of prostate cancer tumor volume was examined by using magnetic resonance (MR) imaging have produced conflicting results, and in these studies, three-dimensional (3D) MR spectroscopic imaging was not used. We undertook this study to determine the accuracy of MR imaging and 3D MR spectroscopic imaging in the measurement of prostate cancer tumor volume.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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MR Imaging Technique
MR imaging was performed with a 1.5-T whole-body MR unit (Signa; GE Medical Systems, Milwaukee, Wis). The details of the MR imaging technique have been previously described (9,10). In brief, patients were examined in the supine position by using the body coil for excitation and a pelvic phased-array coil (GE Medical Systems) in combination with a commercially available balloon-covered expandable endorectal coil (Medrad, Pittsburgh, Pa) for signal reception.
Transverse spin-echo T1-weighted MR images were obtained from the aortic bifurcation to the symphysis pubis with the following parameters: repetition time msec/echo time msec, 700/8; section thickness, 5 mm; intersection gap, 1 mm; field of view, 24 cm; matrix, 256 x 192; frequency direction, transverse (to prevent obscuration of pelvic nodes caused by endorectal coil motion artifact); and excitation, one. Thin-section high-spatial-resolution transverse and coronal T2-weighted fast spin-echo images of the prostate and seminal vesicles were obtained with the following parameters: 5,000/96 (effective); echo train length, 16; section thickness, 3 mm; intersection gap, 0 mm; field of view, 14 cm; matrix, 256 x 192; frequency direction, anteroposterior (to prevent obscuration of the prostate caused by endorectal coil motion artifact); and excitations, three. All MR images were routinely postprocessed to compensate for the reception profile of the endorectal and pelvic phased-array coils (11).
After review of the transverse T2-weighted MR images, a spectroscopic imaging volume was selected to maximize coverage of the prostate and to minimize inclusion of periprostatic fat and rectal air. Three-dimensional MR spectroscopic imaging data were acquired by using a sequence with water and lipid suppressed double spin-echo point-resolved spatially localized spectroscopy, also known as PRESS, that was optimized for the quantitative detection of both choline and citrate (9). Water and lipid suppression was achieved by using band selective inversion with gradient dephasing, or BASING (12). Outer voxel saturation pulses were also used to eliminate susceptibility artifacts from periprostatic fat and rectal air (13). Data sets were acquired as 16 x 8 x 8 phase-encoded spectral arrays (1,024 voxels) with the following parameters: 1,000/130; nominal spectral resolution, 0.24–0.34 cm3; and acquisition time, 17 minutes. The total examination time was 1 hour and included coil placement and patient positioning.
Spectroscopic imaging data were overlaid on the corresponding transverse T2-weighted MR images and evaluated in consensus by two experienced spectroscopists (J.K., M.G.S.) to determine those voxels that were suitable for analysis. Voxels were considered suitable if they consisted of at least 75% peripheral zone tissue, did not include tissue surrounding the urethra or ejaculatory ducts, had a signal-to-noise ratio greater than 5:1, and were not spectrally contaminated by insufficient water or fat suppression. For each usable voxel, the ratio of choline plus creatine to citrate was calculated. Usable peripheral zone voxels with ratios of choline plus creatine to citrate that were 3 SDs greater than the normal mean value were considered to indicate malignancy and were designated "C" for cancer (9).
Usable voxels with a ratio of choline plus creatine to citrate that was 2 SDs greater than the normal mean value were considered to indicate a possible malignancy and were designated "P." These designations were marked on a grid overlaid on the corresponding transverse T2-weighted MR images. In addition, the spectral quality of each examination was subjectively rated as excellent, good, fair, or poor on the basis of signal-to-noise considerations, overall shim, and the presence of baseline distortions induced with water and lipid. Specifically, an examination was considered of excellent spectral quality if the signal-to-noise ratio of all metabolites was greater than 10, all metabolic resonances were well resolved, and there were no baseline distortions owing to residual water or lipid.
An examination was considered of good spectral quality if the signal-to-noise ratio of all metabolites was between eight and 10, all metabolic resonances were reasonably well resolved, or there were minimal baseline distortions owing to residual water or lipid. Examinations with lower signal-to-noise ratios were considered of fair spectral quality provided there was no lipid contamination. Examinations with substantial lipid contamination were considered to be of poor spectral quality. Because the spectroscopic imaging volume was constrained in size and position, the peripheral zone at the base was sometimes partially excluded. Therefore, the percentage of peripheral zone imaged by using 3D MR spectroscopic imaging was estimated by dividing the volume included by the total peripheral zone volume determined from the transverse T2-weighted MR images.
MR Image Interpretation
Two independent and experienced readers (F.V.C., S.D.C.) reviewed all MR images in conjunction with the 3D MR spectroscopic image overlays. Readers were aware that patients had prostate cancer but were unaware of all other clinical data. The overall quality of each MR image was subjectively classified as excellent, intermediate, or nondiagnostic. Image quality was considered excellent if visual examination of the images showed high spatial and contrast resolution and absence of artifacts. Image quality was considered nondiagnostic if poor resolution or extensive artifacts precluded meaningful assessment. All other images were considered to be of intermediate quality. The degree of postbiopsy hemorrhage in the prostate, recognized as irregular areas of increased signal intensity on T1-weighted images, was graded as none, mild (involvement of one or two sextants), moderate (involvement of three or four sextants), or severe (involvement of five or six sextants).
Readers identified peripheral zone tumor as focally reduced signal intensity on T2-weighted images or as a cluster of two or more voxels that were designated as possibly malignant or malignant or as both on spectroscopic images. In practice, MR imaging and 3D MR spectroscopic imaging are often synergistic with respect to tumor identification; for example, an equivocal MR imaging finding may be considered more or less suggestive of a malignant tumor because of the presence or absence of correlative 3D MR spectroscopic imaging findings, respectively. By using their best estimate of tumor location on the basis of a combination of MR imaging and 3D MR spectroscopic imaging findings, readers marked tumor location on a standardized diagram of the prostate. Because prostate cancer is often multifocal, more than one tumor location could be marked for each patient.
After detection and localization of suspected tumor nodules, readers estimated the volume of each recorded nodule by using three different measurement techniques: MR imaging, 3D MR spectroscopic imaging, and a combination of both.
MR imaging.—The area that was suspected of being tumor was outlined on T2-weighted images by using a picture archiving communication system workstation (Impax; Agfa-Gevaert, Mortsel, Belgium) free-form region-of-interest tool. The area was multiplied by the section thickness to calculate the volume for that section. The volumes for all sections were added to calculate the entire tumor volume.
Three-dimensional MR spectroscopic imaging.—The total number of contiguous possibly malignant and malignant voxels was counted and multiplied by the voxel size (0.17 cm3).
Combination of MR imaging and 3D MR spectroscopic imaging.—The total number of contiguous and concordant possibly malignant and malignant voxels was counted and multiplied by the voxel size. Concordant voxels were defined as 3D MR spectroscopic imaging voxels that demonstrated reduced T2 signal intensity on the corresponding area of the transverse T2-weighted MR image.
Not all three measurements were performed for every tumor nodule. For example, MR imaging volume could not be measured for nodules detected only by using spectroscopy. The difference between tumor detection and tumor volume estimation should also be noted; tumor detection was based on the global assessment of MR imaging and 3D MR spectroscopic imaging, whereas tumor volume was measured separately by using MR imaging, 3D MR spectroscopic imaging, and a combination of both.
Histopathologic Analysis
Specimens removed at radical prostatectomy were coated with India ink and fixed in 10% buffered formaldehyde. Transverse step sections were obtained at 3–4-mm intervals in a plane perpendicular to the long axis of the prostate. An experienced pathologist (K.D.J.) recorded the presence and grade of all tumor foci on a standardized diagram of the prostate. Tumor location was classified as peripheral zone or transition zone. Tumor nodules were outlined on the slides, and the cross-sectional area of tumor was measured on each slide. The cross-sectional area was multiplied by the section thickness to calculate the tumor volume for that interval. The volumes per interval were added to calculate the total tumor volume. A preliminary analysis of the first 10 specimens showed no difference in the pre- and postfixation weights of the specimens removed at prostatectomy, and therefore no correction factor was used to correct for tumor shrinkage during fixation. The presence of extracapsular extension and seminal vesicle invasion was also recorded.
Data Analysis
The unit of analysis was the peripheral zone tumor nodule. Both MR tumor detection and tumor volume estimation were analyzed. In the analysis of tumor detection, nodules marked on the schematic prostate diagram were compared with the true location of peripheral zone tumor on the pathologic tumor map and classified as true- or false-positive findings. Tumors detected with imaging were considered true-positive findings at pathologic correlation when tumor was present on the pathologic map within the same region that was considered tumorous at imaging. The effect of histopathologic tumor volume, PSA level, Gleason score, and postbiopsy hemorrhage on tumor detection was analyzed by using logistic regression analysis with generalized estimation equations to account for the clustering effects of multiple tumors in the same patient and for observations of two independent readers who were evaluating the same nodules (14).
The semiquantitative ratings of postbiopsy hemorrhage and spectroscopic quality were evaluated as covariates that might affect detection, by using logistic regression, and that might affect tumor volume estimation, by using a random effects model. In all these regression models, ordinal categorical variables were specified as categorical covariates, and linear contrasts were used to evaluate correlation trends. Spearman correlation coefficients were used whenever we evaluated the correlation to other variables.
For detected nodules, the accuracy of tumor volumes measured by using imaging was assessed by means of comparison with the true histopathologic tumor volume and by means of calculation of Pearson correlation coefficients. The bootstrap method was used to calculate 95% CIs (15). P values were calculated by using a random effects model, with the patient as the random effect and the readers as fixed effects, to account for clustering effects within patients and between readers. Bland-Altman regression analysis was used to evaluate systematic bias between MR tumor volumes and true tumor volumes and measurement agreement between the readers (16). Bland-Altman regression analysis is a statistical method for assessing agreement between two methods of clinical measurement. We used this technique to compare the means and SDs of tumor volumes estimated by different readers and measurement methods. With the analysis, regression of the differences in the measured tumor volumes was divided by the histopathologic tumor volume. A simultaneous zero interceptor and slope of this regression line suggest equal means and SDs of the measurements, whereas if either the interceptor or slope is significantly either greater or less than zero, either the mean or SD of the measured tumor volumes is significantly different from the histopathologic tumor volume. Measurement agreement between readers was evaluated by using the intraclass correlation coefficient with 95% bootstrap CIs.
The effect of histopathologic tumor volume, Gleason score, and postbiopsy hemorrhage on the accuracy of MR tumor volume measurements was assessed by using analysis of measurement error, defined as the difference between MR volume and histopathologic tumor volume expressed as a percentage of the histopathologic tumor volume. The relationship between these measurement errors and the covariates was evaluated by using the Spearman correlation coefficient and medians. Nonparametric methods were used because the measurement errors showed a substantial departure from the normal distribution. P values were derived by using the random effects model for the rank values of measurement errors.
The classification of detected small nodules as true-positive findings often caused problems, because the recorded tumor volume was sometimes much greater than the true tumor volume and also because we were sometimes less confident in the correct registration of smaller lesions between pathologic and imaging maps. Some of these cases, arguably, might have represented chance detection. Because of this concern, and because some authorities consider tumors less than 0.50 cm3 to be clinically unimportant (17), analyses of tumor detection and volume estimation were repeated for only those nodules with a histopathologic volume greater than 0.50 cm3. Statistical calculations were performed by using statistical software (SAS 7.0, SAS Institute, Cary, NC; S-plus, MathSoft, Seattle, Wash).
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Imaging Findings
All MR imaging studies were of excellent quality. Postbiopsy hemorrhage was present in 29 patients and was rated as mild, moderate, and severe in 10, 10, and nine patients, respectively. Three-dimensional MR spectroscopic images were rated as excellent, good, fair, and poor quality in 10, 14, nine, and four patients, respectively. The mean percentage of the peripheral zone included in the 3D MR spectroscopic imaging volume was 95% (range, 85%–100%).
Tumor detection.—The two readers detected 35 (69%) and 39 (76%) of the 51 tumor nodules in the peripheral zone, with 18 and 16 false-positive nodules, respectively. Reader 2 detected all true-positive nodules detected by reader 1, and the 
statistic for reader agreement was 0.64 (95% bootstrap CI: 0.45, 0.80). The two readers detected 20 (65%) and 23 (74%) of the 31 tumor nodules with a tumor volume greater than 0.50 cm3 in the peripheral zone. Tumor detection was unrelated to tumor volume, presence of postbiopsy hemorrhage, PSA level, or Gleason score. In particular, logistic regression analysis of all tumors in the peripheral zone showed that tumor detection was not significantly associated with histopathologic tumor volume (P = .49), hemorrhage (P = .71), PSA level (P = .54), or Gleason score (P = .47). Logistic regression analysis of tumors in the peripheral zone with a volume greater than 0.50 cm3 also showed that tumor detection was not significantly associated with histopathologic tumor volume (P = .43), hemorrhage (P = .08), PSA level (P = .92), or Gleason score (P > .99).
Tumor volume measurement.—The correlation coefficients between MR tumor volume measurements and histopathologic tumor volumes are shown in Table 1. For all tumor nodules, none of the three methods used to measure tumor volume showed a statistically significant correlation with histopathologic tumor volume. Bland-Altman regression analysis showed that with all methods, systematic overestimation of tumor volume occurred. For nodules greater than 0.50 cm3, tumor volume measurements with MR imaging, 3D MR spectroscopic imaging, and a combination of both were all positively correlated with histopathologic tumor volume (Pearson correlation coefficients of 0.49, 0.59, and 0.55, respectively), but only measurements with 3D MR spectroscopic imaging and a combination of MR imaging and 3D MR spectroscopic imaging demonstrated statistical significance (P < .05).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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value (0.64) for interobserver agreement on tumor detection and the high correlation between readers for tumor volume measurements (range, 0.55–0.93) indicate that the abnormalities demonstrated by using MR imaging and 3D MR spectroscopic imaging are relatively objective. However, undetected tumor nodules, false-positive results, and wide variation in accuracy of tumor volume measurement suggest there are still important inherent technical limitations in tumor depiction, in addition to observer variability. The ongoing evolution of MR imaging of the prostate and further refinement of spectroscopic criteria for malignancy that are based on findings in in vivo and in vitro studies may help overcome these obstacles. Pending further improvements in tumor depiction, quantitative tumor volume measurement cannot currently be performed with high confidence in patients who are considering prostatectomy, despite the clinical demand and theoretical appeal of noninvasive volumetric tumor assessment.
In this study, the addition of 3D MR spectroscopic imaging to MR imaging appeared to decrease interobserver agreement (Table 4), although a prior study (19) showed that the addition of 3D MR spectroscopic imaging to MR imaging increases the accuracy of tumor detection. This apparent discrepancy may be owing to statistical variation (the 95% CIs for both values overlap) or to differences in reader interpretation of concordant imaging and spectroscopic abnormalities. Readers may agree with respect to what is abnormal by using MR imaging and may also agree with respect to the number of abnormal 3D MR spectroscopic imaging voxels, but they may not agree with respect to which voxels are abnormal by using both MR imaging and spectroscopy. Only these later voxels were used to calculate tumor volume with the combination of MR imaging and MR spectroscopic imaging.
Our finding that tumor volume estimation is better at higher tumor volumes but that tumor detection is not related to tumor volume may appear contradictory. This apparent paradox is probably due to misclassification of recorded large tumors as true-positive tumors when they encompassed a very small pathologic tumor nodule. It is likely that such mismatched lesions represented false-positive results, where overlap between a large lesion indicated by a reader with a tiny real histopathologic nodule was coincidental. We did not use size concordance as an additional criterion for true-positive results, since this would have created a spurious correlation between measured and actual volumes. Instead, we analyzed our results separately for all tumor nodules versus results for nodules greater than 0.50 cm3 in histopathologic tumor volume.
The finding that tumor volume measurements for nodules greater than 0.50 cm3 were positively correlated with histopathologic tumor volume but that tumor volume measurements for all nodules were not correlated with histopathologic tumor volume supports the view that many apparently detected small tumor nodules represented chance detection. The finding that tumor volume estimation is better at higher tumor volumes is also important to any clinical application of tumor volume measurement. It could be argued that the interpreting radiologist does not know the tumor volume a priori and cannot provide any meaningful volumetric assessment because the estimated tumor volume might represent an inaccurate measurement of a small tumor or a false-positive result. However, in routine practice, clinical findings, PSA levels, and biopsy data are available and provide a sense of the likely tumor extent.
We are aware of three studies in which the measurement of prostate cancer tumor volume was performed by using MR imaging. An early study (6) of 31 nodules in 26 patients who were undergoing prostatectomy did not include documentation of a correlation coefficient but described large under- and overestimations of individual nodule volumes by using MR imaging with a body coil. Two later studies were performed by using an endorectal coil. A study (8) of 25 patients in Italy showed a high correlation between MR volume and histopathologic tumor volume (correlation coefficient, 0.94), whereas a study (7) of 34 patients in the Netherlands showed a very poor correlation. Our findings are similar to those in the latter study.
Two factors may explain these apparently conflicting results. The first is tumor size. The mean histopathologic tumor volume in the study in patients in Italy was 2.90 cm3 (8), which is approximately twice the mean volume in the study (7) in patients in the Netherlands and in those in our study (1.50 cm3 and 1.24 cm3, respectively). Mean PSA values and extracapsular extension rates were not uniformly reported in these studies and cannot be used for additional comparison. Our finding of more accurate tumor volume measurements at higher histopathologic tumor volumes also supports this explanation.
The second important factor that likely accounts for the discordance between these studies is the presence of postbiopsy hemorrhage. Postbiopsy hemorrhage is known to substantially reduce the accuracy of prostate cancer evaluation with MR imaging (20). It is noteworthy that in the study (8) in patients in Italy, all MR examinations were performed before biopsy, whereas in the study (7) in patients in the Netherlands, the examinations were performed at a mean interval of 3 weeks after biopsy. Although the presence of increased T1 signal intensity in the prostate alerts the radiologist to the presence of postbiopsy hemorrhage, it is possible that hemorrhage may be occult on T1-weighted images and may contribute to inaccurate tumor volume measurement.
This study has a number of limitations. As with prior studies (9–11) concerning the investigation of MR imaging and 3D MR spectroscopic imaging in prostate cancer, we only included tumors in the peripheral zone, because heterogeneity in the hyperplastic transition zone of older men limits tumor depiction. However, the majority of tumors are found in the peripheral zone, and 51 (88%) of 58 prostate cancer tumor nodules in this study were found in the peripheral zone. We did not examine the relationship between tumor volume and tumor stage, because too few patients had extracapsular extension (four of 37 patients) for meaningful statistical analysis. We did not explore the relationship between actual or measured tumor volume and outcome, because long-term follow-up data on the patients in the study were not available. We did not investigate the incremental benefit of MR spectroscopic imaging by separately reading images with and without the spectroscopic overlays, because we believe the incremental benefit of spectroscopy is established (19).
Our study has a clear selection bias to patients with low tumor volumes, because only patients who are considered likely to have organ-confined disease are considered candidates for prostatectomy at our institution. An additional factor that contributed to the selection bias toward low-stage disease is the general downward stage migration of prostate cancer in the era of widespread PSA level testing. The rate of organ-confined disease in patients who underwent prostatectomy and MR imaging at our institution between 1992 and 1995 was 56% (43 of 77 patients) (10), compared with 89% (33 of 37 patients) in this study, which was based on prostatectomies performed in 1999.
The same urologists (including P.R.C.) referred patients in both studies. It appears that patients with higher tumor volumes, in whom MR estimation of tumor volume is probably more accurate, are increasingly less likely to undergo surgery. This highlights a methodological problem for MR research in prostate cancer. Patient outcome may ultimately prove to be a better end point for studies of prostate MR imaging, particularly in nonsurgical cases. Finally, it should be noted that histopathologic findings are the best available standard of reference, but the findings are not perfect. Specimen preparation, slicing, and histologic analysis may all introduce bias or error in tumor volume measurement.
In conclusion, the addition of 3D MR spectroscopic imaging to MR imaging increases the overall accuracy of prostate cancer tumor volume measurement, although measurement variability limits consistent quantitative tumor volume estimation, particularly for small tumors. Pending further refinements in prostate cancer tumor volume measurement with MR imaging and 3D MR spectroscopic imaging, we believe it is currently inadvisable to report quantitative tumor volume estimations in patients with small tumors.
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FOOTNOTES |
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Author contributions: Guarantors of integrity of entire study, F.V.C., H.H.; study concepts, F.V.C., H.H.; study design, F.V.C., S.D.C.; literature research, F.V.C.; clinical studies, M.G.S., J.K., K.D.J., P.R.C.; data acquisition, F.V.C., S.D.C., Y.L.; data analysis/interpretation, Y.L.; statistical analysis, Y.L.; manuscript preparation, definition of intellectual content, editing, and revision/review, all authors; manuscript final version approval, F.V.C., H.H., P.R.C.
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J. J. Hom, F. V. Coakley, J. P. Simko, A. Qayyum, Y. Lu, L. Schmitt, P. R. Carroll, and J. Kurhanewicz Prostate Cancer: Endorectal MR Imaging and MR Spectroscopic Imaging--Distinction of True-Positive Results from Chance-detected Lesions Radiology, January 1, 2006; 238(1): 192 - 199. [Abstract] [Full Text] [PDF]
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A-L Grosu, M Piert, and M Molls Experience of PET for target localisation in radiation oncology Br. J. Radiol., November 1, 2005; Supplement_28(1): 18 - 32. [Full Text] [PDF]
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D. R. Aberle, C. Chiles, C. Gatsonis, B. J. Hillman, C. D. Johnson, B. L. McClennan, D. G. Mitchell, E. D. Pisano, M. D. Schnall, and A. G. Sorensen Imaging and Cancer: Research Strategy of the American College of Radiology Imaging Network Radiology, June 1, 2005; 235(3): 741 - 751. [Abstract] [Full Text] [PDF]
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B Cornelissen, V Kersemans, L Jans, L Staelens, R Oltenfreiter, T Thonissen, E Achten, and G Slegers Comparison between 1 T MRI and non-MRI based volumetry in inoculated tumours in mice Br. J. Radiol., April 1, 2005; 78(928): 338 - 342. [Abstract] [Full Text] [PDF]
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J. A. Jung, F. V. Coakley, D. B. Vigneron, M. G. Swanson, A. Qayyum, V. Weinberg, K. D. Jones, P. R. Carroll, and J. Kurhanewicz Prostate Depiction at Endorectal MR Spectroscopic Imaging: Investigation of a Standardized Evaluation System Radiology, December 1, 2004; 233(3): 701 - 708. [Abstract] [Full Text] [PDF]
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F. V. Coakley, H. S. Teh, A. Qayyum, M. G. Swanson, Y. Lu, M. Roach III, B. Pickett, K. Shinohara, D. B. Vigneron, and J. Kurhanewicz Endorectal MR Imaging and MR Spectroscopic Imaging for Locally Recurrent Prostate Cancer after External Beam Radiation Therapy: Preliminary Experience Radiology, November 1, 2004; 233(2): 441 - 448. [Abstract] [Full Text] [PDF]
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A. Qayyum, F. V. Coakley, Y. Lu, J. D. Olpin, L. Wu, B. M. Yeh, P. R. Carroll, and J. Kurhanewicz Organ-Confined Prostate Cancer: Effect of Prior Transrectal Biopsy on Endorectal MRI and MR Spectroscopic Imaging Am. J. Roentgenol., October 1, 2004; 183(4): 1079 - 1083. [Abstract] [Full Text] [PDF]
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A. Shukla-Dave, H. Hricak, S. C. Eberhardt, S. Olgac, M. Muruganandham, P. T. Scardino, V. E. Reuter, J. A. Koutcher, and K. L. Zakian Chronic Prostatitis: MR Imaging and 1H MR Spectroscopic Imaging Findings--Initial Observations Radiology, June 1, 2004; 231(3): 717 - 724. [Abstract] [Full Text] [PDF]
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R. Dhingsa, A. Qayyum, F. V. Coakley, Y. Lu, K. D. Jones, M. G. Swanson, P. R. Carroll, H. Hricak, and J. Kurhanewicz Prostate Cancer Localization with Endorectal MR Imaging and MR Spectroscopic Imaging: Effect of Clinical Data on Reader Accuracy Radiology, January 1, 2004; 230(1): 215 - 220. [Abstract] [Full Text] [PDF]
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