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Abstract

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Objective

To examine the significance of power Doppler sonography (PDS) in the diagnosis of synovial hypertrophy of the knee joint by verifying and comparing the PDS findings with histopathologic findings of synovial membrane vascularity.

Methods

The knee joints of 23 patients who were undergoing arthroplasty of the knee joint because of osteoarthritis or rheumatoid arthritis were examined with ultrasound before arthroplasty. The vascularity of the synovial membrane was classified semiquantitatively using PDS. A sample of synovial tissue was obtained during the arthroplasty, and the vascularity of the synovial tissue was evaluated by immunohistochemistry (factor VIII) and was graded qualitatively by a pathologist who was unaware of the PDS findings. The visual qualitative grading by the examiner was controlled by analyzing PDS images and histologic samples using a digital image evaluation system.

Results

The correlation between the qualitative PDS results and the qualitative grading of the vascularity by the pathologist was 0.89 by Spearman's ρ (P < 0.01). The Pearson correlation coefficient between the digital analysis of the PDS images and the digital analysis of the tissue sections was 0.81 (P < 0.01). Digital image analysis and qualitative grading by the examiner had a correlation of 0.89 by Spearman's ρ (P < 0.01) for the PDS images. The correlation between the qualitative estimation of vascularity by the pathologist and the digital image analysis was 0.88 by Spearman's ρ (P < 0.01).

Conclusion

In the present study, PDS proved to be a reliable diagnostic method for qualitative grading of the vascularity of the synovial tissue. In clinical practice, PDS allows further differentiation of the hypertrophic synovium.

Power Doppler sonography (PDS) was first introduced for cardiologic investigations in the 1980s (1, 2). Since it proved useful in cardiology, PDS was soon applied to other medical diagnostic problems (3–11). PDS characteristically encodes the amplitude of the power spectral density of the Doppler signal, rather than the mean Doppler frequency shift as in conventional color Doppler ultrasound methods (12). While conventional color Doppler sonography is well suited for evaluating high-velocity flow in large vessels, it is less effective in detecting low-velocity blood flow at the microvascular level (13–15). The value of PDS in the detection of soft tissue hyperemia was reported by Newman et al in 1994 (16). Recently, its value for estimating the fraction of moving blood in tissue was confirmed (17–19).

There are several studies on the visualization of the synovial membrane with PDS in osteoarthritis (OA) and rheumatoid arthritis (RA) (20–24), but to our knowledge, no study has been published which compares PDS findings and histopathologic findings of vascularity of the synovial membrane. The present study evaluated the correlation between PDS imaging of the vascularity of the knee joint synovial tissue and histopathologic inspection of the same tissue in order to assess the value of PDS in the imaging of synovitis.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Patients

We evaluated 23 patients (6 men, 17 women), with a mean age of 69 years (range 29–86 years). Ten patients fulfilled at least 4 of the 7 American College of Rheumatology (formerly, the American Rheumatism Association) criteria for RA (25); 13 had OA of the knee joint. All patients had severe knee pain and underwent total knee arthroplasty with synovectomy.

Ultrasound examination

A maximum of 12 hours prior to the operation, the knee joints were examined with an ultrasound real-time scanner (Elegra model; Siemens, Munich, Germany). Ultrasonography was carried out using a 7.5-MHz electronic linear transducer. Standardized anatomical section planes of the scans in the 3 recesses of the knee (suprapatellar and lateral and medial parapatellar) were used as prescribed by Rubaltelli et al (26). The synovial thickness of the suprapatellar recess was documented, as well as the presence of any effusion.

The synovial tissue was visualized using PDS in the suprapatellar recess of the knee joint (27) (Figure 1). Power Doppler settings were standardized with a pulse repetition frequency (PRF) of 1,100 Hz. Although greater low-flow sensitivity can be achieved at lower PRFs (9, 16, 28), the PRF was adjusted to 1,100 Hz to reduce flash artifact (4, 29). This setting worked well in all cases, although in some patients, a lower PRF would have been possible.

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Figure 1. Power Doppler sonography of the synovial membrane of the knee at the upper recesses. AOM = area of measurement and specimen of the synovial tissue; AOC = area of calibration.

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For optimum sensitivity, the PDS gain was set as suggested by Rubin and colleagues (17, 30). This requires manual elevation of the PDS gain-level until the color box is almost uniformly filled with the first indication of color and with only the minimum amount of the next highest signal just beginning to appear. This procedure can be performed either with the scan wiped clean of gel and contacting only air (6) or after applying the gel-covered transducer to the patient, at the depth of the region of interest (9), which in the present study, was the quadriceps muscle, just superior to the suprapatellar recess (Figure 1). This setting resulted in gains of 63–68 dB (8, 23, 29, 31). Using this method of adjustment (17), depth dependency, effects of blood pressure and medication, as well as heart rate and blood viscosity can be expected to have the same influence on the synovial tissue and the reference tissue of the quadriceps muscle and is therefore of minor importance for the measurement.

Two fully trained and experienced examiners (MW and SR) performed the sonography, which took 10–20 minutes for each patient. Neither examiner was aware of the clinical and laboratory findings in the patients.

Each knee was evaluated and graded on a scale of 1–4 according to the amount of the joint effusion and the thickness of the synovial tissue at the suprapatellar recesses (1 = no effusion/hypertrophic synovial tissue, 2 = mild effusion/hypertrophic synovial tissue, 3 = moderate effusion/hypertrophic synovial tissue, and 4 = marked effusion/hypertrophic synovial tissue).

Both investigators examined blood flow in the synovial tissue using the power Doppler mode. The power Doppler signal of the synovial membrane was graded on a scale of 1–4 as described by Newman et al (23) (1 = normal or minimal tissue perfusion, 2 = mild hyperemia, 3 = moderate hyperemia, and 4 = marked hyperemia), always in relation to the surrounding tissue of the quadriceps muscle (Figure 2). When the scores assigned by the 2 investigators did not match, the investigators examined the patient together and reached a consensus on the findings. The area of PDS was marked preoperatively using a waterproof pencil. The ultrasound examination was transferred to an S-VHS video system.

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Figure 2. Distinctive features of different grades of vascularity in frozen sections of synovial tissues stained with hematoxylin and eosin (HE) and with factor VIII (immunohistochemistry) and the corresponding power Doppler sonography (PDS) images. Patient numbers (nr.) correspond to those shown in Table 2.

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Histologic examination

Total knee arthroplasty with routine synovectomy was performed with the patient under spinal anesthesia and with a thigh tourniquet. During the procedure, the surgeon took a specimen of the synovial tissue from the suprapatellar recesses (Figure 1), exactly at the site where the PDS had been performed. Synovial tissue sections were stained with hematoxylin and eosin (H&E) and factor VIII (immunohistochemistry). The degree of vascularity was graded on a scale of 1–4 (1 = normal or minimal vascularity, 2 = mild vascularity, 3 = moderate vascularity, and 4 = marked vascularity) by a pathologist (VK) who was unaware of the PDS findings and the patient's clinical diagnosis (see Figure 2).

Digital image analysis of histology samples

Synovial tissue sections stained with H&E and with factor VIII (immunohistochemistry) were evaluated with the use of a microscope–television (TV) system, according to the procedure described by Krenn et al (32). The measurements (10–30/slide) were taken from different regions of interest in which there was good histologic quality of the synovial tissue, and the data were averaged. A Zeiss Axioplan microscope (Zeiss, Wetzlar, Germany) was used, and the stained sections were scanned with a Sony DXC 830b RGB color TV camera (Sony, Tokyo, Japan) and digitized by a Data Translation DT 2871 color frame grabber (Data Translation, Marlboro, MA).

The size of the images was 512 × 512 pixels, with a dynamic range of 8 bits per color channel and a spatial sampling density of 1.3 pixels/μm. The separation algorithms and calculations were performed on a DEC Alpha-433 Workstation (Digital, Santa Barbara, CA).

The brown-colored areas of interest in the tissue (blood vessels) were separated on the images according to the colorimetrics of the TV system (33) by using the differences between the color channels red (R), green (G), and blue (B). The color brown is represented as a “dirty orange,” which means that the red-yellow (orange) color contains a small proportion of blue. Therefore, the relationship R > G > B can be used to distinguish the blood vessels on the images from the surrounding tissue (34).

The average percentage of brown areas in relation to the whole area of the tissue sample is a measure of the vascularity in the section; this percentage was used for further analyses (see Figure 2).

Digital image analysis of PDS images

The S-VHS video tapes were digitized as bitmap-formatted images (24 bit). Representative screen shots of each examination were taken and analyzed for the PDS signal. The areas of calibration on the screen of the Siemens Elegra equipment were analyzed by color measurement (33) on the DEC Alpha-433 Workstation.

PDS does not allow a direct measurement of vascularity. A low level of PDS signal (dark red color) indicates a low number of moving red blood cells; a high number of moving red blood cells is indicated by a more yellow coloration. An increase in the number of detected blood cells leads to a shift from red to yellow in the color marking. The parts of the tissue with no detectable blood cells were gray or white.

The number of red-yellow pixels (R > G > B and B near zero) is a measure of blood flow. Since this number varies from zero to 10,000+, the results were quantified as shown in Table 1, according to the calibration procedure prescribed by Rubin et al (17) and the manufacturer's power Doppler distribution function algorithm.

Table 1. Quantification of red-yellow pixels as a measure of blood flow*
No. of red-yellow pixelsStage
  • *

    The number of red-yellow pixels is a measure of blood flow; this number varies from 0 to 10,000+. The results were quantified according to the manufacturer's power Doppler distribution function algorithm.

0–1000
101–5000.5
501–1,0001.0
1,001–1,5001.5
1,501–2,0002.0
2,001–2,5012.5
2,501–3,0003.0
3,001–5,0003.5
>5,0004

Statistical analysis

Our main interest was focused on the relationship between the PDS findings and histologic findings of tissue vascularity. In clinical practice, PDS interpretation will, in most cases, lead to qualitative statements. The assessment by the pathologist judging the vascularity of tissue is also qualitative. The relationship of both variables was analyzed using Spearman's rank correlation test.

In contrast, digital data processing ascribes a numerical value to the power Doppler signal as well as to the vascularity of the tissue. The relationship between these numerical scales was studied using Pearson's correlation test.

The correlation between the qualitative results and the absolute results of the digital image analysis of the PDS and of the tissue section was calculated using Spearman's rank correlation test in order to investigate the reliability of the visual interpretation of the tissue sections and the PDS images by the examiner.

Differences between data for the patients with OA and the patients with RA were investigated with the t-test (numerical variables) and the Mann-Whitney U test (qualitative variables).

RESULTS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

The characteristics of the study patients, the ultrasound findings including PDS, and the joint effusion, synovial thickness, and histologic findings are shown in Table 2. The correlation between the qualitative results of PDS and the pathologists' estimation of vascularity was 0.89 by Spearman's ρ (P < 0.01) (Figure 3).

Table 2. Clinical characteristics, medications, and PDS and histologic findings in the knee joint of the study patients*
Patient/ age/sexKneeClinical diagnosisDisease duration, yearsNo. of ACR criteriaQuantitative scoreQualitative scoreCRP, mg/dlBP, mm HgHeart rateCardioactive and antiinflammatory medication
Histology, mean ± SDPDSHistologyPDSEffusionSynovial proliferation
  • *

    Rheumatoid arthritis (RA) was assessed according to the number of American College of Rheumatology (ACR) criteria that were met. Osteoarthritis (OA) was determined according to clinical features. C-reactive protein (CRP) levels were determined on the day of power Doppler sonography (PDS). Blood pressure (BP) and heart rate were determined 10 minutes before PDS was performed. NSAID = nonsteroidal antiinflammatory drug; MTX = methotrexate; SSZ = sulfasalazine; ISDN = isosorbide dinitrate; ACE inhibitor = angiotensin-converting enzyme inhibitor.

1/59/FLRA12636 ± 123.02–33243.5155/7566NSAID, MTX
2/80/MLOA1525 ± 142.032220.1140/8575NSAID
3/70/FRRA25529 ± 182.52–32322.7160/8070NSAID, MTX, corticosteroids, SSZ
4/29/FRRA5432 ± 112.033331.9140/8068NSAID, MTX
5/66/FRRA23541 ± 123.043331.0140/8082NSAID
6/76/MROA817 ± 71.51–21–2310.0160/10078NSAID, ISDN
7/78/FRRA14529 ± 112.533230.7140/6080NSAID
8/75/MROA514 ± 90.51–21310.3140/9080NSAID
9/60/MROA710 ± 80.511221.1160/9085NSAID
10/78/FROA2716 ± 100.521110.7170/10088NSAID, ACE inhibitor
11/66/FLOA910 ± 31.511220.6160/9060NSAID, ACE inhibitor
12/52/FROA423 ± 92.52–32111.4145/9076NSAID
13/76/FRRA11641 ± 113.043–4445.8150/8079NSAID, MTX, corticosteroids
14/75/FROA1617 ± 100.522310.5140/7084ISDN
15/86/MRRA31733 ± 142.543332.4175/9078NSAID, calcium antagonist
16/77/FLOA318 ± 130.52–31–2120.6125/8080Paracetamol, ACE inhibitor
17/65/FLOA1517 ± 61.01–21–2121.4140/6068No medication
18/79/FLOA926 ± 183.033310.0160/9076ACE inhibitor
19/76/FROA833 ± 211.522212.0160/10080NSAID, ACE inhibitor
20/69/FRRA22545 ± 123.544341.2135/8074NSAID, ACE inhibitor
21/81/FLRA13642 ± 222.03–42–3221.6140/6064NSAID, ACE inhibitor
22/56/FRRA17554 ± 263.544231.7120/7076NSAID, MTX, corticosteroids
23/78/MROA1519 ± 122.022320.0150/8078ACE inhibitor
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Figure 3. Correlation between the qualitative estimates of blood flow by power Doppler sonography (PDS) and vascularity in the tissue section (Spearman's ρ = 0.89, P < 0.01).

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The visual estimation of vascularity based on PDS images and on tissue sections was compared with the results of digital image processing by Spearman's rank correlation test. The correlation between visual and digital interpretation of PDS was 0.89 by Spearman's ρ (P < 0.01) (Figure 4). The correlation of visual and digital analysis of the factor VIII–stained sections (immunohistochemistry) was 0.88 by Spearman's ρ (P < 0.01) (Figure 5). Both values support the reliability of the visual interpretation of the tissue sections and the PDS images by the examiner.

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Figure 4. Correlation between the visual (qualitative) interpretation of power Doppler sonography (PDS) images and PDS digital image processing (Spearman's ρ = 0.89, P < 0.01).

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Figure 5. Correlation between the visual and digital image analysis of factor VIII–stained tissue sections (Spearman's ρ = 0.88, P < 0.01).

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Pearson's correlation between the digital analysis of the PDS images and the digital analysis of the factor VIII–stained tissue sections was 0.81 (P < 0.01) (Figure 6).

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Figure 6. Correlation between the digital analysis of power Doppler sonography (PDS) images and digital analysis of factor VIII–stained tissue sections (Pearson's correlation coefficient r = 0.81, P < 0.01).

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We found a correlation between the thickness of the synovial membrane and the PDS signal (Spearman's ρ = 0.69, P < 0.01). Spearman's ρ for correlation of the thickness of the synovial membrane and vascularity in the tissue section was 0.64 (P < 0.01). There was no correlation between synovial proliferation and effusion (Spearman's ρ = 0.223, P = 0.31).

There was a significant increase in the power Doppler signal for the numerical PDS score (P < 0.01) as well as the qualitative grade (P < 0.01) in patients with RA. Digital (P < 0.01) and visual (P < 0.01) analysis of the immunohistochemistry sections showed a higher degree of vascularity in patients with RA, and hypertrophic synovium was more frequently found in patients with RA (P < 0.01). Effusion was found in both groups, but there was no significant between-group difference.

DISCUSSION

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Synovial proliferation is the fundamental event in rheumatoid joint lesions (35). Growth of fibroblast-like synoviocytes and metalloproteinase production by fibroblast-like synoviocytes contribute to cartilage and bone destruction associated with hypervascularized tissue containing fibroblastic elements referred to as pannus (36, 37). A joint affected by inflammatory tissue as seen in RA requires a specific treatment, such as disease-modifying drugs, local injection of corticosteroids, radionucleotide synoviorthesis, or synovectomy. Visualizing inflammatory tissue is therefore an important element in the diagnosis and monitoring of disease activity in RA.

So far, visualization of synovial tissue and synovial vascularity has been dominated by magnetic resonance imaging (MRI). The ability to differentiate between effusion and synovial proliferation by MRI has been greatly improved by the introduction of the intravenous application of paramagnetic contrast agents (38–44). Van Dijke et al (45) described a technique for measuring abnormal capillary permeability in synovial tissue of arthritic knees of rats, by use of dynamic MRI with an intravenous gadolinium-based blood pool agent. In that study, MRI-derived microvascular characteristics correlated positively with histologic findings. O'Byrne et al (46) compared MRI and histologic findings in a rabbit model of OA and immune arthritis. Those investigators reported that MRI can be used to observe the therapeutic effects of disease-modifying drugs on synovial inflammation and cartilage degradation in rabbit knees. Since enhancement of the synovium is time dependent, the sensitivity of MRI can be reduced by chemical shift artifacts (47). Consequently, for a detailed assessment of disease progression based on serial MRI examinations, precise timing and standardization of the MRI protocol are required (48, 49).

The value of PDS in detecting low-velocity blood flow at the microvascular level in several tissues has been demonstrated by Newman et al (16). Strouse et al (50) did not consistently find increased flow in their study of septic arthritis of the hip in children. Their investigations in a rabbit model confirmed their previous findings in children (24). In the latter study, only 23 of 45 examinations of infected knees were unequivocally positive by PDS examinations performed 1–6 days after inoculation. However, several groups of investigators have reported that ultrasound imaging of the synovial tissue is an objective and reliable technique (16, 21, 23, 28, 51–53).

Fiocco et al (21) compared conventional ultrasound imaging of synovial proliferation with arthroscopic visualization before and after synovectomy in patients with knee joint synovitis and found a significant correlation between clinical and ultrasound indices. Those authors concluded that sonography can be used as an objective method for monitoring response to therapy in patients with inflammatory knee joint diseases. Silvestri et al (54) used color Doppler to monitor the activity of RA in the knee joint and found a correlation between vascular findings and clinical symptoms.

In the present studies, effusion was found in patients with OA as well as in patients with RA, with no significant between-group differences. The correlation between the thickness of the synovial membrane, the PDS signal, and tissue vascularity is consistent with clinical experience; however, a thick synovial membrane or effusion does not necessarily mean that inflammation is present. There was no correlation between synovial proliferation and the presence of an effusion. Tissue debris, blood clots, and fibrin are known to mimic some ultrasound features of synovial proliferation (21), and these features can be excluded by PDS.

PDS reflects the movement of blood cells within a vessel; however, it does not always indicate increased vascularity or hyperemia of the synovium, which is still a problem in interpreting PDS images (55). PDS findings are influenced by the examiner, the machine, and the acoustical conditions involved in image processing. A sonographic evaluation of the arthritic joint should also be performed. PDS should be used to assist the clinician in determining whether the region of interest shows increased blood flow compared with other tissues (29). This information can be important in distinguishing between hypervascular and fibrous pannus. The value of PDS in the assessment of therapeutic response to the treatment of synovitis of the knee joint was shown by Newman et al (23), who reported a qualitative decrease in synovial perfusion visualized by PDS after intraarticular administration of steroids.

Our study is the first to correlate PDS findings with histologic findings in the synovial tissue, supporting the value of PDS in clinical practice, where the degree of vascularity can be graded according to PDS images. The best correlation was found when a 1–4 grading scale was used by both the sonographer in assessing PDS signals and the pathologist in assessing the degree of vascularity.

Although techniques of digitizing the images and analyzing blood vessels and PDS signals are automatically assumed to be a more accurate approach, this method can be influenced by technical artifacts. Fat cells with intensely colored cell membranes can mimic a high vascularity in the segmentation algorithms of the image analyzing software. Besides technical considerations, the cost of PDS investigations is of increasing concern in our health care systems. The results of the present study, however, indicate that PDS is a powerful tool in the evaluation and objective assessment of synovial tissue perfusion. PDS represents a readily available, easy to handle, and cost effective alternative to dynamic MRI with intravenous gadolinium-based contrast agent. In the future, the use of ultrasound contrast agents and harmonic imaging, both of which greatly enhance color flow sensitivity, may be shown to increase the potential utility of PDS.

In conclusion, PDS provides a reliable and accurate method for visualizing blood flow in the synovial tissue. The highly significant correlation between the PDS findings and the histologic findings supports the value of this technique. Since ultrasound is an easy to handle, safe, inexpensive, and noninvasive procedure that is available in most departments of rheumatology, PDS may continue to play an important role in the diagnosis and monitoring of musculoskeletal disorders.

Acknowledgements

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Thanks to Mrs. J. Pfeuffer for preparing the tissue sections, H. Schmitz, MD, for support in translating the manuscript, Mrs. J. Hinterberger for scanning the tissue sections in the microscope–TV system, and S. Kirschner, MD, for help with compiling the statistics.

REFERENCES

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES
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