Skip to main content

Assessment of cardiac amyloidosis with 99mTc-pyrophosphate (PYP) quantitative SPECT

Abstract

Background

99mTc-PYP scintigraphy provides differential diagnosis of ATTR cardiomyopathy (ATTR-CM) from light chain cardiac amyloidosis and other myocardial disorders without biopsy. This study was aimed to assess the diagnostic feasibility and the operator reproducibility of 99mTc-PYP quantitative SPECT.

Method

Thirty-seven consecutive patients who underwent a 99mTc-PYP thorax planar scan followed by SPECT and CT scans to diagnose suspected ATTR-CM were enrolled. For the quantitative SPECT, phantom studies were initially performed to determine the image conversion factor (ICF) and partial volume correction (PVC) factor to recover 99mTc-PYP activity concentration in the myocardium for calculating the standardized uptake value (SUV) (unit: g/ml). SUVmax was compared among groups of ATTR-CM, AL cardiac amyloidosis, and other pathogens (others) and among categories of Perugini visual scores (grades 0–3). The intra- and inter-operator reproducibility of quantitative SPECT was verified, and the corresponded repeatability coefficient (RPC) was calculated.

Results

The ICF was 79,327 Bq/ml to convert count rate in pixel to 99mTc activity concentration. PVC factor as a function of the measured activity concentration ratio in the myocardium and blood-pool was [y = 1.424 × (1 − exp(− 0.759 × x)) + 0.104]. SUVmax of ATTR-CM (7.50 ± 2.68) was significantly higher than those of AL (1.96 ± 0.35) and others (2.00 ± 0.74) (all p < 0.05). SUVmax of grade 3 (8.95 ± 1.89) and grade 2 (4.71 ± 0.23) were also significantly higher than those of grade 1 (1.92 ± 0.31) and grade 0 (1.59 ± 0.39) (all p < 0.05). Correlation coefficient (R2) of SUVmax reached 0.966 to 0.978 with only small systematic difference (intra = − 0.14; inter = − 0.23) between two repeated measurements. Intra- and inter-operator RPCs were 0.688 and 0.877.

Conclusions

99mTc-PYP quantitative SPECT integrated with adjustable PVC factors is feasible to quantitatively and objectively assess the burden of cardiac amyloidosis for diagnosis of ATTR-CM.

Background

Cardiac amyloidosis is related to the pathogen that the primary interstitial protein deposition occurs in the extracellular space of the myocardium, leading to impairment of myocardial wall contractility, systolic/diastolic dysfunction, arrhythmia, and eventually heart failure to cause high morbidity and mortality [1]. Main types of cardiac amyloidosis include monoclonal immunoglobulin light chain (AL) and transthyretin amyloidosis cardiomyopathy (ATTR-CM), of which ATTR-CM can be subtyped by pathogenic mutations in the transthyretin gene (ATTRm) or by the accumulation of amyloid fibrils composed of wild-type transthyretin protein (ATTRwt) [2,3,4]. In all different types of cardiac amyloidosis, the incidence rate varies between 5 and 13 per million per year [5,6,7,8,9,10]. Differential diagnosis of cardiac amyloidosis is often challenging. The most reliable approach to diagnose AL cardiac amyloidosis depends on blood and urine tests [11]. The traditional standard for diagnosis of cardiac ATTR amyloidosis relies on echocardiography (ECG) or cardiac magnetic resonance (CMR) along with that the deposit of cardiac amyloidosis should also be proved in an endomyocardial biopsy coupled with immunohistochemistry or mass spectroscopy [12, 13]. Nuclear medicine imaging can help to differentiate ATTR-CM from AL cardiac amyloidosis and other myocardial disorders without the need of biopsy. Positron emission tomography (PET) with β-amyloid-specific imaging tracers such as 18F-florbetapir, 18F-flutemetamol, and 11C-PIB enables the quantitative scheme to evaluate cardiac amyloidosis [14,15,16]. However, this quantitative imaging tool is not yet ready for routine clinical utilization. In recent years, systematic evaluation of the scintigraphy with 99mTc-labeled phosphate tracers (e.g., technetium-99m 3, 3-diphospho-1, 2-propanodicarboxylic acid (99mTc-DPD), technetium-99m pyrophosphate (99mTc-PYP), or 99mTc-hydroxymethylene diphosphonate (99mTc-HMDP)) has been reported as an outstanding non-invasive imaging tool to distinguish ATTR-CM from AL cardiac amyloidosis with excellent performance in differential diagnosis (sensitivity 84–97%, specificity 94–100%) [17,18,19]. Although the scintigraphy with 99mTc-labeled phosphate tracers has demonstrated its effectiveness for diagnosis of ATTR-CM, there still exist relevant limitations in further identifying subgroups who may present different prognosis [20, 21]. The method of quantitative single-photon emission computed tomography (SPECT) has recently been developed to provide the quantitative assessment of amyloid burden adjunct to the visual interpretation of planar images. Several studies have further confirmed that quantitative SPECT possesses a potential in diagnosis of ATTR-CM independently [22,23,24]. The aim of our study is set to report the feasibility and the reproducibility of 99mTc-PYP quantitative SPECT in differential diagnosis of cardiac amyloidosis when SPECT images were reconstructed with full physical corrections, and the correction for partial volume effect to recover true activity concentration in the myocardium was integrated into the quantitation process.

Methods

Study cohorts

Between December 2018 and December 2019, thirty-seven consecutive patients underwent a 99mTc-PYP thorax planar scan followed by SPECT and CT scans to diagnose suspected ATTR-CM. For each study subject, routine examinations were carried out to record comprehensive clinical data accordingly. This study was complied with the amended Declaration of Helsinki approved by the Institutional Review Board of Peking Union Medical College Hospital. All participants provided the informed written consent. According to the previous research study [18], patients were divided into three groups primarily based on clinical features, immunohistochemical or proteomics typing of amyloid, ECG, Perugini visual scores, genetic analyses, and biopsy as the clinical routine for assessment of cardiac amyloidosis. Diagnosis of ATTR-CM included abnormal ECG finding and suggestive amyloidosis by visual grading of 99mTc-PYP planar images equal to 2 or 3 with absence of a detectable monoclonal protein despite serum/urine immunofixation electrophoresis (IFE) and serum free light chain (sFLC) assay. Group A, ATTR-CM (n = 6), was based on clinical examination, ECG finding, positive 99mTc-PYP finding in planar images with Perugini visual scores ≥ 2, and absence of abnormal serum/urine (IFE and sFLC). This diagnostic criterion identified one patient with ATTRwt and five patients with ATTRm. Heterogenous types of TTR mutations included Val50Gly (n = 1), Val50Met (n = 1), Gly73Glu (n = 1), Asp38Asn (n = 1), and Ala117Ser (n = 1). Group B, AL-CM (n = 10), was solely determined according to the presence of abnormal serum/urine (IFE or sFLC) as in lambda (λ)-light chain type (n = 7) and kappa (κ)-light chain type (n = 3). Group C, others (n = 21), is disqualified to fit into the diagnostic criteria of group A and group B. Several of them were ATTR mutation carriers from family history (n = 13) such as Ala117Ser (n = 7), Val50Met (n = 3), Ser97Tyr (n = 2), and Asp38Asn (n = 1) by genetic analyses but without evidence of showing the burden of cardiac amyloidosis. The remaining patients included hypertrophic cardiomyopathy (n = 2) and idiopathic cardiomyopathy (n = 5). Patient characteristics of these three groups are listed in Table 1.

Table 1 Patient characteristics

Phantom experiment

For image quantitation, the experiment to derive the image conversion factor (ICF) to convert pixel value in quantitatively reconstructed SPECT images to 99mTc activity concentration was initially conducted by filling ~ 740 MBq of 99mTc water solution into a cylindrical phantom (radius 16 cm, height 20 cm). ICF was then calculated by the 99mTc true activity concentration divided by pixel value. To note, ICF maintains a constant value when physical interference from attenuation, scatter, and statistical noise can be fully addressed in reconstructed images. To access partial volume effect (PVE) in the myocardium (Myo), a standard cardiac insert phantom (Data Spectrum Corporation, Hillsborough, NC, USA) representing a three-dimensional model of the left ventricle containing regions of the myocardial wall (~ 110 ml) and ventricle (~ 60 ml) was then utilized to measure PVE and to derive partial volume correction (PVC) factor under various activity concentration ratios (ACRs) of Myo and blood-pool (BP) in the ventricle cavity (0.15 to 10.0). PVE specified by the level of erroneous activity concentration was defined by the measured activity concentration divided by the true activity concentration in Myo. As reported, the degree of PVE considered as a function of wall thickness and Myo/BP ACR remains approximately a constant level in the circumstance that Myo/BP ACR is over a certain threshold, and inversely, it rises rapidly with the decreased Myo/BP ACR [25]. The unique property of PVE provides an opportunity to derive and fit the PVC factor (1.0/PVE) as an analytic function of Myo/BP ACR to recover the true activity concentration for the relatively unchanged wall thickness. In this study, acquisition parameters of SPECT scans for the phantom experiment were identical to those used in the patient scanning protocol as indicated in the next section.

Image data acquisition

Each study subject was intravenously injected with a ~ 740-MBq 99mTc-PYP dose prepared by Beijing SHIHONG Pharmaceutical Center and calibrated by a radioactivity meter (CRC-25R, CAPINTEC, USA). Relevant parameters including injection dose, time, and site were properly recorded. Post the 99mTc-PYP injection for 1 h, a planar scan was performed in anterior and left lateral views for 10 min and then followed by a SPECT scan in the thorax position on a dual-head SPECT camera (Discovery 630, GE Healthcare, Haifa, Israel). The SPECT camera consists of low-energy high-resolution collimator with 9.53 mm thickness of NaI(Tl) scintillation crystal. With patient’s heart positioned in the center field of view, planar images were acquired for a total of 750,000 counts with 256 × 256 matrix and 1.46 zoom factor. Imaging parameters for SPECT acquisition utilized 128 × 128 matrix, circular orbit (radius 30 cm), 180° arc, step-and-shoot, 30 steps at 40 s/step, zoom = 1.0, and multiple energy windows (126–154 keV and 109–125 keV). After the completion of SPECT acquisition, a low-dose free-breathing CT scan (120 keV, 35 mA, 12 s) was separately acquired on a dedicated PET/CT scanner (Sinounion Polar Star m660, Beijing, China) for attenuation correction of SPECT images and image fusion. The patient positioning between two scans was optimally consistent to avoid non-translational misregistration.

Image processing of quantitative SPECT

In this study, image reconstruction and data analysis of quantitative SPECT were performed using a cardiac software package (MyoFlowQ, Taipei, Taiwan). This software incorporates image reconstruction and subsequent image analysis on a single platform to measure 99mTc or 99mTc-PYP activity concentration in regions of myocardial wall and ventricle cavity. For the quantitative image reconstruction of SPECT, projection data were pre-corrected for 99mTc isotope decay according to time points of rotation angles, and reconstructed by ordered subsets expectation maximization (OSEM) (4 iterations, 12 subsets) with full physical corrections for photon attenuation, scatter, collimator resolution, and Poisson count statistics as described previously [26,27,28]. Prior to the quantitative image reconstruction, a rapid image reconstruction with filtered back-projection (FBP) was preliminarily executed to provide quick SPECT images for the assessment of registration with CT images. SPECT-CT misregistration was verified visually and manually corrected by applying 3D translation to SPECT images. In the phantom experiment, a consistent region of interest (ROI) was drawn on SPECT images of the cylindrical phantom to count rate in pixel (unit: counts/second/pixel) to 99mTc activity concentration (Bq/ml). To measure myocardial activity of the cardiac insert phantom, SPECT images were manually reoriented into the short-axis view. A threshold of 25% of peak activity was chosen to effectively differentiate between myocardial and ventricle regions. The myocardial centerline contour was automatically detected and refined by using an ellipsoid-approximated geometry with manually determined mitral valve plane to create the polar map. A consistent sampled region (1.0 × 1.0 × 2.0 cm3) was automatically placed in ventricle to measure the activity concentration of BP. PVC factor defined as the true 99mTc activity concentration divided by the measured 99mTc activity concentration from quantitative SPECT was presented in the scatter plot (y-axis = PVC factor, x-axis = measured Myo/BP ACR) and regressed with an exponential recovery model to derive analytic PVC factor as a function of measured Myo/BP ACR [29]. For the analysis of patients’ 99mTc-PYP SPECT images, the same processing steps, including image reorientation, myocardial centerline contour, creation of polar map, and the placement of sampled region in ventricle cavity, were performed identically to those processing steps of cardiac insert phantom. Under the situation when the determination of myocardial centerline contour failed due to ultralow or no uptake of 99mTc-PYP in the myocardium, a ROI (1.0 × 1.0 × 1.0 cm3) was manually placed in the insertion point between left and right ventricles on a transaxial plane of reconstructed images as the located joint of apex in the right ventricle with the apical septal of left ventricle. Post the recovery to absolute 99mTc-PYP uptake using PVC factor derived from the phantom experiment, standardized uptake value (SUV) was calculated with factors of injected 99mTc-PYP dose and patient’s body weight.

Interpretation of planar images and semi-quantitative measurement

Both anterior and lateral views of 99mTc-PYP planar images were evaluated by two consensus nuclear readers in nuclear cardiology to grade using the visual grading rule reported by Perugini et al. as follows: grade 0 = cardiac uptake not visible, grade 1 = mild cardiac uptake visible but inferior to skeletal uptake, grade 2 = moderate cardiac uptake visible equal to or greater than skeletal uptake, and grade 3 = strong cardiac uptake with little or no skeletal uptake. The semi-quantitative analysis of planar images was performed by drawing a patient-specific circular ROI on the heart and mirroring it to the contralateral chest in order to calculate the heart-to-contralateral (H/CL) ratio from the quotient of the mean counts [17].

Measurement of intra- and inter-operator reproducibility

Correlations of image processing for semi-quantitative and quantitative parameters by the 1st operator (OP1) and the 2nd operator (OP2) were verified by linear regression. OP1 had 20 years of experience in image processing of nuclear cardiology, and OP2 encompassed 3 years of experience. To test the intra-operator reproducibility, OP1 processed all image data twice in 4 weeks apart. To test the inter-operator reproducibility, OP2 processed the same image datasets independently.

Statistics analysis

All datasets were analyzed with a statistical software package (IBM SPSS Statistics version 25). Continuous variables were presented as mean ± SD, whereas categorical variables were expressed as actual numbers and percentage. For the comparison between study subgroups, differences in continuous variables were analyzed using the one-way ANOVA with post hoc Bonferroni correction when Levene’s pre-test for homogeneity of variances meets the requirement; otherwise, the one-way Welch ANOVA with post hoc Games-Howell correction was applied. Differences in categorical variables were analyzed using the χ2 test or Fisher exact test. The correlation of H/CL ratio and quantitative parameter (SUVmax) from OP1 and OP2 was obtained by the linear regression. Difference of correlation coefficient between two measurements was tested by the Z test. Bland-Altman statistics were utilized to verify the systematic difference with a 95 % confidence interval (CI) for semi-quantitative and quantitative parameters. The repeatability coefficient (RPC) representing intra- and inter-operator reproducibility was calculated as RPC = 1.96 × SD of difference between the two measurements [30]. All p values used were two sided with p < 0.05 considered statistically significant.

Results

Phantom experiment

Through the cylindrical phantom experiment, the ICF to convert the pixel value to the corresponded activity concentration in quantitative SPECT images was 79,327 Bq/ml per cps/pixel. Activity concentrations in Myo and BP regions were measured in the unit of becquerels per milliliter and then applied to derive PVC factor. Experimental data points of Myo/BP ACR and corresponded PVC factors were (0.315, 0.149), (0.324, 0.194), (0.428, 0.334), (0.967, 0.334), (0.967, 0.646), (1.136, 0.720), (1.307, 0.796) (1.464, 0.906), (1.858, 1.026), (2.571, 1.097), (3.903, 1.198), (6.952, 1.291), and (10.28, 1.367). Figure 1a shows the scatter plot of PVC factor vs the measured Myo/BP ACR. While the data of scatter plot were further fitted with an exponential recovery model, a strong correlation coefficient (R2) as 0.998 was observed to generate an analytic curve as: y = a × (1 − exp(− b × x)) + c, where parameters a, b, and c were 1.424, 0.759, and 0.104, respectively. In the curve, the PVC factor stayed as a constant (1.31) when the measured Myo/BP ACR was ≥ 4.0 (PVC = 1.260 as 95.4% of 1.31), and it declined dramatically below the turning point.

Fig. 1
figure1

a PVC factor to recover as a function of measured activity concentration ratio (ACR) in Myo and BP regions. b Measured Myo/BP ACR and corresponded PCV factor for individual study subject

99mTc-PYP image findings

Image findings of planar and quantitative SPECT for diagnosed ATTR-CM, AL cardiac amyloidosis, and others are summarized in Table 2. In group A diagnosed as ATTR-CM, 66.7% had Perugini scores = 3 and 33% for Perugini visual scores = 2 while 100% of group B diagnosed as AL cardiac amyloidosis had Perugini visual scores = 1. In group C diagnosed by other pathogens, Perugini visual scores were dispersed from 0 to 2. From 99mTc-PYP planar images, H/CL ratio of group A (1.98 ± 0.29) was significantly higher than those of group B (1.28 ± 0.16) and group C (1.38 ± 0.19) (p < 0.0001). From 99mTc-PYP quantitative SPECT, the measured Myo/BP ACR ranges from 0.665 to 5.542 to give PVC factor from 0.46 to 1.30 (Fig. 1b). With the recovery of activity concentration in the myocardium for all study subjects using PVC factor derived from the cardiac phantom experiment, SUVmax of group A (7.50 ± 2.68 g/ml) was also significantly higher than those of group B (1.96 ± 0.35) and group C (2.00 ± 0.74) (all p < 0.05). Similar findings were observed for SUVmedian and SUVmean as listed in Table 2. Figure 2 shows the box plots of H/CL ratio, SUVmax, SUVmedian, and SUVmean for the pathological groups. From the semi-quantitative analysis of 99mTc-PYP planar images, grades 0 and 1 had significantly lower H/CL ratio (1.29 ± 0.81 and 1.34 ± 0.18) than grades 2 and 3 (1.78 ± 0.21 and 2.06 ± 0.29). Furthermore, there was no significant difference between either grades 0 and 1 or grades 2 and 3 (all p < 0.05). From 99mTc-PYP quantitative SPECT, SUVmax of grade 3 (8.95 ± 1.89 g/ml) and grade 2 (4.71 ± 0.23) were significantly higher than those of grade 1 (1.92 ± 0.31) and grade 0 (1.59 ± 0.39) (all p < 0.05). Additionally, neither difference between grades 3 and 2, nor difference between grades 1 and 0 was significant. Findings of planar and quantitative SPECT categorized by Perugini visual scores (grades 0 to 3) are summarized in Table 3 and plotted in box plots in Fig. 3. Figure 4 shows representative patients with planar images acquired in anterior and lateral views to measure H/CL ratio and corresponded quantitative SPECT images to derive SUVmax in the myocardium.

Table 2 99mTc-PYP findings from planar and quantitative SPECT
Fig. 2
figure2

The box plots of H/CL ratio, SUVmax, SUVmedian, and SUVmean among ATTR-CM (group A), AL cardiac amyloidosis (group B), and others (group C)

Table 3 99mTc-PYP findings from planar and quantitative SPECT/CT images for groups divided by Perugini visual scores
Fig. 3
figure3

The box plots of H/CL ratio, SUVmax, SUVmedian, and SUVmean among groups of Perugini visual scores (grades 0–3)

Fig. 4
figure4

Representative images of 99mTc-PYP planar and quantitative SPECT. a Grade = 3 in Perugini visual scores with H/CL ratio = 2.10 and SUVmax = 10.64 g/ml in b. c Grade = 2 with H/CL ratio = 1.87 and SUVmax = 4.74 g/ml in d. e Grade = 1 with H/CL ratio = 1.39 and SUVmax = 1.90 g/ml in f. e Grade = 0 with H/CL ratio = 1.20 and SUVmax = 1.98 g/ml in h

Intra- and inter-operator reproducibility

Figure 5 shows the linear regression and Bland-Altman plots of H/CL ratio and SUVmax from the OP1 who processed 99mTc-PYP planar and quantitative SPECT images twice in 4 weeks apart. The linear regression demonstrated that excellent corrections existed for OP1 to process H/CL ratio (R2 = 0.861) and SUVmax (R2 = 0.978) repeatedly. Differences in correlation coefficients for either H/CL ratio or SUVmax (Z scores = − 3.921, p < 0.0001) were significant. From the Bland-Altman plots, mean difference of H/CL was 0.06 (95% CI = − 0.18–0.30) and determined as − 0.14 (95% CI = − 0.82–0.55) for SUVmax. Values of the intra-operator RPC for H/CL ratio and SUVmax were 0.241 and 0.688 g/ml, respectively. Figure 6 shows the linear regression and Bland-Altman plots of H/CL ratio and SUVmax from OP1 and OP2 who processed 99mTc-PYP planar and quantitative SPECT images independently. The linear regression demonstrated that excellent correlation also existed for OP1 and OP2 to process H/CL ratio (R2 = 0.811) and SUVmax (R2 = 0.966). Differences in correlation coefficients for H/CL ratio and SUVmax were significant (Z scores = − 0.3716, p = 0.0002). From the Bland-Altman plots, mean difference of H/CL was − 0.05 (95% CI = − 0.23–0.33) and determined as − 0.23 (95% CI = − 1.11–0.65) for SUVmax. Values of the inter-operator RPC for H/CL ratio and SUVmax were 0.280 and 0.877 g/ml.

Fig. 5
figure5

Linear regression and Bland-Altman plots of H/CL ratio and SUVmax measured by OP1 who processed the same image sets in 4 weeks apart

Fig. 6
figure6

Linear regression and Bland-Altman plots of H/CL ratio and SUVmax measured by OP1 and OP2 who processed the same image sets independently

Discussion

We initially conducted the phantom study to obtain the ICF for quantitative SPECT and to derive PVC factor for recovering true activity concentration in the myocardium. To note, the PVC factor described by fitting parameters (a, b, c) in the exponential recovery function can only be transferable to the same camera system with the matched set of imaging parameters (e.g., matrix and pixel size). To obtain PVC factor for different camera models, dissimilar sets of imaging parameters, or both, the described phantom experiment and data fitting process should be reperformed to warrant an appropriate recovery function. Indeed, the unique characteristic of PVC factor curve as a function of the measured Myo/BP ACR elucidated that the impact to the myocardium coming from the activity in surrounded area is rather a constant, but varied depending on Myo/BP ACR. To resolve this issue is particularly important for 99mTc-PYP quantitative SPECT as the diagnosis for ATTR-CM must rely on accurate activity measurement. Nonetheless, the solution is not yet applicable in current commercial software packages, therefore hampering 99mTc-PYP quantitative SPECT as a clinical utility [23, 24]. In our study with a majority of patients (29/37) presenting low Myo/BP ACR, we found PVC factor varied in a large range from 0.46 to 1.30 (Fig. 1b). By using individual’s adjustable PVC factor based on the recovery curve, we found SUVmax, SUVmedian, and SUVmean were able to differentiate the ATTR-CM group from groups of AL cardiac amyloidosis and others. For the same cohorts further categorized by Perugini visual scores, SUVmax, SUVmedian, and SUVmean were able to distinguish groups of grades 2 and 3 from grades 0 and 1. 99mTc-PYP quantitative SPECT integrated with adjustable PVC factors is therefore feasible to quantitatively assess the burden of cardiac amyloidosis for diagnosis of ATTR-CM. In our study, we further evaluated the reproducibility of 99mTc-PYP quantitative SPECT. The intra- and inter-reproducibility of the quantitative method were excellent as R2 reached 0.902 to 0.978 with only small systematic difference (intra = − 0.14 to − 0.06; inter = − 0.23 to − 0.11) between two repeated measurements. Both intra- and inter-reproducibility outperformed that of the semi-quantitative method (R2 0.811–0.861, all p < 0.0267). 99mTc-PYP quantitative SPECT developed in this study can be a reproducible and reliable method to measure quantitative parameters (e.g., SUV). To our knowledge, this is the first study to provide the relevant information.

The most widely used gage for 99mTc-PYP scintigraphy for differentiating ATTR-CM from AL cardiac amyloidosis is developed by Perugini via a visual comparison of the myocardium to ribs [20]. Although Perugini visual scoring method is simple and straightforward to implement clinically, the downside of this method is still marked as highly subjective among readers [31]. The semi-quantitative analysis with H/CL has been developed to improve the objectivity effectively. However, the method still suffered from low subjectivity by the manual drawing of ROI on myocardial and CL regions. Under the circumstance of intense extra-cardiac uptake or background, the diagnostic certainty of both methods can no longer be preserved [32]. As proposed, absolute quantitation of myocardial uptake using quantitative SPECT provides a solution to improve objectivity and reliability for 99mTc-PYP scintigraphy [23]. In our study, we demonstrated that the quantitative SPECT integrated with adjustable PVC factors is useful as not only a savior to visual interpretation on planar images suffering from intense extra-cardiac uptake or myocardial uptake overlapped with blood-pool or bone, but also a quantitative and objective imaging method to measure the burden of amyloid deposit in the myocardium. Related patient examples are shown in Fig. 4.

Previous studies reported that images produced by 99mTc-labeled phosphate tracers (e.g., 99mTc-DPD, 99mTc-PYP, 99m Tc-HMDP) are not actually identical for the diagnosis of ATTR-CM [33]. The pattern of increased SUVmax in the group of grade = 3 vs the group of grade = 2 by Perugini visual scores was observable for 99mTc-PYP, but not for 99mTc-DPD or 99m Tc-HMDP [24]. This exceptional difference may provoke an additional value in prognosis for high grade of ATTR-CM with 99mTc-PYP quantitative SPECT. Recently, quantitative PET with bone scan agent, 18fluorine-labeled sodium fluoride (18F-NaF), was evaluated for the diagnosis of ATTR-CM, but not quite promising [34]. Quantitative PET with β-amyloid-specific imaging tracers such as 18F-florbetapir, 18F-flutemetamol, and 11C-PIB enabled the quantitative scheme to evaluate cardiac ATTR amyloidosis [14,15,16]. However, this PET quantitative imaging tool for diagnosis with a potential in prognosis of AL amyloidosis is not yet ready for routine clinical utilization [35]. As 99mTc-labeled phosphate tracers are widely available, quantitative SPECT can be valuable for the diagnosis for ATTR-CM and potentially for the prognosis. Moreover, it can provide a quantitative tool to monitor the disease progression for individual with ATTR mutation carriers from family history who does not yet present clinically relevant symptoms. It also enables quantitative assessment of treatment response to proven therapy as well as helpful in conducting trials of new therapeutic agents.

Study limitations

In this study, only a limited sample size for the ATTR-CM (n = 6) group was available. This limitation restricted to further statistically differentiate the group of Perugini visual scores = 3 from the group of Perugini visual scores = 2 by using the quantitative parameter, SUVmax, although the pattern was observable as shown in our data. Future study should focus to resolve this limitation by increasing the sample size of the ATTR group. Another limitation is that no prognosis data were available. Whether SUVmax or the heterogeneity of SUVmax can provide better prognosis than Perugini visual scores or H/CL ratio cannot be answered by this study. Other related technical limitation may be addressed by SPECT and CT data acquired on separate scanners. When non-translational misregistration between SPECT and CT images (e.g., rotational misregistration) may occur, the current program cannot compensate to correct for the type of error. Nonetheless, in our study, no study subject actually showed non-translational misregistration when careful patient positioning between SPECT and CT scans was carried out. Other limitation may be addressed that this study only validated the inter- and intra-operator reproductivity for the quantitative SPECT with a single 99mTc-PYP scan, and did not provide relevant data to verify the reproductivity among multiple 99mTc-PYP scans on the same cohort.

Conclusions

99mTc-PYP quantitative SPECT integrated with adjustable PVC factors is feasible to quantitatively and objectively assess the burden of cardiac amyloidosis for diagnosis of ATTR-CM.

Availability of data and materials

The datasets used and/or analyzed during the current study were available from corresponding author on reasonable request.

Abbreviations

ACR:

Activity concentration ratio

AL:

Light chain amyloidosis

ATTR:

Amyloid transthyretin

ECG:

Echocardiography

EMB:

Endomyocardial biopsy

FBP:

Filtered back-projection

H/CL:

Heart-to-contralateral

HFpEF:

Heart failure with ejection fraction

ICF:

Image conversion factor

IFE:

Immunofixation electrophoresis

IVS:

Interventricular septal

LVEF:

Left ventricle ejection fraction

LVPW:

Left ventricular posterior wall

OSEM:

Ordered subsets expectation maximization

PET:

Positron emission tomography

PVC:

Partial volume correction

PYP:

Pyrophosphate

RPC:

Repeatability coefficient

sFLC:

Serum free light chain

SPECT:

Single-photon emission computed tomography

SUV:

Standardized uptake value

99mTc:

99mTechnetium

References

  1. 1.

    Fontana M, Corovic A, Scully P, Moon JC. Myocardial amyloidosis: the exemplar interstitial disease. JACC Cardiovasc Imaging. 2019;12:2345–56. https://doi.org/10.1016/j.jcmg.2019.06.023.

    Article  PubMed  Google Scholar 

  2. 2.

    Strouse C, Briasoulis A, Fonseca R, Jethava Y. Approach to a patient with cardiac amyloidosis. J Geriatr Cardiol. 2019;16:567-574. doi:10.11909/j.issn.1671-5411.2019.07.010.

  3. 3.

    Rapezzi C, Quarta CC, Riva L, Longhi S, Gallelli I, Lorenzini M, et al. Transthyretin-related amyloidoses and the heart: a clinical overview. Nat Rev Cardiol. 2010;7:398–408. https://doi.org/10.1038/nrcardio.2010.67.

    CAS  Article  PubMed  Google Scholar 

  4. 4.

    Maurer MS, Hanna M, Grogan M, Dispenzieri A, Witteles R, Drachman B, et al. Genotype and phenotype of transthyretin cardiac amyloidosis: THAOS (transthyretin amyloid outcome survey). J Am Coll Cardiol. 2016;68:161–72. https://doi.org/10.1016/j.jacc.2016.03.596.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Pinney JH, Smith CJ, Taube JB, Lachmann HJ, Venner CP, Gibbs SD, et al. Systemic amyloidosis in England: an epidemiological study. Br J Haematol. 2013;161:525–32. https://doi.org/10.1111/bjh.12286.

    Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Tanskanen M, Peuralinna T, Polvikoski T, Notkola IL, Sulkava R, Hardy J, et al. Senile systemic amyloidosis affects 25% of the very aged and associates with genetic variation in alpha2-macroglobulin and tau: a population-based autopsy study. Ann Med. 2008;40:232–9. https://doi.org/10.1080/07853890701842988.

    CAS  Article  PubMed  Google Scholar 

  7. 7.

    Jacobson DR, Alexander AA, Tagoe C, Buxbaum JN. Prevalence of the amyloidogenic transthyretin (TTR) V122I allele in 14 333 African-Americans. Amyloid. 2015;22:171–4. https://doi.org/10.3109/13506129.2015.1051219.

    CAS  Article  PubMed  Google Scholar 

  8. 8.

    Ruberg FL, Berk JL. Transthyretin (TTR) cardiac amyloidosis. Circulation. 2012;126:1286–300. https://doi.org/10.1161/CIRCULATIONAHA.111.078915.

    Article  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Gonzalez-Lopez E, Gallego-Delgado M, Guzzo-Merello G, de Haro-Del Moral FJ, Cobo-Marcos M, Robles C, et al. Wild-type transthyretin amyloidosis as a cause of heart failure with preserved ejection fraction. Eur Heart J. 2015;36:2585–94. https://doi.org/10.1093/eurheartj/ehv338.

    CAS  Article  PubMed  Google Scholar 

  10. 10.

    Castano A, Narotsky DL, Hamid N, Khalique OK, Morgenstern R, DeLuca A, et al. Unveiling transthyretin cardiac amyloidosis and its predictors among elderly patients with severe aortic stenosis undergoing transcatheter aortic valve replacement. Eur Heart J. 2017;38:2879–87. https://doi.org/10.1093/eurheartj/ehx350.

    Article  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Zhang CL, Feng J, Shen KN, Su W, Huang XF, et al. The diagnostic and prognostic values of serum free light chain in patients with primary light chain amyloidosis. Zhonghua xueyexue zazhi. 2016;37:942–5. https://doi.org/10.3760/cma.j.issn.0253-2727.2016.11.003.

    CAS  Article  PubMed  Google Scholar 

  12. 12.

    Satoskar AA, Efebera Y, Hasan A, Brodsky S, Nadasdy G, Dogan A, et al. Strong transthyretin immunostaining: potential pitfall in cardiac amyloid typing. Am J Surg Pathol. 2011;35:1685–90. https://doi.org/10.1097/PAS.0b013e3182263d74.

    Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Vrana JA, Gamez JD, Madden BJ, Theis JD, Bergen HR 3rd, Dogan A. Classification of amyloidosis by laser microdissection and mass spectrometry-based proteomic analysis in clinical biopsy specimens. Blood. 2009;114:4957–9. https://doi.org/10.1182/blood-2009-07-230722.

    CAS  Article  PubMed  Google Scholar 

  14. 14.

    Park MA, Padera RF, Belanger A, Dubey S, Hwang DH, Veeranna V, et al. 18F-Florbetapir binds specifically to myocardial light chain and transthyretin amyloid deposits: autoradiography study. Circ Cardiovasc Imaging. 2015:8. https://doi.org/10.1161/CIRCIMAGING.114.002954.

  15. 15.

    Lee SP, Lee ES, Choi H, Im HJ, Koh Y, Lee MH, et al. 11C-Pittsburgh B PET imaging in cardiac amyloidosis. JACC Cardiovasc Imaging. 2015;8:50–9. https://doi.org/10.1016/j.jcmg.2014.09.018.

    Article  PubMed  Google Scholar 

  16. 16.

    Dietemann S, Nkoulou R. Amyloid PET imaging in cardiac amyloidosis: a pilot study using F-flutemetamol positron emission tomography. Ann Nuclear Med. 2019;33:624–8. https://doi.org/10.1007/s12149-019-01372-7.

    CAS  Article  Google Scholar 

  17. 17.

    Bokhari S, Morgenstern R, Weinberg R, Kinkhabwala M, Panagiotou D, Castano A, et al. Standardization of (99m)technetium pyrophosphate imaging methodology to diagnose TTR cardiac amyloidosis. J Nucl Cardiol. 2018;25:181–90. https://doi.org/10.1007/s12350-016-0610-4.

    Article  PubMed  Google Scholar 

  18. 18.

    Gillmore JD, Maurer MS, Falk RH, Merlini G, Damy T, Dispenzieri A, et al. Nonbiopsy diagnosis of cardiac transthyretin amyloidosis. Circulation. 2016;133:2404–12. https://doi.org/10.1161/CIRCULATIONAHA.116.021612.

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Cappelli F, Gallini C, Di Mario C, Costanzo EN, Vaggelli L, Tutino F, et al. Accuracy of 99mTc-hydroxymethylene diphosphonate scintigraphy for diagnosis of transthyretin cardiac amyloidosis. J Nucl Cardiol. 2019;26:497–504. https://doi.org/10.1007/s12350-017-0922-z.

    Article  PubMed  Google Scholar 

  20. 20.

    Perugini E, Guidalotti PL, Salvi F, Cooke RM, Pettinato C, Riva L, et al. Noninvasive etiologic diagnosis of cardiac amyloidosis using 99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid scintigraphy. J Am Coll Cardiol. 2005;46:1076–84. https://doi.org/10.1016/j.jacc.2005.05.073.

    Article  PubMed  Google Scholar 

  21. 21.

    Hutt DF, Fontana M, Burniston M, Quigley AM, Petrie A, Ross JC, et al. Prognostic utility of the Perugini grading of 99mTc-DPD scintigraphy in transthyretin (ATTR) amyloidosis and its relationship with skeletal muscle and soft tissue amyloid. Eur Heart J Cardiovasc Imag. 2017;18:1344–50. https://doi.org/10.1093/ehjci/jew325.

    Article  Google Scholar 

  22. 22.

    Ramsay SC, Lindsay K, Fong W, Patford S, Younger J, Atherton J. Tc-HDP quantitative SPECT/CT in transthyretin cardiac amyloid and the development of a reference interval for myocardial uptake in the non-affected population. Eur J Hybrid Imaging. 2018;2:17. https://doi.org/10.1186/s41824-018-0035-1.

    Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Caobelli F, Braun M, Haaf P, Wild D, Zellweger MJ. Quantitative (99m)Tc-DPD SPECT/CT in patients with suspected ATTR cardiac amyloidosis: feasibility and correlation with visual scores. J Nucl Cardiol. 2019. https://doi.org/10.1007/s12350-019-01893-8.

  24. 24.

    Ross JC, Hutt DF, Burniston M, Page J, Steeden JA, Gillmore JD, et al. Quantitation of (99m)Tc-DPD uptake in patients with transthyretin-related cardiac amyloidosis. Amyloid. 2018;25:203–10. https://doi.org/10.1080/13506129.2018.1520087.

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Hutton B, Osiecki A. Correction of partial volume effects in myocardial SPECT. J Nuclear Cardiol. 1998;5:402–13. https://doi.org/10.1016/s1071-3581(98)90146-5.

    CAS  Article  Google Scholar 

  26. 26.

    Hsu B, Chen FC, Wu TC, Huang WS, Hou PN, Chen CC, et al. Quantitation of myocardial blood flow and myocardial flow reserve with 99mTc-sestamibi dynamic SPECT/CT to enhance detection of coronary artery disease. Eur J Nuclear Med Mol Imag. 2014;41:2294–306. https://doi.org/10.1007/s00259-014-2881-9.

    CAS  Article  Google Scholar 

  27. 27.

    Hsu B, Hu LH, Yang BH, Chen LC, Chen YK, Ting CH, et al. SPECT myocardial blood flow quantitation toward clinical use: a comparative study with N-Ammonia PET myocardial blood flow quantitation. Eur J Nuclear Med Mol Imag. 2017;44:117–28. https://doi.org/10.1007/s00259-016-3491-5.

    CAS  Article  Google Scholar 

  28. 28.

    Ma R, Wang L, Wu D, Wang M, Sun X, Hsu B, et al. Myocardial blood flow quantitation in patients with congestive heart failure: head-to-head comparison between rapid-rotating gantry SPECT and CZT SPECT. J Nucl Cardiol. 2019. https://doi.org/10.1007/s12350-019-01621-2.

  29. 29.

    Abramowitz M. Handbook of mathematical functions with formulas, graphs, and mathematical tables. National Bureau of Standards Applied Mathematics Series 55. Tenth Printing. Engineering. 1972:1076.

  30. 30.

    Klein R, Hung GU, Wu TC, Huang WS, Li D, deKemp RA, et al. Feasibility and operator variability of myocardial blood flow and reserve measurements with 99mTc-sestamibi quantitative dynamic SPECT/CT imaging. J Nuclear Cardiol. 2014;21:1075–88. https://doi.org/10.1007/s12350-014-9971-8.

    Article  Google Scholar 

  31. 31.

    Sperry BW, Vranian MN, Tower-Rader A, Hachamovitch R, Hanna M, Brunken R, et al. Regional variation in technetium pyrophosphate uptake in transthyretin cardiac amyloidosis and impact on mortality. JACC Cardiovasc Imaging. 2018;11:234–42. https://doi.org/10.1016/j.jcmg.2017.06.020.

    Article  PubMed  Google Scholar 

  32. 32.

    Ramsay SC, Cuscaden C. The current status of quantitative SPECT/CT in the assessment of transthyretin cardiac amyloidosis. J Nuclear Cardiol. 2019. https://doi.org/10.1007/s12350-019-01935-1.

  33. 33.

    Rapezzi C, Gagliardi C, Milandri A. Analogies and disparities among scintigraphic bone tracers in the diagnosis of cardiac and non-cardiac ATTR amyloidosis. J Nucl Cardiol. 2019;26:1638–41. https://doi.org/10.1007/s12350-018-1235-6.

    Article  PubMed  Google Scholar 

  34. 34.

    Martineau P, Finnerty V, Giraldeau G, Authier S, Harel F, Pelletier-Galarneau M. Examining the sensitivity of 18F-NaF PET for the imaging of cardiac amyloidosis. J Nucl Cardiol. 2019. https://doi.org/10.1007/s12350-019-01675-2.

  35. 35.

    Slart R, Glaudemans A, Noordzij W, Bijzet J, Hazenberg BPC, Nienhuis HLA. Time for new imaging and therapeutic approaches in cardiac amyloidosis. Eur J Nucl Med Mol Imaging. 2019;46:1402–6. https://doi.org/10.1007/s00259-019-04325-4.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This work was sponsored by several funding sources: the CAMS initiative for innovative medicine (Grant No. CAMS-2018-I2M-3-001) and the National Key Research and Development Program of China (Grant Nos. 2016YFC0901500 and 2016YFC0901502).

Author information

Affiliations

Authors

Contributions

CR was responsible for the data acquisition and manuscript drafting. JR, ZT, YD, and ZZ assisted on the data acquisition. ZH assisted on the data analysis. WF and BH performed the data interpretation and the manuscript editing. LF, SZ, and LH contributed to the study design. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Bailing Hsu or Li Huo.

Ethics declarations

Ethics approval and consent to participate

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ren, C., Ren, J., Tian, Z. et al. Assessment of cardiac amyloidosis with 99mTc-pyrophosphate (PYP) quantitative SPECT. EJNMMI Phys 8, 3 (2021). https://doi.org/10.1186/s40658-020-00342-7

Download citation

Keywords

  • ATTR cardiomyopathy
  • 99mTc-PYP quantitative SPECT
  • Standardized uptake value
  • Diagnostic feasibility
  • The operator reproducibility
\