Faculty Bibliography

PURPOSE/OBJECTIVE:To determine the feasibility of texture analysis for the classification of liver cysts and hemangiomas, on nonenhanced, zero-fill interpolated T1- and T2-weighted MR images. MATERIALS AND METHODS/METHODS:Forty-five patients (26 women and 19 men; mean age, 58.1 +/- 16.9 years) with liver cysts or hemangiomas were enrolled in the study. After exclusion of images with artifacts, T1-weighted images of 42 patients, and T2-weighted images of 39 patients, obtained at 3.0 Tesla (T), were available for further analysis. Texture features derived from the gray-level histogram, co-occurrence and run-length matrix, gradient, autoregressive model, and wavelet transform were calculated. Fisher, probability of classification error and average correlation (POE+ACC), and mutual information coefficients were used to extract subsets of optimized texture features. Linear discriminant analysis (LDA) in combination with k nearest neighbor (k-NN) classification, and k-means clustering, were used for lesion classification. RESULTS:LDA/k-NN produced misclassification rates of 16-18% on T1-weighted, and 12-18% on T2-weighted images. K-means clustering yielded misclassification rates of 15-23% on T1-weighted, and 15-25% on T2-weighted images. CONCLUSION/CONCLUSIONS:Texture-based classification of liver cysts and hemangiomas is feasible on zero-fill interpolated MR images obtained at 3.0T. Further studies are warranted to investigate the value of texture-based classification of other liver lesions, such as hepatocellular and cholangiocellular carcinoma, on MRI.

BACKGROUND:To evaluate the prevalence and localization of abnormalities in the hallucal sesamoids detectable by magnetic resonance (MR) imaging in patients with forefoot pain and to determine which pathologies of tarsus, metatarsus and phalanges are associated with these abnormalities. MATERIALS AND METHODS/METHODS:The forefoot MRI examinations of 50 consecutive patients (32 females, 18 males; mean age 51 years, age range 20-86 years) were retrospectively analyzed by two musculoskeletal radiologists. A minimum of coronal and sagittal T1-weighted images and STIR images or T2-weighted images with fat saturation were performed on a 1.5-T scanner. Abnormal findings in the sesamoids were correlated with pathology in the I.MTP (metatarsal-phalangeal) joint, pathology in other parts of the forefoot and clinical information. RESULTS:Signal abnormalities of the sesamoids were found in 7 patients out of 50 (14%). Two patients presented a bone marrow edema (BME) in both sesamoids, in 1 patient only the lateral one was affected; all three associated with pathology and pain in the I.MTP joint. In four patients only the medial sesamoid was affected, not associated with pathology in the I.MTP joint but with pathology in other parts of the forefoot. CONCLUSION/CONCLUSIONS:The prevalence of signal abnormalities in hallucal sesamoids was 14%. BME of the lateral sesamoid or of both were predominantly associated with pathology in the I.MTP joint. In contrast, signal abnormalities of the medial sesamoid, without affection of the lateral one, were associated with pathology in other parts of the forefoot suggesting an overuse injury as a result of compensating posture.

PURPOSE/OBJECTIVE:The purpose was to investigate the in vivo effects of unloading and compression on T1-Gd relaxation times in healthy articular knee cartilage. MATERIALS AND METHODS/METHODS:Ten volunteers were enrolled, and dGEMRIC images of their right knee joints were obtained using 3.0-T MR at three timepoints: directly following exercise ("baseline"), approximately 15 min after unloading ("unloading") and during application of a compressive force (50% of the body weight) generated by a loading device via a footplate ("compression"). RESULTS:Our analysis of variance of pooled data from all cartilage zones demonstrated a significant mean T1-Gd decrease of 56.6 ms between baseline and compression (p < 0.001), and a significant mean decrease of 42.1 ms between unloading and compression (p < 0.001). No significant difference was found between baseline and unloading. Higher mean T1-Gd values were observed in the cartilage contact zone (central femoral and tibial zones; 698.3 +/- 162.2 ms) than in the non-contact zone (anterior and posterior femoral and tibial zones, and dorsal femoral zone; 662.9 +/- 149.3 ms; p < 0.01). CONCLUSION/CONCLUSIONS:T1-Gd times appear to be sensitive to mechanical cartilage stress, and thus, further studies are warranted that investigate the relationship between the biochemical load response and the biomechanical properties of articular cartilage.

OBJECTIVE:The purpose of this study was to assess the diagnostic value of PET/CT as a one step examination in patients with colorectal cancer. Therefore we proved whether diagnostic PET/CT adds information over PET or contrast-enhanced CT alone for staging or restaging of patients with colorectal cancer. METHODS:Seventy-three patients (46 males and 27 females; age range: 50-81 years; mean age: 67 years) with known colorectal cancer underwent 18F-FDG-PET/CT for staging or restaging. RESULTS:Of the 73 patients 26 patients underwent PET/CT for staging and 47 for restaging. 266 metastases could be detected in 60 patients. Contrast-enhanced PET/CT had a lesion-based sensitivity of 100%, contrast-enhanced CT of 91% and PET of 85%. PET/CT identified 2 lesions as false positive. PET/CT could also reach a patient-based sensitivity of 100%, which was superior to contrast-enhanced CT and PET. CONCLUSION/CONCLUSIONS:Our study clearly demonstrated the added value of contrast-enhanced PET/CT in staging and restaging patients with colorectal cancer over CT and PET alone.

OBJECTIVE(S)/OBJECTIVE:Only few information exist about the diagnostic accuracy of PET/CT for restaging patients with metastatic recurrence of breast carcinoma. Therefore, our study hypothesis was to perform diagnostic contrast enhanced CT (ce-CT) and FDG-PET in a one-step investigation, to prove sensitivity of each modality and to determine whether diagnostic PET/CT adds information over PET or contrast enhanced CT alone for restaging of patients with suspected recurrence of breast cancer. METHODS:Fifty-two patients with suspected recurrence of breast cancer were included in our study. All of them were free of metastasis after the first line therapy. Indications for restaging were: Elevated tumor markers n=32, clinical deterioration n=16 and/or suspicious findings on other imaging studies n=48. Integrated PET/CT was performed using contrast-enhanced diagnostic CT for attenuation correction. RESULTS:PET was correct in 44/52 patients (85%), ce-CT in 38/52 patients (73%) and PET/CT in 50/52 patients (96%). Sensitivity and specificity of lesion detection of PET, CT and PET/CT were 84%, 66% and 93%, and 100%, 92%, and 100%, respectively. DISCUSSION/CONCLUSIONS:PET/CT can improve staging and alter therapeutic options in patients suspected to have breast cancer recurrence and distant metastatic disease, primarily by demonstrating local or distant nodal involvement occult at other imaging studies. The added value of FDG-PET/CT over other diagnostic modalities is mainly expressed by the fact that a noninvasive whole-body evaluation is possible in a single examination.

OBJECTIVES/OBJECTIVE:To (1) determine whether magnetic resonance (MR) image interpolation at the pixel or k-space level can improve the results of texture-based pattern classification, and (2) compare the effects of image interpolation on texture features of different categories, with regard to their ability to distinguish between different patterns. MATERIALS AND METHODS/METHODS:We obtained T2-weighted, multislice multiecho MR images of 2 sets of each 3 polystyrene spheres and agar gel (PSAG) phantoms with different nodular patterns (sphere diameter: PSAG-1, 0.8-1.25 mm; PSAG-2, 1.25-2.0 mm; PSAG-3, 2.0-3.15 mm), using a 3.0 Tesla scanner equipped with a dedicated microimaging gradient insert. Image datasets, which consisted of 20 consecutive axial slices each, were obtained with a constant field of view (30 x 30 mm(2)), but with variations of matrix size (MTX): 16 x 16; 32 x 32; 64 x 64; 128 x 128; and 256 x 256. Original images were interpolated to higher matrix sizes (up to 256 x 256) by means of linear and cubic B-spline (pixel level) as well as zero-fill (k-space level) interpolation. For both original and interpolated image datasets, texture features derived from the co-occurrence (COC) and run-length matrix (RUN), absolute gradient (GRA), autoregressive model, and wavelet transform (WAV) were calculated independently. Based on the 3 best texture features of each category, as determined by calculation of Fisher coefficients using images from the first set of PSAG phantoms (training dataset), k-means clustering was performed to separate PSAG-1, PSAG-2, and PSAG-3 images belonging to the second set of phantoms (test dataset). This was done independently for all original and interpolated image datasets. Rates of misclassified data vectors were used as primary outcome measures. RESULTS:For images based on a very low original resolution (MTX = 16 x 16), misclassification rates remained high, despite the use of interpolation. For higher resolution images (MTX = 32 x 32 and 64 x 64), interpolation enhanced the ability of texture features, in all categories except WAV, to discriminate between the 3 phantoms. This positive effect was particularly pronounced for COC and RUN features, and to a lesser degree, also GRA features. No consistent improvements, and even some negative effects, were observed for WAV features, after interpolation. Although there was no clear superiority of any single interpolation techniques at very low resolution (MTX = 16 x 16), zero-fill interpolation outperformed the two pixel interpolation techniques, for images based on higher original resolutions (MTX = 32 x 32 and 64 x 64). We observed the most considerable improvements after interpolation by a factor of 2 or 4. CONCLUSIONS:MR image interpolation has the potential to improve the results of pattern classification, based on COC, RUN, and GRA features. Unless spatial resolution is very poor, zero-filling is the interpolation technique of choice, with a recommended maximum interpolation factor of 4.

MRI texture features are generally considered to be sensitive to variations in signal-to-noise ratio and spatial resolution, which represents an obstacle for the widespread clinical application of texture-based pattern discrimination with MRI. This study investigates the sensitivity of texture features of different categories (co-occurrence matrix, run-length matrix, absolute gradient, autoregressive model, and wavelet transform) to variations in the number of acquisitions (NAs), repetition time (TR), echo time (TE), and sampling bandwidth (SBW) at different spatial resolutions. Special emphasis was placed on the influence of MRI protocol heterogeneity and implications for the results of pattern discrimination. Experiments were performed using two polystyrene spheres and agar gel phantoms with different nodular patterns. T2-weighted multislice multiecho images were obtained using a 3.0 T scanner equipped with a microimaging gradient insert coil. Linear discriminant analysis and k nearest neighbor classification were used for texture-based pattern discrimination. Results show that texture features of all categories are increasingly sensitive to acquisition parameter variations with increasing spatial resolution. Nevertheless, as long as the spatial resolution is sufficiently high, variations in NA, TR, TE, and SBW have little effect on the results of pattern discrimination. Texture features derived from the co-occurrence matrix are superior to features of other categories because they enable discrimination of different patterns close to the resolution limits for the smallest structures of physical texture even for datasets that are heterogeneous with regard to different acquisition parameters, including spatial resolution.

OBJECTIVE:To establish, in patients with subacromial impingement syndrome, (1) the relationship between pain and shoulder function, as determined by the Constant score, and morphological findings, as determined by radiographs and magnetic resonance imaging (MRI) and (2) the relationship between acromial shape and minimum acromiohumeral distance (AHD). DESIGN/METHODS:Cross-sectional study. SETTING/METHODS:Tertiary care center. PATIENTS/METHODS:Forty-seven patients (33 males and 14 females; mean age, 51.7 years) with unilateral subacromial impingement syndrome who had failed to respond to conservative therapy for at least 6 months. INTERVENTIONS/METHODS:The Constant score was determined preoperatively; acromial shape (type I, flat; type II, curved; and type III, hooked) was evaluated on preoperative outlet view radiographs and oblique sagittal T1-weighted MRIs; AHD was evaluated on preoperative anteroposterior radiographs and oblique coronal T1-weighted MRIs. MAIN OUTCOME MEASURES/METHODS:Correlation coefficients and the simple kappa statistic were calculated. Student t test and mean differences with 95% confidence limits were reported for group comparisons. RESULTS:The Constant score was fairly correlated with AHD (r = 0.39, P < 0.01) but not with acromial shape. Patients with an AHD < or =7 mm on MRI scored significantly lower than those with an AHD >7 (mean difference, 18.5; P < 0.01). Acromial shape and AHD were not correlated, neither on radiographs nor on MRI. CONCLUSIONS:AHD seems to better reflect the clinical status of patients with subacromial impingement, but without rotator cuff tears, than acromial shape. Acromial shape is not a good descriptor of subacromial space narrowing.

OBJECTIVES/OBJECTIVE:To objectively identify possible differences in the signal characteristics of benign and malignant soft tissue masses (STM) on magnetic resonance (MR) images by means of texture analysis and to determine the value of these differences for computer-assisted lesion classification. METHOD/METHODS:Fifty-eight patients with histologically proven STM (benign, n=30; malignant, n=28) were included. STM texture was analyzed on routine T1-weighted, T2-weighted and short tau inversion recovery (STIR) images obtained with heterogeneous acquisition protocols. Fisher coefficients (F) and the probability of classification error and average correlation coefficients (POE+ACC) were calculated to identify the most discriminative texture features for separation of benign and malignant STM. F>1 indicated adequate discriminative power of texture features. Based on the texture features, computer-assisted classification of the STM by means of k-nearest-neighbor (k-NN) and artificial neural network (ANN) classification was performed, and accuracy, sensitivity and specificity were calculated. RESULTS:Discriminative power was only adequate for two texture features, derived from the gray-level histogram of the STIR images (first and 10th gray-level percentiles). Accordingly, the best results of STM classification were achieved using texture information from STIR images, with an accuracy of 75.0% (sensitivity, 71.4%; specificity, 78.3%) for the k-NN classifier, and an accuracy of 90.5% (sensitivity, 91.1%; specificity, 90.0%) for the ANN classifier. CONCLUSION/CONCLUSIONS:Texture analysis revealed only small differences in the signal characteristics of benign and malignant STM on routine MR images. Computer-assisted pattern recognition algorithms may aid in the characterization of STM, but more data is necessary to confirm their clinical value.

OBJECTIVE:To investigate the outcome of subchondral stress fractures (SSF) of the knee after treatment with the prostacyclin analogue Iloprost or the opioid analgesic Tramadol. DESIGN/METHODS:Case series/retrospective review. SETTING/METHODS:Tertiary care center. PATIENTS/METHODS:Fourteen patients with at least a single subchondral stress fracture of the knee, surrounded by bone marrow edema, visible on T1-weighted and short tau inversion recovery magnetic resonance images. INTERVENTIONS/METHODS:Nine patients had been treated with oral Iloprost (group 1; 11 SSF) and 5 patients with Tramadol (group 2; 5 SSF) for 4 weeks in the course of a double-blind, randomized clinical trial. MR images were obtained at baseline (1 day before the start of treatment), after 3 months, and after 1 year. MAIN OUTCOME VARIABLES/METHODS:SSF volumes and their rates of change between baseline and follow-up examinations, as determined on T1-weighted images by computer-assisted quantification. RESULTS:After three months, the SSF volumes had decreased by a median of 42.2% in group 1 and increased by a median of 2.2% in group 2 (P = 0.008). After 1 year, the median decrease in SSF volumes was 100.0% in group 1 and 65.7% in group 2 (P = 0.017). CONCLUSION/CONCLUSIONS:This small case series suggests that healing of SSF is more pronounced after Iloprost treatment.