Myotubularin-related-protein-7 inhibits mutant (G12V) K-RAS by direct interaction.

Inhibition of K-RAS effectors like B-RAF or MEK1/2 is accompanied by treatment resistance in cancer patients via re-activation of PI3K and Wnt signaling. We hypothesized that myotubularin-related-protein-7 (MTMR7), which inhibits PI3K and ERK1/2 signaling downstream of RAS, directly targets RAS and thereby prevents resistance. Using cell and structural biology combined with animal studies, we show that MTMR7 binds and inhibits RAS at cellular membranes. Overexpression of MTMR7 reduced RAS GTPase activities and protein levels, ERK1/2 phosphorylation, c-FOS transcription and cancer cell proliferation in vitro. We located the RAS-inhibitory activity of MTMR7 to its charged coiled coil (CC) region and demonstrate direct interaction with the gastrointestinal cancer-relevant K-RASG12V mutant, favouring its GDP-bound state. In mouse models of gastric and intestinal cancer, a cell-permeable MTMR7-CC mimicry peptide decreased tumour growth, Ki67 proliferation index and ERK1/2 nuclear positivity. Thus, MTMR7 mimicry peptide(s) could provide a novel strategy for targeting mutant K-RAS in cancers.

Long-term evaluation of uterine fibroid embolisation using MRI perfusion parameters and patient questionnaires: preliminary results.

BACKGROUND: Uterine fibroid embolisation (UFE) is an established treatment method for symptomatic uterine myomas. This study evaluates the efficacy of UFE using objective magnetic resonance imaging (MRI) data for size and perfusion analysis as well as patient questionnaires assessing fibroid-related symptoms. METHOD: Patients underwent MR-Angiography before UFE and 4 days, 6 and 12 months after the procedure. The images were evaluated using dedicated software. Patient questionnaires were completed before UFE and at 12 months follow-up, focussing on the embolization procedure and symptoms associated with uterine fibroids. Statistical analysis of the questionnaires was performed using paired sample t-test and Wilcoxon signed rank test, while Kruskal-Wallis test and Friedman test were applied for MRI-analysis. RESULTS: Eleven women were included. There was a significant reduction in fibroid-related symptoms. The volume reduction after 12 months was significant in both, uterus and myomas, after an initial increase in uterine volume at the first post-interventional MRI. The perfusion analysis showed that blood flow to the fibroids could be significantly reduced up to 12 months after UFE while uterine tissue was not affected. CONCLUSION: This study shows that uterine fibroid embolisation induces a significant long-term decrease in myoma size and perfusion while healthy uterine tissue remains unaffected. Fibroid-related symptoms are reduced for the sake of improved quality of life.

Are We There Yet? The Value of Deep Learning in a Multicenter Setting for Response Prediction of Locally Advanced Rectal Cancer to Neoadjuvant Chemoradiotherapy.

This retrospective study aims to evaluate the generalizability of a promising state-of-the-art multitask deep learning (DL) model for predicting the response of locally advanced rectal cancer (LARC) to neoadjuvant chemoradiotherapy (nCRT) using a multicenter dataset. To this end, we retrained and validated a Siamese network with two U-Nets joined at multiple layers using pre- and post-therapeutic T2-weighted (T2w), diffusion-weighted (DW) images and apparent diffusion coefficient (ADC) maps of 83 LARC patients acquired under study conditions at four different medical centers. To assess the predictive performance of the model, the trained network was then applied to an external clinical routine dataset of 46 LARC patients imaged without study conditions. The training and test datasets differed significantly in terms of their composition, e.g., T-/N-staging, the time interval between initial staging/nCRT/re-staging and surgery, as well as with respect to acquisition parameters, such as resolution, echo/repetition time, flip angle and field strength. We found that even after dedicated data pre-processing, the predictive performance dropped significantly in this multicenter setting compared to a previously published single- or two-center setting. Testing the network on the external clinical routine dataset yielded an area under the receiver operating characteristic curve of 0.54 (95% confidence interval [CI]: 0.41, 0.65), when using only pre- and post-therapeutic T2w images as input, and 0.60 (95% CI: 0.48, 0.71), when using the combination of pre- and post-therapeutic T2w, DW images, and ADC maps as input. Our study highlights the importance of data quality and harmonization in clinical trials using machine learning. Only in a joint, cross-center effort, involving a multidisciplinary team can we generate large enough curated and annotated datasets and develop the necessary pre-processing pipelines for data harmonization to successfully apply DL models clinically.

Development of an abdominal phantom for the validation of an oligometastatic disease diagnosis workflow.

PURPOSE: The liver is a common site for metastatic disease, which is a challenging and life-threatening condition with a grim prognosis and outcome. We propose a standardized workflow for the diagnosis of oligometastatic disease (OMD), as a gold standard workflow has not been established yet. The envisioned workflow comprises the acquisition of a multimodal image data set, novel image processing techniques, and cone beam computed tomography (CBCT)-guided biopsy for subsequent molecular subtyping. By combining morphological, molecular, and functional information about the tumor, a patient-specific treatment planning is possible. We designed and manufactured an abdominal liver phantom that we used to demonstrate multimodal image acquisition, image processing, and biopsy of the OMD diagnosis workflow. METHODS: The anthropomorphic abdominal phantom contains a rib cage, a portal vein, lungs, a liver with six lesions, and a hepatic vessel tree. This phantom incorporates three different lesion types with varying visibility under computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography CT (PET-CT), which reflects clinical reality. The phantom is puncturable and the size of the corpus and the organs is comparable to those of a real human abdomen. By using several modern additive manufacturing techniques, the manufacturing process is reproducible and allows to incorporate patient-specific anatomies. As a first step of the OMD diagnosis workflow, a preinterventional CT, MRI, and PET-CT data set of the phantom was acquired. The image information was fused using image registration and organ information was extracted via image segmentation. A CBCT-guided needle puncture experiment was performed, where all six liver lesions were punctured with coaxial biopsy needles. RESULTS: Qualitative observation of the image data and quantitative evaluation using contrast-to-noise ratio (CNR) confirms that one lesion type is visible only in MRI and not CT. The other two lesion types are visible in CT and MRI. The CBCT-guided needle placement was performed for all six lesions, including those visible only in MRI and not CBCT. This was possible by successfully merging multimodal preinterventional image data. Lungs, bones, and liver vessels serve as realistic inhibitions during needle path planning. CONCLUSIONS: We have developed a reusable abdominal phantom that has been used to validate a standardized OMD diagnosis workflow. Utilizing the phantom, we have been able to show that a multimodal imaging pipeline is advantageous for a comprehensive detection of liver lesions. In a CBCT-guided needle placement experiment we have punctured lesions that are invisible in CBCT using registered preinterventional MRI scans for needle path planning.

Feature-based CBCT self-calibration for arbitrary trajectories.

PURPOSE: Development of an algorithm to self-calibrate arbitrary CBCT trajectories which can be used to reduce metal artifacts. By using feature detection and matching we want to reduce the amount of parameters for the BFGS optimization and thus reduce the runtime. METHODS: Each projection is 2D-3D registered on a prior image with AKAZE feature detection and brute force matching. Translational misalignment is calculated directly from the misalignment of feature positions, rotations are aligned using a minimization algorithm that fits a quartic function and determines the minimum of this function. EVALUATION: We did three experiments to compare how well the algorithm can handle noise on the different degrees of freedom. Our algorithms are compared to Broyden-Fletcher-Goldfarb-Shanno (BFGS) minimizer with Normalized Gradient Information (NGI) objective function, and BFGS with distance between features objective function using SSIM, nRMSE, and the Dice coefficient of segmented metal object. RESULTS: Our algorithm (Feature ORiented Calibration for Arbitrary Scan Trajectories with Enhanced Reliability (FORCASTER)) performs on par with the state-of-the-art algorithms (BFGS with NGI objective). nRMSE: FORCASTER = 0.3390, BFGS+NGI = 0.3441; SSIM: FORCASTER = 0.83, BFGS + NGI = 0.79; Dice: FORCASTER = 0.86, BFGS + NGI = 0.87. CONCLUSION: The proposed algorithm can determine the parameters of the projection orientations for arbitrary trajectories with calibration quality comparable to state-of-the-art algorithms, but faster and with higher tolerance to errors in the initially guessed parameters.

An anthropomorphic pelvis phantom for MR-guided prostate interventions.

PURPOSE: To design and manufacture a pelvis phantom for magnetic resonance (MR)-guided prostate interventions, such as MRGB (MR-guided biopsy) or brachytherapy seed placement. METHODS: The phantom was designed to mimic the human pelvis incorporating bones, bladder, prostate with four lesions, urethra, arteries, veins, and six lymph nodes embedded in ballistic gelatin. A hollow rectum enables transrectal access to the prostate. To demonstrate the feasibility of the phantom for minimal invasive MRI-guided interventions, a targeted inbore MRGB was performed. The needle probe was rectally inserted and guided using an MRI-compatible remote controlled manipulator (RCM). RESULTS: The presented pelvis phantom has realistic imaging properties for MR imaging (MRI), computed tomography (CT) and ultrasound (US). In the targeted inbore MRGB, a prostate lesion was successfully hit with an accuracy of 3.5 mm. The experiment demonstrates that the limited size of the rectum represents a realistic impairment for needle placements. CONCLUSION: The phantom provides a valuable platform for evaluating the performance of MRGB systems. Interventionalists can use the phantom to learn how to deal with challenging situations, without risking harm to patients.

[MRI-guided minimally invasive treatment of prostate cancer]. / MRT-gestützte minimal-invasive Therapie des Prostatakarzinoms.

CLINICAL/METHODOLOGICAL ISSUE: Multiparametric magnetic resonance imaging (mpMRI) of the prostate plays a crucial role in the diagnosis and local staging of primary prostate cancer. STANDARD RADIOLOGICAL METHODS: Image-guided biopsy techniques such as MRI-ultrasound fusion not only allow guidance for targeted tissue sampling of index lesions for diagnostic confirmation, but also improve the detection of clinically significant prostate cancer. METHODOLOGICAL INNOVATIONS: Minimally invasive, focal therapies of localized prostate cancer complement the treatment spectrum, especially for low- and intermediate-risk patients. PERFORMANCE: In patients of low and intermediate risk, MR-guided, minimally invasive therapies could enable local tumor control, improved functional outcomes and possible subsequent therapy escalation. Further study results related to multimodal approaches and the application of artificial intelligence (AI) by machine and deep learning algorithms will help to leverage the full potential of focal therapies for prostate cancer in the upcoming era of precision medicine. ACHIEVEMENTS: Completion of ongoing randomized trials comparing each minimally invasive therapy approach with established whole-gland procedures is needed before minimally invasive therapies can be implemented into existing treatment guidelines. PRACTICAL RECOMMENDATIONS: This review article highlights minimally invasive therapies of prostate cancer and the key role of mpMRI for planning and conducting these therapies.

A Modified Surgical Model of Hind Limb Ischemia in ApoE-/- Mice using a Miniature Incision.

The purpose of this study is to introduce and evaluate a modified surgical approach to induce acute ischemia in mice that can be implemented in most animal laboratories. Contrary to the conventional approach for double ligation of the femoral artery (DLFA), a smaller incision on the right inguinal region was made to expose the proximal femoral artery (FA) to perform DLFA. Then, using a 7-0 suture, the incision was dragged to the knee region to expose the distal FA. Magnetic resonance imaging (MRI) on bilateral hind limbs was used to detect FA occlusion after the surgery. At 0, 1, 3, 5, and 7 days after the surgery, functional recovery of the hind limbs was visually assessed and graded using the Tarlov scale. Histologic evaluation was performed after euthanizing the animals 7 days after DLFA. The procedures were successfully performed on the right leg in ten ApoE-/- mice, and no mice died during subsequent observation. The incision sizes in all 10 mice were less than 5 mm (4.2 ± 0.63 mm). MRI results showed that FA blood flow in the ischemic side was clearly blocked. The Tarlov scale results demonstrated that hind limb function significantly decreased after the procedure and slowly recovered over the following 7 days. Histologic evaluation showed a significant inflammatory response on the ischemic side and reduced microvascular density in the ischemic hind limb. In conclusion, this study introduces a modified technique using a miniature incision to perform hind limb ischemia (HLI) using DLFA.

Generation of annotated multimodal ground truth datasets for abdominal medical image registration.

PURPOSE: Sparsity of annotated data is a major limitation in medical image processing tasks such as registration. Registered multimodal image data are essential for the diagnosis of medical conditions and the success of interventional medical procedures. To overcome the shortage of data, we present a method that allows the generation of annotated multimodal 4D datasets. METHODS: We use a CycleGAN network architecture to generate multimodal synthetic data from the 4D extended cardiac-torso (XCAT) phantom and real patient data. Organ masks are provided by the XCAT phantom; therefore, the generated dataset can serve as ground truth for image segmentation and registration. Realistic simulation of respiration and heartbeat is possible within the XCAT framework. To underline the usability as a registration ground truth, a proof of principle registration is performed. RESULTS: Compared to real patient data, the synthetic data showed good agreement regarding the image voxel intensity distribution and the noise characteristics. The generated T1-weighted magnetic resonance imaging, computed tomography (CT), and cone beam CT images are inherently co-registered. Thus, the synthetic dataset allowed us to optimize registration parameters of a multimodal non-rigid registration, utilizing liver organ masks for evaluation. CONCLUSION: Our proposed framework provides not only annotated but also multimodal synthetic data which can serve as a ground truth for various tasks in medical imaging processing. We demonstrated the applicability of synthetic data for the development of multimodal medical image registration algorithms.

Impact of Chronic Prostatitis on the PI-RADS Score 3: Proposal for the Addition of a Novel Binary Suffix.

We examined the impact of chronic prostatitis on the diagnostic performance of multiparametric magnetic resonance imaging (mpMRI). In this retrospective study, 63 men underwent 3T mpMRI followed by MRI/ultrasound fusion biopsy to exclude/confirm clinically significant prostate cancer (csPCa). A total of 93 lesions were included for evaluation. Images were assessed by two radiologists. Prostatitis was graded visually on T2-weighted and contrast-enhanced sequences. The correlation of prostatitis features with the assigned Prostate Imaging Reporting and Data System (PI-RADS) and the presence of csPCa were assessed, and the clinical and functional imaging parameters for differentiating between prostatitis and significant tumors were examined. Histopathological analysis was used as the reference standard. The rate of PI-RADS 3 scores tended to be higher in the presence of radiologically severe prostatitis compared with no/discrete prostatitis (n = 52 vs. n = 9; p = 0.225). In severe prostatitis, csPCa was determined in only 7.7% (4/52) of PI-RADS 3 lesions. In severe chronic prostatitis, a binary prostatitis suffix (e.g., PI-RADS 3 i+ versus i-) within the radiological report may help assess the limitations of mpMRI interpretability because of severe prostatitis and avoid unnecessary biopsies. Mean apparent diffusion coefficient (ADCmean) was the best marker (cutoff 0.93 × 10-3 mm2/s) to differentiate between csPCa/non csPCa in severe prostatitis.

Synthesis of CT images from digital body phantoms using CycleGAN.

PURPOSE: The potential of medical image analysis with neural networks is limited by the restricted availability of extensive data sets. The incorporation of synthetic training data is one approach to bypass this shortcoming, as synthetic data offer accurate annotations and unlimited data size. METHODS: We evaluated eleven CycleGAN for the synthesis of computed tomography (CT) images based on XCAT body phantoms. The image quality was assessed in terms of anatomical accuracy and realistic noise properties. We performed two studies exploring various network and training configurations as well as a task-based adaption of the corresponding loss function. RESULTS: The CycleGAN using the Res-Net architecture and three XCAT input slices achieved the best overall performance in the configuration study. In the task-based study, the anatomical accuracy of the generated synthetic CTs remained high ([Formula: see text] and [Formula: see text]). At the same time, the generated noise texture was close to real data with a noise power spectrum correlation coefficient of [Formula: see text]. Simultaneously, we observed an improvement in annotation accuracy of 65% when using the dedicated loss function. The feasibility of a combined training on both real and synthetic data was demonstrated in a blood vessel segmentation task (dice similarity coefficient [Formula: see text]). CONCLUSION: CT synthesis using CycleGAN is a feasible approach to generate realistic images from simulated XCAT phantoms. Synthetic CTs generated with a task-based loss function can be used in addition to real data to improve the performance of segmentation networks.

Feasibility of quantitative MR-perfusion imaging to monitor treatment response after uterine artery embolization (UAE) in symptomatic uterus fibroids.

INTRODUCTION: In 25% of women, symptomatic uterus myomas are diagnosed with clinical and functional impairment ranging from abdominal and pelvic pain to dys- and hypermenorrhea, dyspareunia, pollakiuria and infertility. Women undergoing a treatment increasingly prefer nowadays minimal invasive, uterus preserving therapies like uterine artery embolization (UAE) over surgical hysterectomy, nowadays. To emphasize the efficacy of UAE as a uterus preserving treatment with targeted therapy of myomas only, analysis of tissue perfusion pre and post embolization is required. The purpose of this study was to assess treatment response in UAE in females with symptomatic uterus myomas by quantitative magnetic resonance perfusion imaging. METHODS: Seven females scheduled for uterus myoma embolization underwent three MRI examinations (pre, post, follow-up) including morphological and dynamic contrast enhanced perfusion imaging at 3 T. To measure tumor volume, regions-of-interest covering the tumor and the uterus were drawn by two readers in consensus. Blood flow, blood volume, and mean transit time were calculated by a pixel-by-pixel deconvolution approach. Kruskal-Wallis/Friedman test was employed to test whether the group medians differ significantly with correction for multiple comparisons using Bonferroni method. RESULTS: Change of volume could be observed in all patients after embolization but was significantly different only between pre/post and follow-up time point. Measured differences in all perfusion parameters were significant between pre-intervention and post-intervention/follow-up in the myomas, no significant differences could be detected for the uterus tissue. CONCLUSIONS: Our results demonstrate devascularization of symptomatic myomas which correlates with cessation of hypermenorrhea in all treated patients without affecting healthy uterus tissue. Supplementing UAE with perfusion imaging to monitor early treatment response is feasible and might provide valuable information for the follow-up of patients and contribute to providing confidence for the patients in treatment success.

Correction to: Tomosynthesis implementation with adaptive online calibration on clinical C-arm systems.

The original version of this article unfortunately contained a mistake in table 2.

Tomosynthesis implementation with adaptive online calibration on clinical C-arm systems.

PURPOSE: Cone beam computed tomography (CBCT) systems offer physicians crucial 3D and 2D imaging capabilities during interventions. However, certain medical applications only require very specific information from the CBCTs (e.g., determination of the position of high-contrast objects). In diagnostics, tomosynthesis techniques can be used in these cases to minimize dose exposure. Therefore, integrating such techniques on CBCT systems could also be beneficial for interventions. In this paper, we investigate the performance of our implementation of circular tomosynthesis on a CBCT device. METHODS: The tomosynthesis scan trajectory is realized with step-and-shoot on a clinical C-arm device. The online calibration algorithm uses conventionally acquired 3D CBCT of the scanned object as prior knowledge to correct the imaging geometries. The online calibration algorithm was compared to an offline calibration to test its performance. A ball bearing phantom was used to evaluate the reconstructions with respect to geometric distortions. The evaluation was done for three different scenarios to test the robustness of our tomosynthesis implementation against object deviations (e.g., pen) and different object positioning. RESULTS: The circular tomosynthesis was tested on a ball bearing and an anthropomorphic phantom. The results show that the calibration is robust against isocenter shifts and object deviations in the CBCT. All reconstructions used 100 projections and displayed limited angle artifacts. The accuracy of the positions and shapes of high-contrast objects were, however, determined precisely. (The maximal center position deviation is 0.31 mm.) CONCLUSION: For medical procedures that primarily determine the precise position of high-contrast objects, circular tomosynthesis could offer an approach to reduce dose exposure.

Comparison of perfusion models for quantitative T1 weighted DCE-MRI of rectal cancer.

In this work, the two compartment exchange model and two compartment uptake model were applied to obtain quantitative perfusion parameters in rectum carcinoma and the results were compared to those obtained by the deconvolution algorithm. Eighteen patients with newly diagnosed rectal carcinoma underwent 3 T MRI of the pelvis including a T1 weighted dynamic contrastenhanced (DCE) protocol before treatment. Mean values for Plasma Flow (PF), Plasma Volume (PV) and Mean Transit Time (MTT) were obtained for all three approaches and visualized in parameter cards. For the two compartment models, Akaike Information Criterion (AIC) and [Formula: see text] were calculated. Perfusion parameters determined with the compartment models show results in accordance with previous studies focusing on rectal cancer DCE-CT (PF2CX = 68 ± 44 ml/100 ml/min, PF2CU = 55 ± 36 ml/100 ml/min) with similar fit quality (AIC:169 ± 81/179 ± 77, [Formula: see text]:10 ± 12/9 ± 10). Values for PF are overestimated whereas PV and MTT are underestimated compared to results of the deconvolution algorithm. Significant differences were found among all models for perfusion parameters as well as between the AIC and [Formula: see text] values. Quantitative perfusion parameters are dependent on the chosen tracer kinetic model. According to the obtained parameters, all approaches seem capable of providing quantitative perfusion values in DCE-MRI of rectal cancer.

Diffusion-weighted MR imaging of pancreatic cancer: A comparison of mono-exponential, bi-exponential and non-Gaussian kurtosis models.

OBJECTIVES: To compare two Gaussian diffusion-weighted MRI (DWI) models including mono-exponential and bi-exponential, with the non-Gaussian kurtosis model in patients with pancreatic ductal adenocarcinoma. MATERIALS AND METHODS: After written informed consent, 15 consecutive patients with pancreatic ductal adenocarcinoma underwent free-breathing DWI (1.5T, b-values: 0, 50, 150, 200, 300, 600 and 1000 s/mm2). Mean values of DWI-derived metrics ADC, D, D*, f, K and DK were calculated from multiple regions of interest in all tumours and non-tumorous parenchyma and compared. Area under the curve was determined for all metrics. RESULTS: Mean ADC and DK showed significant differences between tumours and non-tumorous parenchyma (both P < 0.001). Area under the curve for ADC, D, D*, f, K, and DK were 0.77, 0.52, 0.53, 0.62, 0.42, and 0.84, respectively. CONCLUSION: ADC and DK could differentiate tumours from non-tumorous parenchyma with the latter showing a higher diagnostic accuracy. Correction for kurtosis effects has the potential to increase the diagnostic accuracy of DWI in patients with pancreatic ductal adenocarcinoma.

An open source software for analysis of dynamic contrast enhanced magnetic resonance images: UMMPerfusion revisited.

BACKGROUND: Perfusion imaging has become an important image based tool to derive the physiological information in various applications, like tumor diagnostics and therapy, stroke, (cardio-) vascular diseases, or functional assessment of organs. However, even after 20 years of intense research in this field, perfusion imaging still remains a research tool without a broad clinical usage. One problem is the lack of standardization in technical aspects which have to be considered for successful quantitative evaluation; the second problem is a lack of tools that allow a direct integration into the diagnostic workflow in radiology. RESULTS: Five compartment models, namely, a one compartment model (1CP), a two compartment exchange (2CXM), a two compartment uptake model (2CUM), a two compartment filtration model (2FM) and eventually the extended Toft's model (ETM) were implemented as plugin for the DICOM workstation OsiriX. Moreover, the plugin has a clean graphical user interface and provides means for quality management during the perfusion data analysis. Based on reference test data, the implementation was validated against a reference implementation. No differences were found in the calculated parameters. CONCLUSION: We developed open source software to analyse DCE-MRI perfusion data. The software is designed as plugin for the DICOM Workstation OsiriX. It features a clean GUI and provides a simple workflow for data analysis while it could also be seen as a toolbox providing an implementation of several recent compartment models to be applied in research tasks. Integration into the infrastructure of a radiology department is given via OsiriX. Results can be saved automatically and reports generated automatically during data analysis ensure certain quality control.

Quantitative sodium MRI of kidney.

One of the main tasks of the human kidneys is to maintain the homeostasis of the body's fluid and electrolyte balance by filtration of the plasma and excretion of the end products. Herein, the regulation of extracellular sodium in the kidney is of particular importance. Sodium MRI ((23)Na MRI) allows for the absolute quantification of the tissue sodium concentration (TSC) and thereby provides a direct link between TSC and tissue viability. Renal (23)Na MRI can provide new insights into physiological tissue function and viability thought to differ from the information obtained by standard (1)H MRI. Sodium imaging has the potential to become an independent surrogate biomarker not only for renal imaging, but also for oncology indications. However, this technique is now on the threshold of clinical implementation. Numerous, initial pre-clinical and clinical studies have already outlined the potential of this technique; however, future studies need to be extended to larger patient groups to show the diagnostic outcome. In conclusion, (23)Na MRI is seen as a powerful technique with the option to establish a non-invasive renal biomarker for tissue viability, but is still a long way from real clinical implementation.

Non-invasive quantitative pulmonary V/Q imaging using Fourier decomposition MRI at 1.5T.

OBJECTIVES: Techniques for quantitative pulmonary perfusion and ventilation using the Fourier Decomposition method were recently demonstrated. We combine these two techniques and show that ventilation-perfusion (V/Q) imaging is possible using only a single MR acquisition of less than thirty seconds. METHODS: The Fourier Decomposition method is used in combination with two quantification techniques, which extract baselines from within the images themselves and thus allows quantification. For the perfusion, a region assumed to consist of 100% blood is utilized, while for the ventilation the zero-frequency component is used. V/Q-imaging is then done by dividing the quantified ventilation map with the quantified perfusion map. The techniques were used on ten healthy volunteers and fifteen patients diagnosed with lung cancer. RESULTS: A mean V/Q-ratio of 1.15 ± 0.22 was found for the healthy volunteers and a mean V/Q-ratio of 1.93 ± 0.83 for the non-afflicted lung in the patients. Mean V/Q-ratio in the afflicted (tumor-bearing) lung was found to be 1.61 ± 1.06. Functional defects were clearly visible in many of the patient images, but 5 of 15 patient images had to be excluded due to artifacts or low SNR, indicating a lack of robustness. CONCLUSION: Non-invasive, quantitative V/Q-imaging is possible using Fourier Decomposition MRI. The method requires only a single acquisition of less than 30 seconds, but robustness in patients remains an issue.

A generic support vector machine model for preoperative glioma survival associations.

PURPOSE: To develop a generic support vector machine (SVM) model by using magnetic resonance (MR) imaging-based blood volume distribution data for preoperative glioma survival associations and to prospectively evaluate the diagnostic effectiveness of this model in autonomous patient data. MATERIALS AND METHODS: Institutional and regional medical ethics committees approved the study, and all patients signed a consent form. Two hundred thirty-five preoperative adult patients from two institutions with a subsequent histologically confirmed diagnosis of glioma after surgery were included retrospectively. An SVM learning technique was applied to MR imaging-based whole-tumor relative cerebral blood volume (rCBV) histograms. SVM models with the highest diagnostic accuracy for 6-month and 1-, 2-, and 3-year survival associations were trained on 101 patients from the first institution. With Cox survival analysis, the diagnostic effectiveness of the SVM models was tested on independent data from 134 patients at the second institution. RESULTS: were adjusted for known survival predictors, including patient age, tumor size, neurologic status, and postsurgery treatment, and were compared with survival associations from an expert reader. RESULTS: Compared with total qualitative assessment by an expert reader, the whole-tumor rCBV-based SVM model was the strongest parameter associated with 6-month and 1-, 2-, and 3-year survival in the independent patient data (area under the receiver operating characteristic curve, 0.794-0.851; hazard ratio, 5.4-21.2). DISCUSSION: Machine learning by means of SVM in combination with whole-tumor rCBV histogram analysis can be used to identify early patient survival in aggressive gliomas. The SVM model returned higher diagnostic accuracy values than an expert reader, and the model appears to be insensitive to patient, observer, and institutional variations.