Respiratory Research Magnetic resonance lung function -a breakthrough for lung imaging and functional assessment? A phantom study and clinical trial

Maren Zapke
Hans-Georg †1
University Children's Hospital
University Erlangen-Nuremberg
Loschgestr. 1591054Erlangen, Germany

Topf
University Children's Hospital
University Erlangen-Nuremberg
Loschgestr. 1591054Erlangen, Germany

Martin Zenker firstname.lastname@example.com
University Children's Hospital
University Erlangen-Nuremberg
Loschgestr. 1591054Erlangen, Germany

Rainer Kuth firstname.lastname@example.com
Siemens medical solutions
Henkestr. 12791052Erlangen, Germany

Michael Deimling email@example.com
Siemens medical solutions
Henkestr. 12791052Erlangen, Germany

Peter Kreisler firstname.lastname@example.com
Siemens medical solutions
Henkestr. 12791052Erlangen, Germany

Manfred Rauh firstname.lastname@example.com
University Children's Hospital
University Erlangen-Nuremberg
Loschgestr. 1591054Erlangen, Germany

Christophe Chefd'hotel
Siemens Corporate Research
755 College Road East08540-6632PrincetonNJUSA

Bernhard Geiger firstname.lastname@example.com
Siemens Corporate Research
755 College Road East08540-6632PrincetonNJUSA

Thomas Rupprecht email@example.com
Children's Hospital
Preuschwitzer Straße 101D-95445BayreuthGermany

Respiratory Research Magnetic resonance lung function -a breakthrough for lung imaging and functional assessment? A phantom study and clinical trial
10.1186/1465-9921-7-106BioMed Central Page 1 of 9 (page number not for citation purposes) Research * Corresponding author †Equal contributors
Background: Chronic lung diseases are a major issue in public health. A serial pulmonary assessment using imaging techniques free of ionizing radiation and which provides early information on local function impairment would therefore be a considerably important development. Magnetic resonance imaging (MRI) is a powerful tool for the static and dynamic imaging of many organs. Its application in lung imaging however, has been limited due to the low water content of the lung and the artefacts evident at air-tissue interfaces. Many attempts have been made to visualize local ventilation using the inhalation of hyperpolarized gases or gadolinium aerosol responding to MRI. None of these methods are applicable for broad clinical use as they require specific equipment.Methods:We have shown previously that low-field MRI can be used for static imaging of the lung. Here we show that mathematical processing of data derived from serial MRI scans during the respiratory cycle produces good quality images of local ventilation without any contrast agent. A phantom study and investigations in 85 patients were performed.Results:The phantom study proved our theoretical considerations. In 99 patient investigations good correlation (r = 0.8; p ≤ 0.001) was seen for pulmonary function tests and MR ventilation measurements. Small ventilation defects were visualized.Conclusion:With this method, ventilation defects can be diagnosed long before any imaging or pulmonary function test will indicate disease. This surprisingly simple approach could easily be incorporated in clinical routine and may be a breakthrough for lung imaging and functional assessment.

Background

Magnetic resonance imaging (MRI) relies on signals emitted by hydrogen nuclei brought into a magnetic field and stimulated by an electromagnetic radio wave. The usual MRI rule is, the stronger the magnetic field, the stronger the signal. When signal strength is increased imaging is faster, the slices are thinner and the images have a better resolution. With respect to imaging the lung, we have advocated a change of paradigms and could demonstrate why less is more in lung MRI. A low magnetic field strength (0.2 T) yields a lower MR signal but also less artefacts [1][2][3][4] This reduction of the artefacts enables us to image lung tissue at low field strength.

Since the lung contains mainly air there is little tissue to give an MR signal, therefore the slice thickness of the images needs to be increased (20 to 200 mm), to produce a clear image [5][6][7][8]. We have previously shown that lung MRI is possible and that this technique can be used efficiently for fast and reliable static imaging of the lung [6][7][8].

Starting point of our approach to a functional (dynamic) assessment of the lung was the observation that in 'realtime' videos of low-field MRI scans grey values of the lung parenchyma changed noticeably during respiration, presumably reflecting the changing tissue/air ratio. This suggested that local ventilation could be measured without a contrast agent and without specific scanner technology, solely on the basis of the data produced by serial low-field MR images.

Methods

Theoretical considerations

As the spatial expansion of the lung and thorax changes with inflation and deflation, it is difficult to define the corresponding lung regions at different times during the respiratory cycle in order to make comparative measurements. We have therefore had to develop an algorithm to adjust the lung margins to a virtually constant shape while preserving the information for signal intensity (Fig. 1).

Calculation of ventilation, represented by a change in air content of a lung region, was carried out according to the following considerations shown as a simplified model in Fig. 1: Briefly, a defined volume (region of interest = ROI) in expiration has a defined MR signal (S exp ) depending on the content of air and lung parenchyma. At inspiration some of the voxels are replaced by air with a signal equivalent to background noise (S noise ) resulting in a signal at inspiration S insp . Presuming a homogeneous distribution of lung parenchyma within the ROI the total ventilation (V abs ) in ml air added during inspiration/ml lung parenchyma can now be calculated from the measured signals as V abs = (S exp -S insp )/(S exp -S noise ) (1) Accordingly, the ventilation at any point of the respiratory cycle (V act ) can be calculated by the actual signal at this point (S act ) as follows V act = (S exp -S act )/(S exp -S noise ) (2)

Phantom

To simulate lung tissue with its low overall signal intensity and multiple air/tissue interfaces we created a phantom. A cubic sponge of 5 × 12.5 × 20 cm was soaked with silicon oil (Nr.7742, Merck, Darmstadt, Germany) and subsequently squeezed so that its inner surfaces were moistened with a liquid film responsive to MRI. We measured the MR signal serially during slow compression of the sponge (Fig. 2). The "ventilation" expressed as relative air content was measured directly by calculating the change of volume (length as imaged by MRI × width × depth) during compression and compared to the MRI "ventilation" calculated using the equations given above.

Patients

We performed 99 investigations for 85 patients (60 m/25 f, 3-41 years, mean age 14.1 ± 7.8 y) in a pilot study after approval by the local ethics committee. Written informed consent was given for each investigation by the patients and/or their legal guardians. The patients were divided into five groups. Healthy n = 4, asthma n = 39, cystic fibrosis (CF) n = 19, other lung disease (i.e. pneumonia) n = 17, other disease n = 6.

Imaging and postprocessing

All MR imaging was performed at 0.2T (Magnetom Open, Siemens, Erlangen, Germany). The fast lung imaging was performed as described previously [7,8]. We chose a true FISP (Fast Imaging with Steady-state Precession) sequence [8][9][10][11] modified according to the special needs of functional imaging [1,8]. The initial images of the lung included coronal, lateral and transversal pictures in order to visualize possible morphologic changes and to calculate the lung volume. For "real time" respiration imaging we decreased the spatial resolution to 128 × 128. Repetition time TR 4.2 ms; echo time TE 2.0 ms; flip angle FA 90°; acquisition time TA 1.2 sec/image (including the preparation of the sequence). With this sequence we obtained 50 coronal images over a time period of one minute during slow, maximum amplitude respiration. To overcome the low proton density we increased the slice thickness to 60 mm. The signal was therefore strong enough for clear images of the lung. Conventional pulmonary function tests (PFT) were performed in parallel for 85 investigations. Vital capacity (vc) was chosen for comparison because of the similar breathing technique for vc in PFT and ventilation imaging using MR. a. Native ventilation MR image of one patient during expiration and inspiration Figure 1 a. Native ventilation MR image of one patient during expiration and inspiration. For precise measurement the region of interest would have to move during the respiratory cycle, we therefore include a schematic of our theoretical considerations. The four circles schematically represent four alveoli in a volume (voxel). During inspiration, tissue will be replaced by air causing a lower MR signal as shown on the right. In the same volume now only one of the "Alveoli" will give a signal. The ventilation can be derived from this signal change. b. Upper images: native (unregistered) MR ventilation images during expiration and inspiration. Measurements at the same location are almost impossible while the lung is moving as the same region of interest can not be exactly located. Note the different MR signal and the different size and shape of the lung. Lower images: Registered images. The registration process artificially changes the volume of the lung. An interpolation of the original image intensity values was used to compute the warped image when specific regions are expanded or contracted. The signal changes of the lung are then noted, the size and shape of the thorax stay the same. This way the signal change of each pixel can be measured and ventilation calculated. Note the different MR signal. In contrast to the upper images size and shape of the lung stay unchanged.

a. Hypothesis

Inspiration

Registration and measurements

All the images were transferred to a separate workstation. To compensate for breathing motion we used a registration algorithm proposed by C. Chefd'hotel et al. [12,13]. Registration was performed pair wise between all the images and an arbitrary reference image. For each pair [13], this algorithm finds a deformation that maximizes the local cross-correlation between the selected reference and the image being registered. This deformation is modelled as a smooth vector field that gives for each pixel on the reference its corresponding location on the second image. The local cross-correlation criterion was selected for its robustness to intensity changes, signal inhomogeneities, and noise. The algorithm recovers the deformation by composition of small displacements, incrementally maximizing the similarity criterion. This process, which can be seen as the numerical implementa-tion of a transport equation, offers a large capture range, which is required for this application. Given how pathologies can affect breathing motion, we found difficult to use a physical model to constrain the recovered deformation field. Instead, a simple smoothness assumption was used, and proved very effective in practice. This algorithm was selected for its ability to register images without requiring the extraction and selection of anatomical landmarks. Note that during the breathing cycle, parts of the lungs come in and out of the coronal acquisition plane (despite the large slice thickness). This type of deformation can not be captured by the registration method.

On the registered images we measured signal changes bilaterally in the upper, middle, and lower field for each image throughout the respiratory cycle and calculated the actual ventilation V act (equation 2). Total MR ventilation MR image of the phantom at "inspiration" = maximal air content and "expiration" = minimal air content Figure 2 MR image of the phantom at "inspiration" = maximal air content and "expiration" = minimal air content. The graph shows the correlation between the air content in ml air/ml sponge measured by MRI (= MR ventilation) and that calculated from the volume of the sponge (= real ventilation). Dashed lines = regression line and 95% confidence interval.

Phantom imaging

To give a quantitative estimate of total lung ventilation and allow a comparison with PFT results, we performed ventilation measurements in six representative ROIs (Fig.  3). Total lung ventilation was extrapolated by multiplying the mean ventilation (in ml air/ml lung parenchyma) derived from those ROIs with the total lung volume determined by the static thorax MRI scans. The mean ventilation was compared to the conventional PFT of the same day.

Ventilation maps

To visualize dynamic "real time" ventilation at maximum resolution, we produced ventilation maps, calculating the signal changes between each image over the respiratory cycle. The ventilation was calculated for each pixel and colour-coded red for a decrease in air content (expiration) and green for an increase in air content (inspiration). To assess the ventilation near real-time, a video was produced for each patient showing the increase or decrease of air content in 50 images over 1 minute. Thus the ventilation of the whole lung over the respiratory cycle was evaluated (supplementary videos on request).

Results

Phantom imaging

We considered maximum compression of the sponge to be "no ventilation" (0). The lung phantom confirmed that "ventilation" (= the increase of air in the sponge) can be calculated reliably with this MRI based method (r = 0.99; p ≤ 0.001) (Fig. 2).

Patient imaging

Whole lung ventilation determined by MRI correlated very well with the vital capacity (vc) derived from conventional PFT, with an overall r = 0.8 (p ≤ 0.001) for linear regression (Fig. 3). For healthy subjects r = 1; for asthma r = 0.84; (p ≤ 0.001), for cystic fibrosis (CF) r = 0.8; (p ≤ 0.001), for other lung disease r = 0.74; (p ≤ 0.001), for other disease r = 1 (table 1).

In addition to the global function parameters corresponding to results using conventional PFT, the six local measurements allowed differentiation of ventilation of the upper, middle, and lower lung regions (table 2). While in healthy persons, the lower fields of both lungs were markedly more ventilated (p ≤ 0.05), this effect was diminished in patients with asthma or CF (not significant; Wilcoxon test for matched pairs) (table 2). This is in agreement with values reported in the literature [14]. The mean ventilation in any of these segments was reduced in asthma patients and was even less in CF patients compared to healthy persons (table 2). For asthma: lower fields p ≤ 0.05; middle and upper fields not significant. For CF: lower fields p ≤ 0.001; middle and upper fields p ≤ 0.05 (Wilcoxon test).

Ventilation maps

In healthy persons, ventilation maps showed a homogeneous distribution while impaired ventilation was seen mostly in the lower lung regions and peripherally in patients suffering from asthma, less frequently in the upper or middle fields. In CF patients, diffusely distributed ventilation deficits were frequently observed (Fig. 4). In most cases, these typical patterns allowed differentiation of the disease categories simply by viewing the ventilation maps.

In our pilot study 25 investigations were performed (healthy n = 1; asthma n = 16; CF n = 3; other lung disease n = 5) in persons who had a normal global PFT (vc and fev1 > 90%). However, only 5 (20%) of these were rated to have no ventilation defects in the ventilation mapping. 5 (20%) had ≤ 3, 13 (52%) > 3, and 2 (8%) diffuse ventilation defects. On the other hand, of 15 investigations (CF n = 12; other lung disease n = 2; other disease n = 1) of patients with pathologic PFT (vc and fev1 < 70%), 3 (20%) had > 3 and 12 (80%) diffuse ventilation defects.

Discussion and conclusion

These data indicate that the method presented here could be used to visualize local destruction of the lung long before an impairment can be detected by conventional PFT. Native ventilation lung MRI appears therefore to be just as good as other methods, such as helium-3 imaging, with which similar results have been reported [15][16][17][18]. Our method may even be superior with respect to costeffectiveness and feasibility in clinical routine. One examination takes only 10-15 minutes. The method could be established for any low-field MR-scanner, no other special equipment or patient preparation is needed. Investigations can be repeated without exposing the patient to radiation or contrast agents, making it a perfect tool for studying diseases which require patients to have regular scans, such as asthma. Another significant advantage is the rapid collection of images. For ventilation mapping, images are taken about one a second, so several breathing cycles can be imaged within 1 min. This is important for studying diseases like asthma, in which local ventilation may change rapidly due to airway closure, as well as for the examination of less cooperative patients such as young children. In addition, investigations of physiological and pathophysiological processes and conditions can be performed without the application of a contrast agent which might itself alter the normal function of the lung. The advantages of local ventilation imaging have been previously discussed [19][20][21][22][23]. The novelty of this method Upper image and graph: patient with normal pulmonary function test Figure 3 Upper image and graph: patient with normal pulmonary function test. On the left, a MR ventilation image is shown with the 6 ROIs (in different colours) used for ventilation measurement, on the right are the ventilation graphs which show the ventilation (= ml air/ml lung parenchyma) in 50 images for each ROI during the respiratory cycles. The 50 measurements span a total of one minute. The colours of the graphs match the colours of the ROIs in the ventilation image to differenciate the 6 lung regions. The ventilation is similar in each of the ROIs. Note the tiring of the young patient (maximal in-and expiration at the beginning only). Ventilation measurements: Right: upper field (turquoise) 0.64 ml/cm 3 ; middle field (violet) 0.68 ml/cm 3 ; lower field (brown) 0.65 ml/cm 3 . Left: upper field (yellow) 0.67 ml/cm 3 ; middle field (pink) 0.68 ml/cm 3 ; lower field (blue) 0.62 ml/cm 3 . Middle image and graph: patient with cystic fibrosis. The total ventilation is markedly decreased compared to the healthy patient. Additionally, the different lung regions show a very different ventilation, poorest in the left middle field. Ventilation measurements: Right: upper field (turquoise) 0.27 ml/cm 3 ; middle field (violet) 0.17 ml/cm 3 ; lower field (brown) 0.3 ml/cm 3 . Left: upper field (yellow) 0.2 ml/cm 3 ; middle field (pink) 0.32 ml/cm 3 ; lower field (blue) 0.38 ml/cm 3  is the quantitative measurement of the ventilation which can even be calculated for each voxel.

One of the basic assumptions of the method presented in the paper is that the MR signal of the lung parenchyma changes during ventilation mostly due to the different air content. Significant changes in T2* due to influences like perfusion and others would therefore diminish the accuracy of the ventilation calculation. From previous studies of our group and others it is well known, that T2* is relatively long (about 19 ms) at 0.2 T [1] and the signal decay is flat during the short time of measurement. Therefore the assumption of a relatively robust (against small changes in T2*) signal measurement was made, knowing this possible source of error which made a phantom and clinical validation of the method necessary.

According to our data the ventilation values seem reliable as they correlate closely with the lung function study which is the "gold standard" of ventilation assessment. However, as shown in figure 3, at high vital capacities MR ventilation may slightly underestimate the ventilation measured by global lung function tests. This problem may be caused by the slice thickness which in patients with a high vc should in future studies probably be adjusted to the thorax diameter to image as much of the lung as pos-sible. Up to now the algorithm for morphing the lung works by matching the boundaries only. Therefore regions that expand different in the slice direction may be under-or overestimated. However the ventilation measured in the different fields is not dependent on the posterior-anterior (pa) expansion as it is measured in ml air per ml parenchyma. Therefore regions that expand more will have a higher ventilation regionally as seen in the lower lung fields. The overall ventilation however may be affected as it was calculated using the mean thorax diameter. In a future step more precise measurements of the different thorax expansions in the pa direction could overcome this problem.

At this early stage of the study, the image transformation was, in part, done manually. For registration and ventilation mapping, one image was selected on which to perform the further computational steps. At this point a critical observation of the results by the investigator is necessary to check the plausibility of the registration process. In future, automated image selection and processing should be performed easily. By imaging multiple slices, 3D ventilation maps could also be achieved in the near future. In conclusion, the method presented here has the potential to become a major improvement of pulmonary assessment for clinical purposes as well as for research.  T. Rupprecht was the initiator of the study and wrote the ventilation map tool. He had great part in data interpreta-Ventilation map images Figure 4 Ventilation map images. One image selected from the ventilation map video. Increase in air content is coded red (inspiration); decrease is coded green (expiration). In image b and c note the artifacts in the region of the diaphragm which occur secondary to the registration process which registers the lungs only. However, the lung is still clearly outlined. a. healthy person in inspiration. Note the homogeneous contribution of air in inspiration. b. patient with cystic fibrosis. Note the multiple ventilation defects (black areas) and the poor overall ventilation (patchy ventilation pattern and little colour coded areas). c. patient with mycoplasma pneumonia. Despite normal global lung function a large ventilation defect (Circled black area) is noted in the right lower field where conventional imaging shows a pneumonic infiltrate. d. patient with asthma and good fev1 in the pulmonary function test. Despite good fev1 this patient may require more efficient treatment as there is still an impairment of local ventilation peripherally and in the left lower field (arrows). tion and preparation of the manuscript. M. Zapke, and HG. Topf were responsible for patient recruitment, performed the patient investigations, the data acquisition, postprocessing and interpretation as well as the preparation of the manuscript. R. Kuth, M. Deimling and P. Kreisler had part in the sequence modelling and hard-and software acquisition. M. Rauh had part in the phantom design. C. Chefd'hotel and B. Geiger programmed the registration tool.

Additional material

.
Bottom Graph: Correlation of MR ventilation and vital capacity measured by conventional pulmonary function test (r = 0,8; p ≤ 0,001). Black lines = regression line and 95% confidence interval.

Table 2 :
2MRI ventilation measurements.Measurement of the local ventilation in 6 ROIs by MRI. The ventilation is given as ml air per ml lung parenchyma. Note the differences of local ventilation for different groups of patients. For comparison FVC and VC of the conventional pulmonary function test. FVC% = forced vital capacity in % of the expected. VC (%) = vital capacity in % of the expected.Lung region/Diagnosis
All patients
Healthy
Asthma
CF

Right upper field (ml/ml)
0.38 ± 0.15
0.52 ± 0.18
0.43 ± 0.14
0.31 ± 0.13
Right middle field (ml/ml)
0.39 ± 0.14
0.53 ± 0.16
0.44 ± 0.13
0.32 ± 0.12
Right lower field (ml/ml)
0.41 ± 0.14
0.62 ± 0.10
0.45 ± 0.14
0.35 ± 0.12
Left upper field (ml/ml)
0.37 ± 0.15
0.50 ± 0.14
0.42 ± 0.15
0.31 ± 0.13
Left middle field (ml/ml)
0.38 ± 0.13
0.51 ± 0.18
0.41 ± 0.13
0.33 ± 0.10
Left lower field (ml/ml)
0.41 ± 0.14
0.65 ± 0.11
0.43 ± 0.13
0.36 ± 0.11
Mean (ml/ml)
0.39 ± 0.13
0.55 ± 0.12
0.43 ± 0.13
0.33 ± 0.11
Mean FVC (%)
81 ± 18
93 ± 13
89 ± 12
67 ± 11
Mean VC (%)
80 ± 18
93 ± 13
87 ± 13
67 ± 20

Table 1 :
1Comparison of ventilation measurements.Conventional pulmonary function measurements in liters and percent of the predicted compared to the ventilation measured by MRI in liters. Mean values ± standard deviation. VC = vital capacity; FVC = forced vital capacity; FEV1 = forced expiratory volume in 1 secondDiagnosis/Ventilation
VC (L)
VC (%)
FVC (L)
FVC (%)
FEV1 (L)
FEV1 (%)
MR ventilation (L)

Healthy
2.33 ± 0.08
92.7 ± 12.7
2.29 ± 0.92
93 ± 13.9
1.98 ± 2.33
96.5 ± 21.8
2.29 ± 0.24
Asthma
2.65 ± 1.19
86.9 ± 13.3
2,68 ± 1.21
89.8 ± 11.8
2,39 ± 1.03
97 ± 14.1
2,51 ± 1.45
CF
2.51 ± 1.11
66.9 ± 20.3
2.44 ± 1.05
67.1 ± 18.9
1.7 ± 0.85
57.5 ± 25.9
2.86 ± 1.46
Other lung disease
2.21 ± 0.79
79.4 ± 16.8
2.2 ± 0.78
80.9 ± 17.5
2.05 ± 0.75
89.8 ± 21.7
2.07 ± 1.09
Other disease
1.87 ± 1.58
63.2 ± 6.3
1.87 ± 1.58
67.9 ± 9.4
1.78 ± 1.7
68.3 ± 5.2
2.02 ± 1.59
All
2.49 ± 1.08
79.5 ± 18.1
2.49 ± 1.08
81.4 ± 17.9
2.12 ± 0.96
84.3 ± 25.6
2.49 ± 1.38

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Competing interestsAuthors Rupprecht and Zapke are owners of a pending pct patent application and interested in contacting potential licensees.The remaining authors declare that they have no competing financial interest.Authors' contributions and acknowledgementsWe thank Prof. Dr. W. Rascher for his support, L. Fiedler and M. Jakobi for the patient investigations, L. Naehrlich and T. Zimmermann for patient recruitment.Publish with Bio Med Central and every scientist can read your work free of charge
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Correlation of Wnt5a expression with histopathological grade/stage in urothelial carcinoma of the bladder

Ramiro Malgor
Seth Crouser
Danielle Greco
Colin Brockett
Karen Coschigano
Masato Nakazawa
Scott Jenkinson
Correlation of Wnt5a expression with histopathological grade/stage in urothelial carcinoma of the bladder
R E S E A R C H Open Access
Background: Bladder cancer, including urothelial carcinoma (UC), is the most common malignancy of the urinary tract and the fourth most frequent cancer overall in men. Wnt5a, a member of the Wnt family of proteins, has been shown to have contradictory roles in the pathogenesis of many cancers, acting either as tumor suppressor or tumor promoter. The objective of this study was to investigate the expression and role of Wnt5a in the pathogenesis of UC and suggest possible clinical applications for diagnosis, prognosis and treatment. Methods: We characterized the expression of Wnt5a in 33 human UC samples using immunohistochemistry. The samples were obtained via transurethral resection, immediately fixed in formalin and then embedded in paraffin. The correlation between Wnt5a immunoreactivity, histological grade, and pathological stage of the tumor was analyzed. The expression of Wnt5a mRNA as well as the effect of Wnt5a on cell migration was also evaluated in two UC cell lines, T24 and J82, and a normal urothelial cell line.Results: Our immunohistochemical results revealed that Wnt5a staining intensity correlated positively with the histological grade and pathological stage of the UC. Wnt5a mRNA expression differed widely in the three urothelial cell lines, with high levels in one carcinoma cell line and low levels in the other cell line in comparison to the normal urothelial cell line. Migration increased in both UC cell lines in response to Wnt5a treatment. Conclusions: Our results show that the Wnt5a pathway may play a role in the pathogenesis of UC and suggest that Wnt5a may serve as an additional, complementary diagnostic/prognostic marker for UC. Virtual slide: http://www.diagnosticpathology.diagnomx.eu/vs/1952312091979566

Background

Urinary bladder cancer is the fourth most frequent cancer overall in men in developed countries [1] and the most common malignancy of the urinary tract [2,3]. Worldwide, 297,338 new cases and 112,255 deaths due to bladder cancer in males were reported in 2008 [3]. In the United States, it is estimated that there will be 54,610 new cases of bladder cancer and 10,820 deaths in 2013 [4]. Approximately 95% of the tumors arising in the bladder originate in the urothelium, resulting in urothelial carcinoma (UC). Squamous cell carcinoma and adenocarcinoma are the other major forms of malignant tumors in the bladder.

Two important biological features of UC are its recurrence and its progression from superficial to invasive tumors. Approximately 50-65% of patients with noninvasive UC develop a recurrent tumor within 5 years after the first treatment [3]. A majority of tumors at pTa stage are low grade and less than 5% of the tumors in this group will progress to a higher stage. In contrast, most of the tumors at pT1 pathological stage, which include tumors with invasion into the lamina propria, are high grade; 30-50% of the tumors in this group will progress to a higher stage [1,2]. These features make UC challenging in clinical practice in relation to diagnosis, prognosis, treatment, or follow-up for each individual patient.

Wnt proteins are a group of secreted glycoproteins that play critical physiological roles during embryonic development, regulating cell proliferation, morphology, motility and fate [5]. Aberrant Wnt signaling has been implicated in pathological conditions such as cancer and inflammatory diseases [6][7][8][9][10]. The canonical or βcatenin dependent signaling pathway is well recognized pathway in the Wnt family and is involved in normal cell growth and differentiation as well as in cancer. In the context of bladder cancers the hypermethylation of Wnt antagonist genes such as Wnt inhibitory factor 1 (WIF1), mutations in adenomatous polyposis coli (APC) and aberrant expression of β-catenin have been reported to be associated with increased aggressiveness and poor prognosis [11][12][13][14][15]. Recently, epigenetic deregulation of Wnt pathway inhibitors has been implicated in abnormal activation of the canonical Wnt signaling pathway in bladder tumors [16]. All of these findings demonstrated the probable role of the canonical Wnt signaling pathway in the pathogenesis of UC of the bladder.

Wnt5a is a member of the Wnt family that belongs to a non-canonical/non-transforming signaling pathway. The non-canonical signaling involves numerous cellular pathways, all of them β-catenin-independent; however, based on the specific Wnt receptors present, Wnt5a can inhibit or promote β-catenin dependent signaling, which results in contradictory roles of Wnt5a in cancer [17]. Wnt5a has been described as a tumor promoter and a tumor suppressor for different malignancies [6,17]. It has been implicated in cancer progression as a potent enhancer of cell motility and invasiveness for malignant melanoma [18]. Up-regulation of Wnt5a has been observed in lung, stomach, colon, breast, pancreas and prostate cancer as well [7,19,20]. The opposite function for Wnt5a, as a tumor suppressor, has been described in hematopoietic, brain, thyroid and colorectal cancers [21][22][23]. Specifically, Wnt5a has been shown to act as a tumor suppressor for colorectal carcinoma by antagonizing canonical Wnt/β-catenin signaling [23].

The role of Wnt5a in the pathogenesis/progression of UC has not been fully elucidated [14,15]. Olson et al. reported the role of Wnt5a as a tumor suppressor gene in UC because ectopic expression of human Wnt5a in a UC cell line lacking the chromosomal region where Wnt5a resides abolished the cell's tumorigenic capacity [24]. Despite efforts to clarify the role of the non-canonical Wnt signaling pathway, and Wnt5a in particular, in the pathogenesis of UC, much is still unknown.

The aim of this study was to investigate the expression of Wnt5a protein in human UC. To accomplish this, we examined the expression of Wnt5a by immunohistochemistry (IHC) in 33 formalin-fixed, paraffin-embedded (FFPE) human UC samples. We found a significant positive correlation between Wnt5a expression and the histological grade and pathological stage of the tumor. Using in vitro methods, we also found that Wnt5a may be involved in the migration of malignant UC cells, which could have implications regarding the invasiveness of the tumor.

Materials and methods

Human urothelial carcinoma tissue specimens Samples from 33 patients collected at the time of diagnostic/therapeutic transurethral resection and diagnosed as urothelial carcinoma of the bladder were included in this study. FFPE tissue blocks were archived at the University Medical Associates -Pathology Department (UMA-Pathology lab, Athens, OH). Ethical approval for the study was obtained from the Ohio University Institutional Review Board (IRB 07E112).

The diagnosis and classification of the 33 samples were performed according to the WHO/ISUP consensus classification system and the American College of Surgeon's Cancer Program Standards. Hematoxylin and eosin (H&E) stains were used for diagnosis and staging of the tumors. Pathological stage was determined by the degree of invasion into the lamina propria. Histological grade was defined based on architecture, polarity, thickness, and cohesiveness, as well as cytologic features including pleomorphism, chromasia, presence of nucleoli, mitosis and umbrella cells.

Immunohistochemistry FFPE tissue specimens were immunostained for Wnt5a using a Wnt5a polyclonal antibody. For each case, two consecutive 4 μm sections were mounted onto Superfrost glass slides. Sections were deparaffinized followed by antigen retrieval using 10 mM citrate buffer, pH 6.0, at 90°C for 30 minutes. Endogenous peroxidase activity was blocked with 3% H 2 O 2 in phosphate buffered saline (PBS). Endogenous biotin and avidin were blocked using the Streptavidin/Biotin Blocking Kit (Vector Laboratories, Inc., Burlingame, CA). Rabbit polyclonal antibody against human Wnt5a (Santa Cruz Biotechnology, Santa Cruz, CA) was applied to one of the two sections at 4 μg/ml diluted in 1% bovine serum albumin (BSA), in PBS. As an isotype control, normal rabbit IgG (Invitrogen, Grand Island, NY) was applied to the other section at the same concentration. Slides were incubated overnight at 4°C in a humidified chamber. A peroxidase-based visualization kit, Universal LSAB™ + Kit/HRP, Rabbit/Mouse/Goat, was subsequently used according to the manufacturer's protocol (Dako North America, Inc., Carpinteria, CA). Briefly, after three washes, the slides were incubated with the biotinylated secondary antibody for 20 minutes, washed three times, incubated with streptavidin-HRP for 20 minutes, developed with 3,3′-diaminobenzidine (DAB) chromogen (Sigma, St. Louis, MO) for 3 minutes, and counterstained with hematoxylin. Wnt5a staining was scored as the intensity of staining in tumor cells (ignoring staining in surrounding non-tumor tissue) on a scale of 0 (no staining) to 3 (high intensity) by two independent observers. Cases with discrepant scores were re-evaluated jointly until agreement was reached.

Cell culture HTB-1™ (J82) and HTB-4™ (T24) urothelial carcinoma cell lines (ATCC, Manassas, VA) were cultured in Eagle's Minimum Essential Medium and McCoy's 5a Medium Modified, respectively, according to ATCC recommendations. The T24 cell line, characterized as non-tumorigenic, was derived from a poorly differentiated, high histological grade, recurrent tumor. The J82 cell line, with tumorigenic capacity, was derived from a poorly differentiated, high grade, invasive UC tumor [25]. The normal urothelial cell (NUC) line (Lifeline Cell Technology, Walkersville, MD) was cultured in ProstaLife™ Prostate Epithelial Cell Culture Medium according to the manufacturer's recommendations. Control conditioned medium (cCM) was prepared using L cells (CRL-2648™, ATCC) grown in ATCC-formulated Dulbecco's Modified Eagle's medium plus 10% fetal bovine serum. Wnt5aconditioned medium (Wnt5aCM) was prepared using L Wnt-5A cells (CRL-2814™, ATCC) grown in Dulbecco's Modified Eagle's medium with 4 mM L-glutamine provided by ATCC and supplemented with 0.6 mg/ml G418 and 10% fetal bovine serum. For each conditioned medium, the cells were split 1:10 in culture medium (without G418) in 10 cm petri dishes and grown for 4 days. The medium was subsequently removed and sterilized by filtration (first batch of conditioned medium). Fresh culture medium (without G418) was added and cultured for 3 more days. The medium was removed again and sterilized as above (second batch of conditioned medium). The first and second batches were mixed 1:1 and kept frozen until needed.

Real time PCR

RNA was extracted from cells grown in 6-well plates using the RNeasy® Mini kit (Qiagen, Valencia, CA) following the manufacturer's protocol. One microgram of RNA from each sample was reverse transcribed to cDNA using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA). Real-time quantitative PCR was performed in duplicate for each sample using a genespecific Taqman probe, Taqman™ Gene Expression Master Mix, and a StepOnePlus™ Real-Time PCR System according to the manufacturer's protocol (Applied Biosystems, Foster City, CA). Wnt5a (Hs00180103_m1) and the following six potential housekeeping genes were assayed: HPRT (Hs 99999909), GAPDH (Hs99999905), ACTB (Hs99999903), B2M (Hs99999907), UBC (Hs00824723), and SDHA (Hs 00188166). The most stable housekeeping genes were selected for normalization purposes using the Normfinder algorithm as outlined by Andersen et al. [26]. After normalization, data were presented as the fold change of Wnt5a RNA expression in each UC cell line relative to the level of expression observed in the NUC cells.

Migration assay

Migration of T24 and J82 cells was qualitatively examined by scratch assay and then quantified using the Oris™ Cell Migration Assay kit (Platypus Technologies, LLC, Madison, WI) according to the manufacturer's protocol. For the scratch assay, T24 and J82 cells were grown to confluence. The monolayers were washed with PBS, a cross was scratched into the surface of each monolayer, and then the cells were incubated with either regular medium (RM) in which each cell line normally grew, or cCM or Wnt5aCM, prepared as described above. Cellular migration was observed and visually recorded at 24 h intervals.

For the Oris Cell Migration Assay, a 96-well plate was populated with silicone stoppers and cells were added to each well. When the cells were confluent, the stoppers were removed and the clear area defined as the area before migration. The cells were then incubated under four different conditions: RM, RM supplemented with recombinant Wnt5a (R&D Systems) at 100 ng/ml (rWnt5a), cCM or Wnt5aCM. The cells were allowed to grow for 24 hours and then migration was stopped by fixation with 10% formalin. Each well was digitally imaged and traced, with the migration area defined as the percentage of the previously clear area now occupied by cells after 24 hours of growth. The measurements were performed using Image-Pro® Plus (Media Cybernetics, Inc., Silver Spring, MD).

Statistical analysis

Logistic regression statistical analysis was performed to investigate the correlation between Wnt5a immunostaining and two variables, tumor histological grade and pathological stage. Cell migration was evaluated using t-tests to compare the effect of different treatments versus control. Statistical significance was tested at an alpha of 0.05. The software SPSS version 17 was used for data analysis (IBM SPSS, Armonk, NY).

Results

Wnt5a immunostaining increases with increasing histological grade and pathological stage of the tumor Wnt5a protein was diffusely expressed by, and largely confined to, tumor cells in all 33 samples (Figures 1, 2 and  3). Specificity of Wnt5a staining was demonstrated by the lack of staining in the isotype controls. Intensity of Wnt5a staining positively correlated with the histological grade of the tumor (Table 1). Of the 12 samples classified as noninvasive papillary UC of low grade, six samples (50%) were 1+ for Wnt5a staining, four samples (33%) were 2+, and only two samples (17%) were 3+. In contrast, of the 21 samples classified as high grade, including noninvasive and invasive UC, 20 cases (95%) were 2+ or 3+ and only one case (5%) was scored as 1+. Staining intensity predicted a binary dependent variable of tumor grade (odds ratio = 1.29 [IC95: 1.03~1.60], p = 0.033); an increase in staining intensity was associated with an increased odds ratio (OR) of 1.29. This effect of staining intensity was not moderated by the stage (interaction between intensity and stage, p = 0.14), indicating that intensity predicted the tumor grade regardless of the stage. In fact, the staining intensity predicted the tumor grade at every stage (OR at stages 1-3 = 1.43, 2.00, 1.70; ps < 0.01).

Intensity of Wnt5a staining also positively correlated with the pathological stage of the tumor ( Table 2). Of the cases with noninvasive disease (stage pTa), seven of 20 (35%) had a low score 1+; eight of 20 (40%) were 2+ and five of 20 (25%) scored 3+ for Wnt5a immonostaining. In contrast, of seven UC samples that had invasion into the lamina propria (stage pT1), five (71%) were 2+ and the remaining two (29%) were 3+. Further, of the five samples with invasion into detrusor muscle (stage pT2), one (20%) had a score of 2+ while the remaining four (80%) had a score of 3+. Statistical analysis showed that staining intensity predicts the tumor stage; the OR for the staining intensity effect was significant (OR = 4.37, p = 0.017). In other words, for one point increase in the staining score, the odds of the    Finally, correlation of stage, grade and Wnt5a staining of the UC samples was also assessed (Table 3). Not surprisingly, all 12 tumors showing invasive properties (pT1 or pT2) were also high grade and exhibited moderate to strong (2+ or 3+) Wnt5a staining. Interestingly, of the eight high grade, noninvasive tumors, only one (12.5%) had weak (1+) staining while seven (87.5%) had moderate to strong (2+ or 3+) Wnt5a staining.

Wnt5a mRNA expression differs widely between urothelial cell lines

Wnt5a mRNA expression was compared among three cells lines: a normal urothelial cell line (NUC) and two different urothelial carcinoma cell lines (J82 and T24). Interestingly, in comparison to the normal urothelial cell line, Wnt5a mRNA expression was increased more than 3-fold in the J82 cell line but decreased 10-fold in the T24 cell line (Figure 4).

Exogenously applied Wnt5a results in different migration rates of UC cell lines

Scratch assays showed that application of Wnt5a in the medium appears to increase the migration rates for both J82 and T24 UC cell lines, with more dramatic results for the faster growing T24 cell line ( Figure 5). To validate and quantify these results, we repeated the experiment using an Oris Cell Migration Assay kit ( Figure 6). In comparison to regular and controlconditioned media, application of Wnt5a-conditioned medium significantly increased migration of T24 cells. Addition of recombinant Wnt5a instead of conditioned medium had little effect on T24 migration. In contrast,   addition of recombinant Wnt5a nearly doubled the migration rate for J82 cells, although the difference did not reach statistical significance. Addition of Wnt5a-con ditioned medium had no significant effect.

Discussion

Urinary bladder cancer is the fourth most frequent cancer in men in the world today [1][2][3]. Due to its great plasticity and biological variability with respect to multifocality, recurrence, and invasion comportment, it is difficult to predict the behavior of an initially noninvasive UC [2,3]. This feature makes the diagnosis of UC challenging, not only for its early detection, but also for accurate prediction of tumor recurrence and progression.

Multiple biomarkers used for other cancers have been described with potential diagnostic or prognostic value for UC as well, including p53, cytokeratin 20, E-cadherin, Ki67, CD44 and survivin [27,28]. Currently a combination of these immunohistochemical biomarkers assayed within panel is the best way to characterize subtypes and predict the behavior/aggresiveness of UC [28]. More recently, other promising biomarkers for UC have been reported. In a large retrospective exploratory study, expression of microRNA-100 was negatively associated with stage, recurrence, prognosis and death of patients with bladder cancer [29]. In another large study, the cell surface zincdependent metalloprotease CD10 was strongly correlated with tumor grade and stage and possibly associated with tumor progression in bladder cancer pathogenesis [30]. In contrast to initial studies correlating increased COX-2 expression and recurrence of urinary bladder cancer, a large study focused on non-muscle invasive bladder cancer found that lower levels of COX-2 and tumor-infiltrating RM cCM Wnt5aCM  lymphocytes were predictive of recurrence, suggesting the need of close follow-up and adjuvant therapy for these patients [31]. In the current study Wnt5a protein expression by malignant cells was observed in all 33 samples included in the study; however, intensities, and hence protein levels, varied, correlating with both grade and stage and suggesting that Wnt5a may also serve as a biomarker of UC. To prove the predictive nature of Wnt5a as a diagnostic or prognostic biomarker of UC, further investigation into the relationship between Wnt5a expression by the tumor and clinical progression of the disease in a large number of patients, is required. Expression of Wnt5a by UC tumor cells may also be a predictor of an aggressive subgroup of UC. We found that weak Wnt5a expression was predominantly seen in low grade UC samples and all were in a noninvasive (pTa) stage. This suggests that low Wnt5a expression may be indicative of non-aggressive tumors. In contrast, moderate to strong Wnt5a expression was seen in all three pathological stages, but was usually associated with high grade, high stage tumors. Thus, moderate to strong expression of Wnt5a is likely to indicate an aggressive tumor or transformation to an invasive phenotype. In support of this hypothesis previous studies have reported the role of Wnt5a as a pro-angiogenic gene [32,33] and also the importance of the Wnt signaling pathway in epithelial-mesenchymal transition (EMT) of cancer [34]. In addition, Huang CL et al. reported the association of Wnt5a with tumor proliferation in non-small-cell lung cancer (NSCLC); the authors concluded that overexpression of Wnt5a could increase aggressiveness in NSCLC [35].

The present study also assessed Wnt5a mRNA expression in two UC cell lines, both from high grade, poorly differentiated tumors. Interestingly, the expression differed significantly between them, with one of the cancer cell lines expressing much higher levels and the other expressing much lower levels of Wnt5a mRNA in comparison to the normal urothelial cell line. This result is similar to the result published many years ago by Bui et al. in which they described different Wnt5a mRNA expression levels for different UC cell lines [36]. In that study the authors suggested that Wnt5a may modulate cell shape and cell migration [36].

In support of a role of Wnt5a in cell migration, Wnt5a has been associated with migration ability in melanoma [18]. Our group previously reported constitutive Wnt5a expression in human pancreatic cancer and malignant melanoma cell lines and suggested the role of Wnt5a in growth and migration in both of these cancer cell lines [19]. In this study we investigated migration response to exogenously applied Wnt5a in the two UC cell lines. We found that the T24 cell line, which has a low level of Wnt5a transcription, showed a significant increase in migration rate while J82, with high Wnt5a transcription, did not significantly respond to the application of Wnt5a. It is possible that J82, with high Wnt5a RNA, is already maximally saturated by Wnt5a and cannot respond further, while T24, with low Wnt5a RNA, is submaximally saturated and thus capable of responding to exogenous Wnt5a. Alternatively, it is possible that different cell lines have different responses to Wnt5a due to expression of different Wnt5a receptors. It is well known that the interaction between Wnt ligands and their receptors determine the signaling that will be activated, and multiple receptors may respond to Wnt5a signaling, each leading to activation of different downstream signaling pathways and effects [17,37,38]. Therefore, different responses might be associated with the presence of different receptors for Wnt5a ligand in each tumor cell line.

Conclusion

In conclusion, our results support previous work suggesting that the Wnt5a signaling pathway plays a pathological role in UC. The correlation of Wnt5a protein expression in UC tissue sections with histological grade and pathological stage of the tumor suggests its possible use as diagnostic/prognostic tool for UC. Further studies to investigate association between Wnt5a expression, tumor behavior and clinical outcome are necessary to fully validate the utility of Wnt5a for early diagnosis/prognosis of UC. Further studies are also needed to clarify the underlying mechanisms connecting Wnt5a and different tumor behavior. These investigations promise to deliver predictability for a relatively unpredictable cancer.

Figure 1 Figure 2
12Histological grade and pathological stage were determined in all 33 samples of human UC included in the study. The samples were diagnosed as noninvasive papillary UC of low grade (12 samples), noninvasive papillary UC of high grade (8 samples) or invasive UC (13 samples, all high grade). For pathological stage of the disease, 20 of 33 cases were in pTa, 7 in pT1, 5 in pT2, and one could not be determined. Wnt5a expression in three cases of low grade, noninvasive, papillary urothelial carcinoma as assessed by IHC. (A) H&E staining; (B) Wnt5a immuno-staining showing slight reactivity; (C) isotype control (all at × 200). Wnt5a expression in three cases of high grade urothelial carcinoma as assessed by IHC. (Top row) Noninvasive urothelial carcinoma (pTa stage); (middle row) a case with lamina propria invasion (pT1 stage); (bottom row) a case with muscle invasion (pT2 stage); (A) H&E staining; (B) Wnt5a immuno-staining showing strong reactivity; (C), isotype control (all at × 200).

Figure 3
3Wnt5a expression in three cases of high grade, invasive urothelial neoplasms (pT2 stage) as assessed by IHC. (A) H&E staining at low magnification shows deep invasion areas in the bladder wall (×40); (B) H&E staining (×200); (C) Wnt5a immune-staining showing strong reactivity (×200); (D) isotype control (×200).

pTa: non invasive; pT1: invasion to the lamina propria; pT2: invasion of the detrusor muscle; N.D.: could not be determined. * 1+ weak; 2+ moderate; 3+ strong. sample being at a more advanced stage increased by 4.37 [95% CI: 1.43-16.74].

non-invasive; pT1: invasion to the lamina propria; pT2: invasion of the detrusor muscle; N.D.: could not be determined. * 1+ weak; 2+ moderate; 3+ strong.

Figure 4
4Wnt5a mRNA expression in a normal urothelial cell line (NUC) and two urothelial carcinoma cell lines, J82 and T24, as assessed by real time RT/PCR. The average fold change ± standard error (SE) for each cell line is shown in comparison to NUC after normalization with two different housekeeping genes, SDHA (left) and B2M (right).

Figure 5
5Application of Wnt5a-conditioned medium increases migration of T24 and J82 cell lines in scratch assays. Scratch assays are shown at time 0 (0 hours) and then 24 hours (T24) or 48 hours (J82) after the application of three different treatments: regular growth medium (RM), control-conditioned medium (cCM) and Wnt5a-conditioned medium (Wnt5aCM).

Figure 6
6Differing migration rates for T24 and J82 cell lines in response to exogenous Wnt5a. Average migration area ± SE was determined using the Oris Cell Migration Assay kit 24 hr after application of regular medium (RM), regular medium supplemented with recombinant Wnt5a at 100 ng/ml (rWnt5a), control-conditioned medium (cCM), or Wnt5a-conditioned medium (Wnt5aCM). (A) Migration rate for the T24 cell line; (B) migration rate for the J82 cell line. * p = 0.05; ** p = 0.022.

Table 1
1Correlation of Wnt5a staining intensity and histological grade of the tumors * 1+ weak; 2+ moderate; 3+ strong.Wnt5a staining intensity *

1+
2+
3+

Histological grade

Low grade
6
4
2
(n = 12)

High grade
1
1 0
1 0
(n = 21)

Table 2
2Correlation of Wnt5a staining intensity and pathological stage of the tumorsWnt5a staining intensity *

1+
2+
3+

Table 3
3Correlation of stage, grade and Wnt5a staining intensityStage^N
umber
of cases

Staining intensity for
low grade subset *

Staining intensity for
high grade subset *

pTa
20

6 (1+)
1 (1+)

4 (2+)
4 (2+)

2 (3+)
3 (3+)

Malgor et al. Diagnostic Pathology 2013, 8:139 http://www.diagnosticpathology.org/content/8/1/139
http://www.diagnosticpathology.org/content/8/1/139
AcknowledgementThis study was supported in part by an Ohio University Heritage College of Osteopathic Medicine Research & Scholarly Affairs Committee (RSAC) Award.Competing interestsThe authors declare that they have no competing interests.Authors' contributions RM conceived the project idea, provided funds, performed literature review, and drafted the majority of the manuscript. SC, DG and CB collected data, reviewed literature and drafted portions of the manuscript. KC analyzed and interpreted data and critically revised the manuscript. MN performed statistical analysis and reviewed the manuscript. SJ provided cases and reviewed the manuscript. All authors read and approved the final manuscript.
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Correlation of Wnt5a expression with histopathological grade/stage in urothelial carcinoma of the bladder. Malgor, Diagnostic Pathology. 8139Cite this article asCite this article as: Malgor et al.: Correlation of Wnt5a expression with histopathological grade/stage in urothelial carcinoma of the bladder. Diagnostic Pathology 2013 8:139.