Whole-body adipose tissue analysis: comparison of MRI, CT and dual energy X-ray absorptiometry.

The aim of this study was to validate a recently proposed MRI-based T(1)-mapping method for analysis of whole-body adipose tissue (AT) using an established CT protocol as reference and to include results from dual energy X-ray absorptiometry (DEXA). 10 subjects, drawn from the Swedish Obese Subjects Sibling-pairs study, were examined using CT, MRI and DEXA. The CT analysis was based on 28 imaged slices. T(1) maps were calculated using contiguous MRI data from two different gradient echo sequences acquired using different flip angles. CT and MRI comparison was performed slice-wise and for the whole-body region. Fat weights were compared between all three modalities. Strong correlations (r > or = 0.977, p<0.0001) were found between MRI and CT whole-body and AT volumes. MRI visceral AT volume was underestimated by 0.79 +/- 0.75 l (p = 0.005), but total AT was not significantly different from that estimated by CT (MRI - CT = -0.61+/-1.17 l; p = 0.114). DEXA underestimated fat weights by 5.23 +/- 1.71 kg (p = 0.005) compared with CT. MRI underestimated whole-body volume by 2.03 +/- 1.61 l (p = 0.005) compared with CT. Weights estimated either by CT or by DEXA were not significantly different from weights measured using scales. In conclusion, strong correlations were found between whole-body AT results from CT, MRI-based T(1) mapping and DEXA. If the differences between the results from T(1)-mapping and CT-based analysis are accepted, the T(1)-mapping method allows fully automated post-processing of whole-body MRI data, allowing longitudinal whole-body studies that are also applicable for children and adolescents.

Automated and reproducible segmentation of visceral and subcutaneous adipose tissue from abdominal MRI.

OBJECTIVES: (1) To develop a fully automated algorithm for segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT), excluding intermuscular adipose tissue (IMAT) and bone marrow (BM), from axial abdominal magnetic resonance imaging (MRI) data. (2) To evaluate the algorithm accuracy and total method reproducibility using a semi-automatically segmented reference and data from repeated measurements. BACKGROUND: MRI is a widely used in adipose tissue (AT) assessment. Manual analysis of MRI data is time consuming and biased by the operator. Automated analysis spares resources and increase reproducibility. Fully automated algorithms have been presented. However, reproducibility analysis has not been performed nor has methods for exclusion of IMAT and BM been presented. METHODS: In total, 49 data sets from 31 subjects were acquired using a clinical 1.5 T MRI scanner. Thirteen data sets were used in the derivation of the automated algorithm and 36 were used in the validation. Common image analysis tools such as thresholding, morphological operations and geometrical models were used to segment VAT and SAT. Accuracy was assessed using a semi-automatically created reference. Reproducibility was assessed from repeated measurements. RESULTS: Resulting AT volumes from the automated analysis and the reference were not found to differ significantly (2.0+/-14% and 0.84+/-2.7%, given as mean+/-s.d., for VAT and SAT, respectively). The automated analysis of the repeated measurements data significantly increased the reproducibility of the VAT measurements. One athletic subject with very small amounts of AT was considered to be an outlier. CONCLUSIONS: An automated method for segmentation of VAT and SAT and exclusion of IMAT and BM from abdominal MRI data has been reported. The accuracy and reproducibility of the method has also been demonstrated using a semi-automatically segmented reference and analysis of repeated acquisitions. The accuracy of the method is limited in lean subjects.

[Idiopathic orbital inflammatory syndrome (orbital pseudotumors): diagnosis and therapy]. / Idiopathische entzündliche intraorbitale Fibrosklerose: Diagnostik und therapeutische Möglichkeiten.

BACKGROUND: Pseudotumors of the orbit comprise a group of idiopathic inflammatory processes and are, except for endocrine orbitopathy, the most common reason for exophthalmos in adults. Orbital pseudotumors, also called idiopathic orbital inflammatory syndrome (IOIS), can be determined from orbital involvement in systemic fibrosing diseases. Finding the correct diagnosis can be challenging. Due to the topographic relations of the orbit to neighbouring structures, a multidisciplinary cooperation is highly recommended. CASE REPORT: We report a case of a 42-year-old woman with unilateral exophthalmos. Additionally we found impaired motility of the affected bulbus, ptosis and reduction of visual acuity. Orbital MR imaging demonstrated dense fibrotic masses filling the whole orbita including the extraocular muscles as well as the optic nerve. Tissue specimens were extracted while performing orbital decompression via a lateral orbitotomy. Histological examination revealed a lymphatic infiltration and fibrotically destroyed tissue containing the lacrimal gland. After surgical decompression, oral steroid therapy and immunotherapy, a recovery of the visual loss could be seen. CONCLUSIONS: Intraorbital fibrosclerosing pseudotumors often require a difficult long-term treatment. Therapeutic options are steroid therapy, immunotherapy, radiotherapy and surgery. The diagnostic steps include blood tests, ultrasound, CT and/or MRI as well as histological differentiation. Solid tumors and orbital involvement in diseases of the hematopoetic system have to be excluded. Since intraorbital fibrosis can be accompanied by manifestations in various other organs, a complete investigation of the body and thorough follow up are crucial.

Automatic registration and error detection of multiple slices using landmarks.

OBJECTIVES: When analysing the 3D structure of tissue, serial sectioning and staining of the resulting slices is sometimes the preferred option. This leads to severe registration problems. In this paper, a method for automatic registration and error detection of slices using landmark needles has been developed. A cost function takes some parameters from the current state of the problem to be solved as input and gives a quality of the current solution as output. The cost function used in this paper, is based on a model of the slices and the landmark needles. The method has been used to register slices of prostates in order to create 3D computer models. Manual registration of the same prostates has been undertaken and compared with the results from the algorithm. METHODS: Prostates from sixteen men who underwent radical prostatectomy were formalin fixed with landmark needles, sliced and the slices were computer reconstructed. The cost function takes rotation and translation for each prostate slice, as well as slope and offset for each landmark needle as input. The current quality of fit of the model, using the input parameters given, is returned. The function takes the built-in instability of the model into account. The method uses a standard algorithm to optimize the prostate slice positions. To verify the result, s standard method in statistics was used. RESULTS: The methods were evaluated for 16 prostates. When testing blindly, a physician could not determine whether the registration shown to him were created by the automated method described in this paper, or manually by an expert, except in one out of 16 cases. Visual inspection and analysis of the outlier confirmed that the input data had been deformed. The automatic detection of erroneous slices marked a few slices, including the outlier, as suspicious. CONCLUSIONS: The model based registration performs better than traditional simple slice-wise registration. In the case of prostate slice registration, other aspects, such as the physical slicing method used, may be more important to the final result than the selection of registration method to use.

Modeling prostate cancer distributions.

OBJECTIVES: To use computer-assisted three-dimensional (3D) reconstruction to study cancer distribution in the prostate. The distributions have been determined using data from 81 prostates surgically removed because of cancer. METHODS: The pattern of distribution was determined by reshaping (morphing) all prostates in the same size category (small, medium, large) into the same shape and by overlayering the 3D distribution of all cancers into a "unit prostate." Also, the pattern of 3D distribution was defined for small, medium, and large volume cancers. RESULTS: The study yielded a clear, visual "scatter diagram" representation of the statistics of prostate cancer distribution. It confirmed previous general knowledge: small cancers are mainly found in the lower one third and principally in the dorsolateral part of the gland. CONCLUSIONS: This report is part of the investigations preliminary to establishing an optimal protocol for needle biopsy of prostate cancer.

Biopsy protocol stability in a three-dimensional model of prostate cancer: changes in cancer yield after adjustment of biopsy positions.

OBJECTIVES: Transrectal ultrasound-guided prostate biopsies are often taken according to a systematic, standardized schedule. The diagnostic stability of this system was evaluated by moving the biopsies in a three-dimensional (3D) model. METHODS: A computerized 3D reconstruction was made from each of 75 radical prostatectomy specimens. Simulated core biopsies imitated a standardized 10-biopsy protocol, including sextant biopsies. In total, 30,000 biopsies were generated by moving the standardized biopsies 1, 2, 3, and 4 mm (parallel needle shifts) or 5 degrees, 10 degrees, 15 degrees, and 20 degrees(rotation of the needle tip) in a random direction. RESULTS: The diagnosis of the individual biopsy changed from cancer to benign or vice versa in 4.9% to 1 5.7% after 1 to 4-mm parallel needle shifts and 2.0% to 7.5% after 5 degrees to 20 degrees rotations. The corresponding figures for the final diagnosis of the 10-biopsy set were 0.8% to 9.6% and 0.5% to 3.2%. Transition zone biopsies containing cancer changed to benign more often than the other biopsies (P <0.001). Parallel needle shifts of 2 mm changed the diagnosis more often than the 15 degrees rotation (9.4% and 5.9%, respectively, P <0.001), although conveying the same overall needle shift. CONCLUSIONS: The cancer yield of prostate biopsies is influenced even by small changes in needle positions. The transition zone biopsies are most likely to change from cancer to benign when moved. Changing the insertion point of the needle has a higher impact on cancer yield than rotating the tip.

Three-dimensional computer reconstruction of prostate cancer from radical prostatectomy specimens: evaluation of the model by core biopsy simulation.

OBJECTIVES: A technique was developed for three-dimensional (3D) modeling of prostate cancer and transrectal biopsies. To test the model, the cancer yield of a simulated 10-biopsy protocol was compared with a simulated sextant protocol and with preoperative biopsies regarding cancer detection and correlation with tumor volume. METHODS: Transrectal ultrasound-guided core biopsies were taken from 81 men according to a standardized 10-biopsy protocol that included sextant biopsies. The patients underwent radical prostatectomy and specimens were step-sectioned and whole-mounted. Cancer and the prostate capsule were outlined on the slides and the regions transferred to a computer software program developed by our group. A 3D volume of each prostate was reconstructed from the sections. Virtual core biopsy needles imitating the positions of the real biopsies were inserted into the prostate and the cancer yield was calculated. Only the standardized positions were considered in this study (ie, additional biopsies from hypoechoic foci were not accounted for). RESULTS: Of the cancers detected with 10 standardized virtual biopsies, 24% would have remained undetected with sextant biopsies. The cancer yield of 10 virtual biopsies correlated with the preoperative biopsies (r = 0.64) and with the tumor volume (r = 0.56). A multiple regression analysis showed that the cancer yield of a simulation of 10 biopsies correlated better with tumor volume than did a simulation of sextant biopsies (P = 0.02). CONCLUSIONS: We conclude that computer-assisted 3D reconstruction of prostate cancer can be used as a model for evaluation and optimization of biopsy protocols.

Three-dimensional modeling of biopsy protocols for localized prostate cancer.

Prostate cancer is the most common malignant tumor in American men, yet only a small percentage of men will develop clinically significant disease. Needle core biopsies are used to confirm the presence of cancer prior to surgery. While needle core biopsies have shown some ability to predict tumor volume and grade in prostatectomy specimens, for the individual patient they are neither sensitive nor specific enough to guide therapy. In this paper, we describe a system for simulating needle biopsies on three-dimensional models of cancerous prostates reconstructed from serial sections. First we segment the serial sections, delineating tumors and landmarks. Next, we register the sections using a color-merging scheme, and reconstruct the three-dimensional model using modified-shape-based interpolation. The resulting volume can be rendered, and simulated needle core biopsies can be taken from the reconstructed model. We use our system to simulate two different biopsy protocols on a reconstructed prostate specimen.