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1.  BMC medical imaging reviewer acknowledgement 2014 
BMC Medical Imaging  2015;15(1):3.
Contributing reviewers
The editors of BMC Medical Imaging would like to thank all our reviewers who have contributed to the journal in Volume 14 (2014).
PMCID: PMC4324902
2.  Determination of the human spine curve based on laser triangulation 
BMC Medical Imaging  2015;15(1):2.
The main objective of the present method was to automatically obtain a spatial curve of the thoracic and lumbar spine based on a 3D shape measurement of a human torso with developed scoliosis. Manual determination of the spine curve, which was based on palpation of the thoracic and lumbar spinous processes, was found to be an appropriate way to validate the method. Therefore a new, noninvasive, optical 3D method for human torso evaluation in medical practice is introduced.
Twenty-four patients with confirmed clinical diagnosis of scoliosis were scanned using a specially developed 3D laser profilometer. The measuring principle of the system is based on laser triangulation with one-laser-plane illumination. The measurement took approximately 10 seconds at 700 mm of the longitudinal translation along the back. The single point measurement accuracy was 0.1 mm. Computer analysis of the measured surface returned two 3D curves. The first curve was determined by manual marking (manual curve), and the second was determined by detecting surface curvature extremes (automatic curve). The manual and automatic curve comparison was given as the root mean square deviation (RMSD) for each patient. The intra-operator study involved assessing 20 successive measurements of the same person, and the inter-operator study involved assessing measurements from 8 operators.
The results obtained for the 24 patients showed that the typical RMSD between the manual and automatic curve was 5.0 mm in the frontal plane and 1.0 mm in the sagittal plane, which is a good result compared with palpatory accuracy (9.8 mm). The intra-operator repeatability of the presented method in the frontal and sagittal planes was 0.45 mm and 0.06 mm, respectively. The inter-operator repeatability assessment shows that that the presented method is invariant to the operator of the computer program with the presented method.
The main novelty of the presented paper is the development of a new, non-contact method that provides a quick, precise and non-invasive way to determine the spatial spine curve for patients with developed scoliosis and the validation of the presented method using the palpation of the spinous processes, where no harmful ionizing radiation is present.
PMCID: PMC4327951  PMID: 25651841
Laser profilometry; 3D; Back shape analysis; Scoliosis; Spatial spine curve; Cubic splines
3.  Validation of digit-length ratio (2D:4D) assessments on the basis of DXA-derived hand scans 
BMC Medical Imaging  2015;15(1):1.
The second-to-fourth digit-length ratio (2D:4D) may be a correlate of prenatal sex steroids, and it has been linked to sporting prowess. The aim of the study was to validate dual-energy X-ray-absorptiometry (DXA) as a technique to assess 2D:4D in soccer players under 15 years of age (U-15).
Paired X-ray and DXA scans of the left hands of 63 male U-15 elite soccer players (age: 14.0 ± 0.3 years) were performed, and 2D:4D was then compared between the two techniques. The 2D:4D measurements were performed twice by two blinded raters. Intrarater and interrater reliability, as well as agreement between the X-ray and the DXA assessments, were tested.
Intrarater reliabilities of both raters using X-ray with intraclass correlation coefficients (ICCs) of 0.97 and 0.90 were excellent. Using DXA, the ICCs were 0.90 and 0.91 thus also showing excellent reliability. Interrater reliabilities were excellent using both the X-ray (ICC of 0.94) and the DXA (ICC of 0.90), assessments respectively. Bland-Altman plots demonstrated that the 2D:4D ratios of the two raters did not differ significantly between the X-ray and the DXA assessments. The standard errors of estimate were 0.01 for both techniques. The 95% limits of agreement of ±0.018 (±2.0%) and ±0.023 (±2.6%), respectively, were within the acceptable tolerance of 5%, and showed very good agreement.
DXA offered a replicable technique for assessing 2D:4D in youth soccer players. Therefore, the DXA technique seems to be an alternative method for evaluating 2D:4D in youth sports.
PMCID: PMC4323124  PMID: 25645550
Talent identification; Young athletes; Finger length; Measurement techniques
4.  Breast vibro-acoustography: initial experience in benign lesions 
BMC Medical Imaging  2014;14(1):40.
Vibro-acoustography (VA) is a newly developed imaging technology that is based on low-frequency vibrations induced in the object by the radiation force of ultrasound. VA is sensitive to the dynamic characteristics of tissue. Here, we evaluate the performance of VA in identifying benign lesions and compare the results to those of mammography.
An integrated mammography-VA system designed for in vivo breast imaging was tested on a group of female volunteers, age ≥ 18 years, with suspected breast lesions based on clinical examination. A set of VA scans was acquired after each corresponding mammography. Most lesions were classified as benign based on their histological results. However, in 4 cases, initial diagnosis based on clinical imaging determined that the lesions were cysts. These cysts were aspirated with needle aspiration and disappeared completely under direct ultrasound visualization. Therefore, no biopsies were performed on these cases and lesions were classified as benign based on clinical findings per clinical standards. To define the VA characteristics of benign breast masses, we adopted the features that are normally attributed to such masses in mammography. In a blinded assessment, three radiologists evaluated the VA images independently. The diagnostic accuracy of VA for detection of benign lesions was assessed by comparing the reviewers’ evaluations with clinical data.
Out of a total 29 benign lesions in the group, the reviewers were able to locate all lesions on VA images and mammography, 100% with (95% confidence interval (CI): 88% to 100%). Two reviewers were also able to correctly classify 83% (95% CI: 65% to 92%), and the third reviewer 86% (95% CI: 65% to 95%) of lesions, as benign on VA images and 86% (95% CI: 69% to 95%) on mammography.
The results suggest that the mammographic characteristics of benign lesion may also be used to identify such lesions in VA. Furthermore, the results show the ability of VA to detect benign breast abnormalities with a performance comparable to mammography. Therefore, the VA technology has the potential to be utilized as a complementary tool for breast imaging applications. Additional studies are needed to compare the capabilities of VA and traditional ultrasound imaging.
PMCID: PMC4304615  PMID: 25547172
Breast neoplasms; Breast ultrasonography; Mammography; Vibro-acoustography; Benign breast lesion
5.  Breast cancer detection using sonography in women with mammographically dense breasts 
BMC Medical Imaging  2014;14(1):41.
Mammography, the gold standard for breast cancer screening misses some cancers, especially in women with dense breasts. Breast ultrasonography as a supplementary imaging tool for further evaluation of symptomatic women with mammographically dense breasts may improve the detection of mass lesions otherwise missed at mammography.
The purpose of this study was to determine the incremental breast cancer detection rate using US scanning in symptomatic women with mammographically dense breasts in a resource poor environment.
A cross sectional descriptive study. Women referred for mammography underwent bilateral breast ultrasound, and mammography for symptom evaluation. The lesions seen by both modalities were described using sonographic BI-RADS lexicon and categorized. Ultrasound guided core biopsies were performed. IRB approval was obtained and all participants provided informed written consent.
In total 148 women with mammographically dense breasts were recruited over six months. The prevalence of breast cancer in symptomatic women with mammographically dense breasts was 22/148 (15%). Mammography detected 16/22 (73%) of these cases and missed 6/22 (27%). The six breast cancer cases missed were correctly diagnosed on breast ultrasonography. Sonographic features typical of breast malignancy were irregular shape, non-parallel orientation, non circumscribed margin, echogenic halo, and increased lesion vascularity (p values < 0.005). Typical sonofeatures of benign mass lesions were: oval shape, parallel orientation and circumscribed margin (p values <0.005).
Breast ultrasound scan as a supplementary imaging tool detected 27% more malignant mass lesions otherwise missed by mammography among these symptomatic women with mammographically dense breasts. We recommend that ultra sound scanning in routine evaluation of symptomatic women with mammographically dense breasts.
PMCID: PMC4311471  PMID: 25547239
Sonography; Breast cancer; BIRADS; Dense breasts
6.  Myofibre segmentation in H&E stained adult skeletal muscle images using coherence-enhancing diffusion filtering 
BMC Medical Imaging  2014;14(1):38.
The correct segmentation of myofibres in histological muscle biopsy images is a critical step in the automatic analysis process. Errors occurring as a result of incorrect segmentations have a compounding effect on latter morphometric analysis and as such it is vital that the fibres are correctly segmented. This paper presents a new automatic approach to myofibre segmentation in H&E stained adult skeletal muscle images that is based on Coherence-Enhancing Diffusion filtering.
The procedure can be broadly divided into four steps: 1) pre-processing of the images to extract only the eosinophilic structures, 2) performing of Coherence-Enhancing Diffusion filtering to enhance the myofibre boundaries whilst smoothing the interior regions, 3) morphological filtering to connect unconnected boundary regions and remove noise, and 4) marker controlled watershed transform to split touching fibres.
The method has been tested on a set of adult cases with a total of 2,832 fibres. Evaluation was done in terms of segmentation accuracy and other clinical metrics.
The results show that the proposed approach achieves a segmentation accuracy of 89% which is a significant improvement over existing methods.
PMCID: PMC4274691  PMID: 25352214
Digital pathology; Muscle biopsy; Image segmentation
7.  Noise-compensated homotopic non-local regularized reconstruction for rapid retinal optical coherence tomography image acquisitions 
BMC Medical Imaging  2014;14:37.
Optical coherence tomography (OCT) is a minimally invasive imaging technique, which utilizes the spatial and temporal coherence properties of optical waves backscattered from biological material. Recent advances in tunable lasers and infrared camera technologies have enabled an increase in the OCT imaging speed by a factor of more than 100, which is important for retinal imaging where we wish to study fast physiological processes in the biological tissue. However, the high scanning rate causes proportional decrease of the detector exposure time, resulting in a reduction of the system signal-to-noise ratio (SNR). One approach to improving the image quality of OCT tomograms acquired at high speed is to compensate for the noise component in the images without compromising the sharpness of the image details.
In this study, we propose a novel reconstruction method for rapid OCT image acquisitions, based on a noise-compensated homotopic modified James-Stein non-local regularized optimization strategy. The performance of the algorithm was tested on a series of high resolution OCT images of the human retina acquired at different imaging rates.
Quantitative analysis was used to evaluate the performance of the algorithm using two state-of-art denoising strategies. Results demonstrate significant SNR improvements when using our proposed approach when compared to other approaches.
A new reconstruction method based on a noise-compensated homotopic modified James-Stein non-local regularized optimization strategy was developed for the purpose of improving the quality of rapid OCT image acquisitions. Preliminary results show the proposed method shows considerable promise as a tool to improve the visualization and analysis of biological material using OCT.
PMCID: PMC4204388  PMID: 25319186
8.  Automatic diagnosis of melanoma using machine learning methods on a spectroscopic system 
BMC Medical Imaging  2014;14:36.
Early and accurate diagnosis of melanoma, the deadliest type of skin cancer, has the potential to reduce morbidity and mortality rate. However, early diagnosis of melanoma is not trivial even for experienced dermatologists, as it needs sampling and laboratory tests which can be extremely complex and subjective. The accuracy of clinical diagnosis of melanoma is also an issue especially in distinguishing between melanoma and mole. To solve these problems, this paper presents an approach that makes non-subjective judgements based on quantitative measures for automatic diagnosis of melanoma.
Our approach involves image acquisition, image processing, feature extraction, and classification. 187 images (19 malignant melanoma and 168 benign lesions) were collected in a clinic by a spectroscopic device that combines single-scattered, polarized light spectroscopy with multiple-scattered, un-polarized light spectroscopy. After noise reduction and image normalization, features were extracted based on statistical measurements (i.e. mean, standard deviation, mean absolute deviation, L 1 norm, and L 2 norm) of image pixel intensities to characterize the pattern of melanoma. Finally, these features were fed into certain classifiers to train learning models for classification.
We adopted three classifiers – artificial neural network, naïve bayes, and k-nearest neighbour to evaluate our approach separately. The naive bayes classifier achieved the best performance - 89% accuracy, 89% sensitivity and 89% specificity, which was integrated with our approach in a desktop application running on the spectroscopic system for diagnosis of melanoma.
Our work has two strengths. (1) We have used single scattered polarized light spectroscopy and multiple scattered unpolarized light spectroscopy to decipher the multilayered characteristics of human skin. (2) Our approach does not need image segmentation, as we directly probe tiny spots in the lesion skin and the image scans do not involve background skin. The desktop application for automatic diagnosis of melanoma can help dermatologists get a non-subjective second opinion for their diagnosis decision.
PMCID: PMC4204387  PMID: 25311811
9.  3D facial landmarks: Inter-operator variability of manual annotation 
BMC Medical Imaging  2014;14:35.
Manual annotation of landmarks is a known source of variance, which exist in all fields of medical imaging, influencing the accuracy and interpretation of the results. However, the variability of human facial landmarks is only sparsely addressed in the current literature as opposed to e.g. the research fields of orthodontics and cephalometrics. We present a full facial 3D annotation procedure and a sparse set of manually annotated landmarks, in effort to reduce operator time and minimize the variance.
Facial scans from 36 voluntary unrelated blood donors from the Danish Blood Donor Study was randomly chosen. Six operators twice manually annotated 73 anatomical and pseudo-landmarks, using a three-step scheme producing a dense point correspondence map. We analyzed both the intra- and inter-operator variability, using mixed-model ANOVA. We then compared four sparse sets of landmarks in order to construct a dense correspondence map of the 3D scans with a minimum point variance.
The anatomical landmarks of the eye were associated with the lowest variance, particularly the center of the pupils. Whereas points of the jaw and eyebrows have the highest variation. We see marginal variability in regards to intra-operator and portraits. Using a sparse set of landmarks (n=14), that capture the whole face, the dense point mean variance was reduced from 1.92 to 0.54 mm.
The inter-operator variability was primarily associated with particular landmarks, where more leniently landmarks had the highest variability. The variables embedded in the portray and the reliability of a trained operator did only have marginal influence on the variability. Further, using 14 of the annotated landmarks we were able to reduced the variability and create a dense correspondences mesh to capture all facial features.
PMCID: PMC4205300  PMID: 25306436
3D Facial landmarks; Inter-operator annotation variance; Dense point correspondence; Point distribution mode; ANOVA
10.  Breakthrough reactions of iodinated and gadolinium contrast media after oral steroid premedication protocol 
BMC Medical Imaging  2014;14:34.
Adverse reactions to iodinated and gadolinium contrast media are an important clinical issue. Although some guidelines have proposed oral steroid premedication protocols to prevent adverse reactions, some patients may have reactions to contrast media in spite of premedication (breakthrough reaction; BTR).
The purpose of this study was to assess the frequency, type and severity of BTR when following an oral steroid premedication protocol.
All iodinated and gadolinium contrast-enhanced radiologic examinations between August 2011 and February 2013 for which the premedication protocol was applied in our institution were assessed for BTRs.
The protocol was applied to a total of 252 examinations (153 patients, ages 15–87 years; 63 males, 90 females). Of these, 152 were for prior acute adverse reactions to contrast media, 85 were for a history of bronchial asthma, and 15 were for other reasons. There were 198 contrast enhanced CTs and 54 contrast enhanced MRIs. There were nine BTR (4.5%) for iodinated contrast media, and only one BTR (1.9%) for gadolinium contrast media: eight were mild and one was moderate. No patient who had a mild index reaction (IR) had a severe BTR.
Incidence of BTRs when following the premedication protocol was low. This study by no means proves the efficacy of premedication, but provides some support for following a premedication protocol to improve safety of contrast-enhanced examinations when prior adverse reactions are mild, or when there is a history of asthma.
PMCID: PMC4195268  PMID: 25287952
Iodinated contrast media; Gadolinium contrast media; Breakthrough reaction; Acute adverse reaction
11.  Interactive neonatal gastrointestinal magnetic resonance imaging using fruit juice as an oral contrast media 
BMC Medical Imaging  2014;14:33.
The objective was to evaluate the use of fruit juice with an interactive inversion recovery (IR) MR pulse sequence to visualise the gastrointestinal tract.
We investigated the relaxation properties of 12 different natural fruit juices in vitro, to identify which could be used as oral contrast. We then describe our initial experience using an interactive MR pulse sequence to allow optimal visualisation after administering pineapple juice orally, and suppressing pre-existing bowel fluid contents, with variable TI in three adult and one child volunteer.
Pineapple juice (PJ) had both the shortest T1 (243 ms) and shortest T2 (48 ms) of the fruit juices tested. Optimal signal differentiation between pre-existing bowel contents and oral PJ administration was obtained with TIs of between 900 and 1100 ms.
The use of an inversion recovery preparation allowed long T1 pre-existing bowel contents to be suppressed whilst the short T1 of fruit juice acts as a positive contrast medium. Pineapple juice could be used as oral contrast agent for neonatal gastrointestinal magnetic resonance imaging.
PMCID: PMC4186814  PMID: 25245815
Neonatal; MRI; Bowel; Fruit juice
12.  The accuracy of a designed software for automated localization of craniofacial landmarks on CBCT images 
BMC Medical Imaging  2014;14:32.
Two-dimensional projection radiographs have been traditionally considered the modality of choice for cephalometric analysis. To overcome the shortcomings of two-dimensional images, three-dimensional computed tomography (CT) has been used to evaluate craniofacial structures. However, manual landmark detection depends on medical expertise, and the process is time-consuming. The present study was designed to produce software capable of automated localization of craniofacial landmarks on cone beam (CB) CT images based on image registration and to evaluate its accuracy.
The software was designed using MATLAB programming language. The technique was a combination of feature-based (principal axes registration) and voxel similarity-based methods for image registration. A total of 8 CBCT images were selected as our reference images for creating a head atlas. Then, 20 CBCT images were randomly selected as the test images for evaluating the method. Three experts twice located 14 landmarks in all 28 CBCT images during two examinations set 6 weeks apart. The differences in the distances of coordinates of each landmark on each image between manual and automated detection methods were calculated and reported as mean errors.
The combined intraclass correlation coefficient for intraobserver reliability was 0.89 and for interobserver reliability 0.87 (95% confidence interval, 0.82 to 0.93). The mean errors of all 14 landmarks were <4 mm. Additionally, 63.57% of landmarks had a mean error of <3 mm compared with manual detection (gold standard method).
The accuracy of our approach for automated localization of craniofacial landmarks, which was based on combining feature-based and voxel similarity-based methods for image registration, was acceptable. Nevertheless we recommend repetition of this study using other techniques, such as intensity-based methods.
PMCID: PMC4171715  PMID: 25223399
13.  Automatic measurement of aortic annulus diameter in 3-dimensional Transoesophageal echocardiography 
BMC Medical Imaging  2014;14:31.
Transcatheter aortic valve implantation involves percutaneously implanting a biomechanical aortic valve to treat severe aortic stenosis. In order to select a proper device, precise sizing of the aortic valve annulus must be completed.
In this paper, we describe a fully automatic segmentation method to measure the aortic annulus diameter in patients with aortic calcification, operating on 3-dimensional transesophageal echocardiographic images. The method is based on state estimation of a subdivision surface representation of the left ventricular outflow tract and aortic root. The state estimation is solved by an extended Kalman filter driven by edge detections normal to the subdivision surface.
The method was validated on echocardiographic recordings of 16 patients. Comparison against two manual measurements showed agreements (mean ±SD) of -0.3±1.6 and -0.2±2.3 mm for perimeter-derived diameters, compared to an interobserver agreement of -0.1±2.1 mm.
With this study, we demonstrated the feasibility of an efficient and fully automatic measurement of the aortic annulus in patients with aortic disease. The algorithm robustly measured the aortic annulus diameter, providing measurements indistinguishable from those done by cardiologists.
PMCID: PMC4274687  PMID: 25200865
Segmentation; Subdivision surface; 3-Dimensional Echocardiography; Aortic valve; Transcatheter aortic valve implantation
14.  Influence of trigger type, tube voltage and heart rate on calcified plaque imaging in dual source cardiac computed tomography: phantom study 
BMC Medical Imaging  2014;14:30.
To investigate the impact of high pitch cardiac CT vs. retrospective ECG gated CT on the quantification of calcified vessel stenoses, with assessment of the influence of tube voltage, reconstruction kernel and heart rate.
A 4D cardiac movement phantom equipped with three different plaque phantoms (12.5%, 25% and 50% stenosis at different calcification levels), was scanned with a 128-row dual source CT scanner, applying different trigger types (gated vs. prospectively triggered high pitch), tube voltages (100-120 kV) and heart rates (50–90 beats per minute, bpm). Images were reconstructed using different standard (B26f, B46f, B70f) and iterative (I26f, I70f) convolution kernels. Absolute and relative plaque sizes were measured and statistically compared. Radiation dose associated with the different methods (gated vs. high pitch, 100 kV vs. 120 kV) were compared.
Compared to the known diameters of the phantom plaques and vessels both CT-examination techniques overestimated the degrees of stenoses. Using the high pitch CT-protocol plaques appeared larger (0.09 ± 0.31 mm, 2 ± 8 percent points, PP) in comparison to the ECG-gated CT-scans. Reducing tube voltage had a similar effect, resulting in higher grading of the same stenoses by 3 ± 8 PP. In turn, sharper convolution kernels lead to a lower grading of stenoses (differences of up to 5%). Pairwise comparison of B26f and I26f, B46f and B70f, and B70f and I70f showed differences of 0–1 ± 6–8 PP of the plaque depiction. Motion artifacts were present only at 90 bpm high pitch experiments. High-pitch protocols were associated with significantly lower radiation doses compared with the ECG-gated protocols (258.0 mGy vs. 2829.8 mGy CTDIvol, p ≤ 0.0001).
Prospectively triggered high-pitch cardiac CT led to an overestimation of plaque diameter and degree of stenoses in a coronary phantom. This overestimation is only slight and probably negligible in a clinical situation. Even at higher heart rates high pitch CT-scanning allowed reliable measurements of plaque and vessel diameters with only slight differences compared ECG-gated protocols, although motion artifacts were present at 90 bpm using the high pitch protocols.
PMCID: PMC4174388  PMID: 25178653
15.  Validation of a measuring technique with computed tomography for cement penetration into trabecular bone underneath the tibial tray in total knee arthroplasty on a cadaver model 
BMC Medical Imaging  2014;14:29.
In total knee arthroplasty (TKA), cement penetration between 3 and 5 mm beneath the tibial tray is required to prevent loosening of the tibia component. The objective of this study was to develop and validate a reliable in vivo measuring technique using CT imaging to assess cement distribution and penetration depth in the total area underneath a tibia prosthesis.
We defined the radiodensity ranges for trabecular tibia bone, polymethylmethacrylate (PMMA) cement and cement-penetrated trabecular bone and measured the percentages of cement penetration at various depths after cementing two tibia prostheses onto redundant femoral heads. One prosthesis was subsequently removed to examine the influence of the metal tibia prostheses on the quality of the CT images. The percentages of cement penetration in the CT slices were compared with percentages measured with photographs of the corresponding transversal slices.
Trabecular bone and cement-penetrated trabecular bone had no overlap in quantitative scale of radio-density. There was no significant difference in mean HU values when measuring with or without the tibia prosthesis. The percentages of measured cement-penetrated trabecular bone in the CT slices of the specimen were within the range of percentages that could be expected based on the measurements with the photographs (p = 0.04).
CT scan images provide valid results in measuring the penetration and distribution of cement into trabecular bone underneath the tibia component of a TKA. Since the proposed method does not turn metal elements into artefacts, it enables clinicians to assess the width and density of the cement mantle in vivo and to compare the results of different cementing methods in TKA.
PMCID: PMC4150551  PMID: 25158996
Computed tomography; CT scan; Cement penetration; Total knee arthroplasty; TKA
16.  Masked smoothing using separable kernels for CT perfusion images 
BMC Medical Imaging  2014;14:28.
CT perfusion images have a high contrast ratio between voxels representing different anatomy, such as tissue or vessels, which makes image segmentation of tissue and vascular regions relatively easy. However, grey and white matter tissue regions have relatively low values and can suffer from poor signal to noise ratios. While smoothing can improve the image quality of the tissue regions, the inclusion of much higher valued vascular voxels can skew the tissue values. It is thus desirable to smooth tissue voxels separately from other voxel types, as has been previously implemented using mean filter kernels. We created a novel Masked Smoothing method that performs Gaussian smoothing restricted to tissue voxels. Unlike previous methods, it is implemented as a combination of separable kernels and is therefore fast enough to consider for clinical work, even for large kernel sizes.
We compare our Masked Smoothing method to alternatives using Gaussian smoothing on an unaltered image volume and Gaussian smoothing on an image volume with vascular voxels set to zero. Each method was tested on simulation data, collected phantom data, and CT perfusion data sets. We then examined tissue voxels for bias and noise reduction.
Simulation and phantom experiments demonstrate that Masked Smoothing does not bias the underlying tissue value, whereas the other smoothing methods create significant bias. Furthermore, using actual CT perfusion data, we demonstrate significant differences in the calculated CBF and CBV values dependent on the smoothing method used.
The Masked Smoothing is fast enough to allow eventual clinical usage and can remove the bias of tissue voxel values that neighbor blood vessels. Conversely, the other Gaussian smoothing methods introduced significant bias to the tissue voxels.
PMCID: PMC4155389  PMID: 25145879
17.  The use of PET-MRI in the follow-up after radiofrequency- and microwave ablation of colorectal liver metastases 
BMC Medical Imaging  2014;14:27.
Thermal ablation of colorectal liver metastases (CRLM) may result in local progression, which generally appear within a year of treatment. As the timely diagnosis of this progression allows potentially curative local treatment, an optimal follow-up imaging strategy is essential. PET-MRI is a one potential imaging modality, combining the advantages of PET and MRI. The aim of this study is evaluate fluorine-18 deoxyglucose positron emission tomography (FDG) PET-MRI as a modality for detection of local tumor progression during the first year following thermal ablation, as compared to the current standard, FDG PET-CT. The ability of FDG PET-MRI to detect new intrahepatic lesions, and the extent to which FDG PET-MRI alters clinical management, inter-observer variability and patient preference will also be included as secondary outcomes.
Twenty patients undergoing treatment with radiofrequency or microwave ablation for (recurrent) CRLM will be included in this prospective trial. During the first year of follow-up, patients will be scanned at the VU University Medical Center at 3-monthly intervals using a 4-phase liver CT, FDG PET-CT and FDG PET-MRI. Patients treated with chemotherapy <6 weeks prior to scanning or with a contra-indication for MRI will be excluded. MRI will be performed using both whole body imaging (mDixon) and dedicated liver sequences, including diffusion-weighted imaging, T1 in-phase and opposed-phase, T2 and dynamic contrast-enhanced imaging. The results of all modalities will be scored by 4 individual reviewers and inter-observer agreement will be determined. The reference standard will be histology or clinical follow-up. A questionnaire regarding patients’ experience with both modalities will also be completed at the end of the follow-up year.
Improved treatment options for local site recurrences following CRLM ablation mean that accurate post-ablation staging is becoming increasingly important. The combination of the sensitivity of MRI as a detection method for small intrahepatic lesions with the ability of FDG PET to visualize enhanced metabolism at the ablation site suggests that FDG PET-MRI could potentially improve the accuracy of (early) detection of progressive disease, and thus allow swifter and more effective decision-making regarding appropriate treatment.
Trial registration
Trial registration number: NCT01895673
PMCID: PMC4141664  PMID: 25103913
Radiofrequency ablation; Liver neoplasms/secondary; Neoplasm recurrence; Local; Liver neoplasms/surgery; FDG-PET; PET-MRI; Magnetic resonance imaging/methods; Microwave ablation
18.  Diffusion-weighted MRI characteristics of the cerebral metastasis to brain boundary predicts patient outcomes 
BMC Medical Imaging  2014;14:26.
Diffusion-weighted MRI (DWI) has been used in neurosurgical practice mainly to distinguish cerebral metastases from abscess and glioma. There is evidence from other solid organ cancers and metastases that DWI may be used as a biomarker of prognosis and treatment response. We therefore investigated DWI characteristics of cerebral metastases and their peritumoral region recorded pre-operatively and related these to patient outcomes.
Retrospective analysis of 76 cases operated upon at a single institution with DWI performed pre-operatively at 1.5T. Maps of apparent diffusion coefficient (ADC) were generated using standard protocols. Readings were taken from the tumor, peritumoral region and across the brain-tumor interface. Patient outcomes were overall survival and time to local recurrence.
A minimum ADC greater than 919.4 × 10-6 mm2/s within a metastasis predicted longer overall survival regardless of adjuvant therapies. This was not simply due to differences between the types of primary cancer because the effect was observed even in a subgroup of 36 patients with the same primary, non-small cell lung cancer. The change in diffusion across the tumor border and into peritumoral brain was measured by the “ADC transition coefficient” or ATC and this was more strongly predictive than ADC readings alone. Metastases with a sharp change in diffusion across their border (ATC >0.279) showed shorter overall survival compared to those with a more diffuse edge. The ATC was the only imaging measurement which independently predicted overall survival in multivariate analysis (hazard ratio 0.54, 95% CI 0.3 – 0.97, p = 0.04).
DWI demonstrates changes in the tumor, across the tumor edge and in the peritumoral region which may not be visible on conventional MRI and this may be useful in predicting patient outcomes for operated cerebral metastases.
PMCID: PMC4126355  PMID: 25086595
Cerebral metastasis; Brain neoplasms; Secondary; Neoplasm invasiveness; Diffusion-weighted imaging; Apparent diffusion coefficient; MRI
19.  Determination of regional lung air volume distribution at mid-tidal breathing from computed tomography: a retrospective study of normal variability and reproducibility 
BMC Medical Imaging  2014;14:25.
Determination of regional lung air volume has several clinical applications. This study investigates the use of mid-tidal breathing CT scans to provide regional lung volume data.
Low resolution CT scans of the thorax were obtained during tidal breathing in 11 healthy control male subjects, each on two separate occasions. A 3D map of air volume was derived, and total lung volume calculated. The regional distribution of air volume from centre to periphery of the lung was analysed using a radial transform and also using one dimensional profiles in three orthogonal directions.
The total air volumes for the right and left lungs were 1035 +/− 280 ml and 864 +/− 315 ml, respectively (mean and SD). The corresponding fractional air volume concentrations (FAVC) were 0.680 +/− 0.044 and 0.658 +/− 0.062. All differences between the right and left lung were highly significant (p < 0.0001). The coefficients of variation of repeated measurement of right and left lung air volumes and FAVC were 6.5% and 6.9% and 2.5% and 3.6%, respectively. FAVC correlated significantly with lung space volume (r = 0.78) (p < 0.005). FAVC increased from the centre towards the periphery of the lung. Central to peripheral ratios were significantly higher for the right (0.100 +/− 0.007 SD) than the left (0.089 +/− 0.013 SD) (p < 0.0001).
A technique for measuring the distribution of air volume in the lung at mid-tidal breathing is described. Mean values and reproducibility are described for healthy male control subjects. Fractional air volume concentration is shown to increase with lung size.
PMCID: PMC4118261  PMID: 25063729
Regional lung volume measurement; Computed tomography; Reproducibility
20.  Analysis of regional bone scan index measurements for the survival of patients with prostate cancer 
BMC Medical Imaging  2014;14:24.
A bone scan is a common method for monitoring bone metastases in patients with advanced prostate cancer. The Bone Scan Index (BSI) measures the tumor burden on the skeleton, expressed as a percentage of the total skeletal mass. Previous studies have shown that BSI is associated with survival of prostate cancer patients. The objective in this study was to investigate to what extent regional BSI measurements, as obtained by an automated method, can improve the survival analysis for advanced prostate cancer.
The automated method for analyzing bone scan images computed BSI values for twelve skeletal regions, in a study population consisting of 1013 patients diagnosed with prostate cancer. In the survival analysis we used the standard Cox proportional hazards model and a more advanced non-linear method based on artificial neural networks. The concordance index (C-index) was used to measure the performance of the models.
A Cox model with age and total BSI obtained a C-index of 70.4%. The best Cox model with regional measurements from Costae, Pelvis, Scapula and the Spine, together with age, got a similar C-index (70.5%). The overall best single skeletal localisation, as measured by the C-index, was Costae. The non-linear model performed equally well as the Cox model, ruling out any significant non-linear interactions among the regional BSI measurements.
The present study showed that the localisation of bone metastases obtained from the bone scans in prostate cancer patients does not improve the performance of the survival models compared to models using the total BSI. However a ranking procedure indicated that some regions are more important than others.
PMCID: PMC4105506  PMID: 25012268
Artificial neural networks; Machine learning; Bone scan index; Survival analysis; Prostate cancer
21.  Fuzzy technique for microcalcifications clustering in digital mammograms 
BMC Medical Imaging  2014;14:23.
Mammography has established itself as the most efficient technique for the identification of the pathological breast lesions. Among the various types of lesions, microcalcifications are the most difficult to identify since they are quite small (0.1-1.0 mm) and often poorly contrasted against an images background. Within this context, the Computer Aided Detection (CAD) systems could turn out to be very useful in breast cancer control.
In this paper we present a potentially powerful microcalcifications cluster enhancement method applicable to digital mammograms. The segmentation phase employs a form filter, obtained from LoG filter, to overcome the dependence from target dimensions and to optimize the recognition efficiency. A clustering method, based on a Fuzzy C-means (FCM), has been developed. The described method, Fuzzy C-means with Features (FCM-WF), was tested on simulated clusters of microcalcifications, implying that the location of the cluster within the breast and the exact number of microcalcifications are known.
The proposed method has been also tested on a set of images from the mini-Mammographic database provided by Mammographic Image Analysis Society (MIAS) publicly available.
The comparison between FCM-WF and standard FCM algorithms, applied on both databases, shows that the former produces better microcalcifications associations for clustering than the latter: with respect to the private and the public database we had a performance improvement of 10% and 5% with regard to the Merit Figure and a 22% and a 10% of reduction of false positives potentially identified in the images, both to the benefit of the FCM-WF. The method was also evaluated in terms of Sensitivity (93% and 82%), Accuracy (95% and 94%), FP/image (4% for both database) and Precision (62% and 65%).
Thanks to the private database and to the informations contained in it regarding every single microcalcification, we tested the developed clustering method with great accuracy. In particular we verified that 70% of the injected clusters of the private database remained unaffected if the reconstruction is performed with the FCM-WF. Testing the method on the MIAS databases allowed also to verify the segmentation properties of the algorithm, showing that 80% of pathological clusters remained unaffected.
PMCID: PMC4105893  PMID: 24961885
Breast cancer; Microcalcifications; Spatial filters; Clustering; Fuzzy logic; C-means; Mammography; Segmentation
22.  Fractal dimension analysis of malignant and benign endobronchial ultrasound nodes 
BMC Medical Imaging  2014;14:22.
Endobronchial ultrasonography (EBUS) has been applied as a routine procedure for the diagnostic of hiliar and mediastinal nodes. The authors assessed the relationship between the echographic appearance of mediastinal nodes, based on endobronchial ultrasound images, and the likelihood of malignancy.
The images of twelve malignant and eleven benign nodes were evaluated. A previous processing method was applied to improve the quality of the images and to enhance the details. Texture and morphology parameters analyzed were: the image texture of the echographies and a fractal dimension that expressed the relationship between area and perimeter of the structures that appear in the image, and characterizes the convoluted inner structure of the hiliar and mediastinal nodes.
Processed images showed that relationship between log perimeter and log area of hilar nodes was lineal (i.e. perimeter vs. area follow a power law). Fractal dimension was lower in the malignant nodes compared with non-malignant nodes (1.47(0.09), 1.53(0.10) mean(SD), Mann–Whitney U test p < 0.05)).
Fractal dimension of ultrasonographic images of mediastinal nodes obtained through endobronchial ultrasound differ in malignant nodes from non-malignant. This parameter could differentiate malignat and non-malignat mediastinic and hiliar nodes.
PMCID: PMC4061455  PMID: 24920158
23.  Impact of a standardized training program on midwives’ ability to assess fetal heart anatomy by ultrasound 
BMC Medical Imaging  2014;14:20.
Studies of prenatal detection of congenital heart disease (CHD) in the UK, Italy, and Norway indicate that it should be possible to improve the prenatal detection rate of CHD in Sweden. These studies have shown that training programs, visualization of the outflow tracts and color-Doppler all can help to speed up and improve the detection rate and accuracy. We aimed to introduce a more accurate standardized fetal cardiac ultrasound screening protocol in Sweden.
A novel pedagogical model for training midwives in standardized cardiac imaging was developed, a model using a think-aloud analysis during a pre- and post-course test and a subsequent group reflection. The self-estimated difficulties and knowledge gaps of two experienced and two beginner midwives were identified. A two-day course with mixed lectures, demonstrations and hands-on sessions was followed by a feedback session three months later consisting of an interview and check-up. The long-term effects were tested two years later.
At the post-course test the self-assessed uncertainty was lower than at the pre-course test. The qualitative evaluation showed that the color Doppler images were difficult to interpret, but the training seems to have improved their ability to use the new technique. The ability to perform the method remained at the new level at follow-up both three months and two years later.
Our results indicate that by implementing new imaging modalities and providing hands-on training, uncertainty can be reduced and examination time decreased, but they also show that continuous on-site training with clinical and technical back-up is important.
PMCID: PMC4047785  PMID: 24889837
Color Doppler; Congenital heart disease; Detection of congenital heart defects; Fetal heart scanning; Learning program; Prenatal cardiology; Second trimester screening; Standardized training program; Ultrasound screening
24.  Brain region’s relative proximity as marker for Alzheimer’s disease based on structural MRI 
BMC Medical Imaging  2014;14:21.
Alzheimer’s disease (AD) is a progressive, incurable neurodegenerative disease and the most common type of dementia. It cannot be prevented, cured or drastically slowed, even though AD research has increased in the past 5-10 years. Instead of focusing on the brain volume or on the single brain structures like hippocampus, this paper investigates the relationship and proximity between regions in the brain and uses this information as a novel way of classifying normal control (NC), mild cognitive impaired (MCI), and AD subjects.
A longitudinal cohort of 528 subjects (170 NC, 240 MCI, and 114 AD) from ADNI at baseline and month 12 was studied. We investigated a marker based on Procrustes aligned center of masses and the percentile surface connectivity between regions. These markers were classified using a linear discriminant analysis in a cross validation setting and compared to whole brain and hippocampus volume.
We found that both our markers was able to significantly classify the subjects. The surface connectivity marker showed the best results with an area under the curve (AUC) at 0.877 (p<0.001), 0.784 (p<0.001), 0,766 (p<0.001) for NC-AD, NC-MCI, and MCI-AD, respectively, for the functional regions in the brain. The surface connectivity marker was able to classify MCI-converters with an AUC of 0.599 (p<0.05) for the 1-year period.
Our results show that our relative proximity markers include more information than whole brain and hippocampus volume. Our results demonstrate that our proximity markers have the potential to assist in early diagnosis of AD.
PMCID: PMC4048460  PMID: 24889999
Alzheimer’s disease; Mild cognitive impairment; Bio markers; MRI; Diagnosis and classification; Proximity
25.  The more you look, the more you find: challenging results on FDG-PET CT in a patient with neurofibromatosis type I 
BMC Medical Imaging  2014;14:19.
FDG-PET/CT is part of the standard diagnostic management of a patients with a large variety of common and less common malignant tumors, based on the increased glucose metabolism within tumors.
Case presentation
A hybrid fluorodeoxyglucose positron emission tomography and computed tomography (FDG-PET/CT) was performed in a neurofibromatosis patient to rule out relapse of malignant peripheral nerve sheet tumor. The scan revealed non-malignant neurofibromas, a testis seminoma and hypermetabolic syphilitic granulomata.
This case stresses the need to rule out infectious diseases when atypical hypermetabolic lesions are present.
PMCID: PMC4071334  PMID: 24885974
Syphilis; PET; Fluorodeoyglucose; Neurofibromatosis; Testicular seminoma

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