Dynamic whole-body PET imaging: principles, potentials and applications

A novel method for the diagnosis of atherosclerosis based on nanotechnology

Cardiovascular disease (CVD) is a global health concern, presenting significant risks to human health. Atherosclerosis is among the most prevalent CVD, impacting the medium and large arteries in the kidneys, brain, heart, and other vital organs, as well as the lower limbs. As the disease progresses, arterial obstruction can result in heart attacks and strokes. Therefore, patients with atherosclerosis should receive accurate diagnosis and timely therapeutic intervention. With the advancements in nanomedicine, researchers have proposed new research strategies and methods for atherosclerosis imaging. This paper summarizes some current research findings on the use of nanomaterials in diagnosing atherosclerosis and offers insights for optimizing the imaging applications of nanomaterials in the future.

Application of Dynamic [18F]FDG PET/CT Multiparametric Imaging Leads to an Improved Differentiation of Benign and Malignant Lung Lesions

PURPOSE

To evaluate the potential of whole-body dynamic (WBD) 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography ([18F]FDG PET/CT) multiparametric imaging in the differential diagnosis between benign and malignant lung lesions.

PROCEDURES

We retrospectively analyzed WBD PET/CT scans from patients with lung lesions performed between April 2020 and March 2023. Multiparametric images including standardized uptake value (SUV), metabolic rate (MRFDG) and distribution volume (DVFDG) were visually interpreted and compared. We adopted SUVmax, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) for semi-quantitative analysis, MRmax and DVmax values for quantitative analysis. We also collected the patients' clinical characteristics. The variables above with P-value < 0.05 in the univariate analysis were entered into a multivariate logistic regression. The statistically significant metrics were plotted on receiver-operating characteristic (ROC) curves.

RESULTS

A total of 60 patients were included for data evaluation. We found that most malignant lesions showed high uptake on MRFDG and SUV images, and low or absent uptake on DVFDG images, while benign lesions showed low uptake on MRFDG images and high uptake on DVFDG images. Most malignant lesions showed a characteristic pattern of gradually increasing FDG uptake, whereas benign lesions presented an initial rise with rapid fall, then kept stable at a low level. The AUC values of MRmax and SUVmax are 0.874 (95% CI: 0.763-0.946) and 0.792 (95% CI: 0.667-0.886), respectively. DeLong's test showed the difference between the areas is statistically significant (P < 0.001).

CONCLUSIONS

Our study demonstrated that dynamic [18F]FDG PET/CT imaging based on the Patlak analysis was a more accurate method of distinguishing malignancies from benign lesions than conventional static PET/CT scans.

Glucose metabolic rate from four-dimensional [18F]FDG PET/CT to differentiate sarcoid lesions from malignant lesions

OBJECTIVES

On 18F-Fludeoxyglucose (FDG) PET/CT, active sarcoid lesions are often difficult to differentiate from malignant lesions. We investigated the potential of the glucose metabolic rate (MRglc, mg/min/100 mL), a new quantification of glucose metabolic kinetics derived from direct reconstruction based on linear Patlak analysis, to distinguish between sarcoidosis and malignant lesions.

MATERIALS AND METHODS

A total of 100 patients with cardiac sarcoidosis (CS) and 67 patients with cancer who underwent four-dimensional FDG PET/CT were enrolled. The lesions with a standardized uptake value (SUV) ≥ 2.7 on the standard scan were included as active lesions in the analysis. SUV and MRglc were derived using data acquired between 30 min and 50 min on four-dimensional FDG PET/CT. The mean value in the volume of interest (size 1.5 cm3) was measured. The diagnostic performance of sarcoidosis using MRglc and SUV was evaluated using receiver-operating-characteristic (ROC) analysis.

RESULTS

A total of 90 sarcoidosis lesions from 44 CS patients (18 males, 63.4 ± 12.2 years) and 87 malignant lesions from 57 cancer-bearing patients (32 males, 65 ± 14 years) were analyzed. SUV and MRglc for sarcoid lesions were significantly lower than those for malignant lesions (SUV, 4.98 ± 2.00 vs 6.21 ± 2.14; MRglc, 2.52 ± 1.39 vs 3.68 ± 1.61; p < 0.01). ROC analysis indicated that the ability to discriminate sarcoid patients from those with malignancy yielded areas under the curves of 0.703 and 0.754, with sensitivities of 64% and 77% and specificities of 75% and 72% for SUV 5.025 and MRglc 2.855, respectively.

CONCLUSION

MRglc was significantly lower in sarcoid lesions than malignant lesions, and improved sarcoid lesions identification over SUV alone.

CLINICAL RELEVANCE STATEMENT

MRglc improves sarcoid lymph node identification over SUV alone and is expected to shorten the examination time by eliminating delayed scans.

KEY POINTS

Active sarcoid lesions are sometimes associated with FDG accumulation and should be differentiated from malignant lesions. SUV and metabolic rate of glucose (MRglc) strongly positively correlated, and MRglc could differentiate sarcoid and malignant lesions. MRglc allows for accurate evaluation and staging of malignant lesions.

Quantitative Assessments of Tumor Activity in a General Oncologic PET/CT Population: Which Metric Minimizes Tracer Uptake Time Dependence?

In oncologic PET, the SUV and standardized uptake ratio (SUR) of a viable tumor generally increase during the postinjection period. In contrast, the net influx rate (Ki ), which is derived from dynamic PET data, should remain relatively constant. Uptake-time-corrected SUV (cSUV) and SUR (cSUR) have been proposed as uptake-time-independent, static alternatives to Ki Our primary aim was to quantify the intrascan repeatability of Ki , SUV, cSUV, SUR, and cSUR among malignant lesions on PET/CT. An exploratory aim was to assess the ability of cSUR to estimate Ki Methods: This prospective, single-center study enrolled adults undergoing standard-of-care oncologic PET/CT. SUV and Ki images were reconstructed from dynamic PET data obtained before (∼35-50 min after injection) and after (∼75-90 min after injection) standard-of-care imaging. Tumors were manually segmented. Quantitative metrics were extracted. cSUVs and cSURs were calculated for a 60-min postinjection reference uptake time. The magnitude of the intrascan test-retest percent change (test-retest |%Δ|) was calculated. Coefficients of determination (R 2) and intraclass correlation coefficients (ICC) were also computed. Differences between metrics were assessed via the Wilcoxon signed-rank test (α, 0.05). Results: This study enrolled 78 subjects; 41 subjects (mean age, 63.8 y; 24 men) with 116 lesions were analyzed. For both tracers, SUVmax and maximum SUR (SURmax) had large early-to-late increases (i.e., poor intrascan repeatability). Among [18F]FDG-avid lesions (n = 93), there were no differences in intrascan repeatability (median test-retest |%Δ|; ICC) between the maximum Ki (Ki ,max) (13%; 0.97) and either the maximum cSUV (cSUVmax) (12%, P = 0.90; 0.96) or the maximum cSUR (cSURmax) (13%, P = 0.67; 0.94). For DOTATATE-avid lesions (n = 23), there were no differences in intrascan repeatability between the Ki ,max (11%; 0.98) and either the cSUVmax (13%, P = 0.41; 0.98) or the cSURmax (11%, P = 0.08; 0.94). The SUVmax, cSUVmax, SURmax, and cSURmax were all strongly correlated with the Ki ,max for both [18F]FDG (R 2, 0.81-0.92) and DOTATATE (R 2, 0.88-0.96), but the cSURmax provided the best agreement with the Ki ,max across early-to-late time points for [18F]FDG (ICC, 0.69-0.75) and DOTATATE (ICC, 0.90-0.91). Conclusion: Ki ,max, cSUVmax, and cSURmax had low uptake time dependence compared with SUVmax and SURmax The Ki ,max can be predicted from cSURmax.

The value of net influx constant based on FDG PET/CT dynamic imaging in the differential diagnosis of metastatic from non-metastatic lymph nodes in lung cancer

OBJECTIVES

This study aims to evaluate the value of the dynamic and static quantitative metabolic parameters derived from 18F-fluorodeoxyglucose (FDG)-positron emission tomography/CT (PET/CT) in the differential diagnosis of metastatic from non-metastatic lymph nodes (LNs) in lung cancer and to validate them based on the results of a previous study.

METHODS

One hundred and twenty-one patients with lung nodules or masses detected on chest CT scan underwent 18F-FDG PET/CT dynamic + static imaging with informed consent. A retrospective collection of 126 LNs in 37 patients with lung cancer was pathologically confirmed. Static image analysis parameters include LN-SUVmax and LN-SUVmax/primary tumor SUVmax (LN-SUVmax/PT-SUVmax). Dynamic metabolic parameters including the net influx rate (Ki) and the surrogate of perfusion (K1) and of each LN were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. Ki/K1 was then calculated as a separate marker. Based on the pathological findings, we divided into a metastatic group and a non-metastatic group. The χ2 test was used to evaluate the agreement of the individual and combined diagnosis of each metabolic parameter with the gold standard. The receiver-operating characteristic (ROC) analysis was performed for each parameter to determine the diagnostic efficacy in differentiating non-metastatic from metastatic LNs with high FDG-avid. P < 0.05 was considered statistically significant.

RESULTS

Among the 126 FDG-avid LNs confirmed by pathology, 70 LNs were metastatic, and 56 LNs were non-metastatic. For ROC analysis, in separate assays, the dynamic metabolic parameter Ki [sensitivity (SEN) of 84.30%, specificity (SPE) of 94.60%, accuracy of 88.89%, and AUC of 0.895] had a better diagnostic value than the static metabolic parameter SUVmax (SEN of 82.90%, SPE of 62.50%, accuracy of 74.60%, and AUC of 0.727) in differentiating between metastatic from non-metastatic LNs groups, respectively. In the combined diagnosis group, the combined SUVmax + Ki diagnosis had a better diagnostic value in the differential diagnosis of metastatic from non-metastatic LNs, with SEN, SPE, accuracy, and AUC of 84.3%, 94.6%, 88.89%, and 0.907, respectively.

CONCLUSIONS

When the cutoff value of Ki was 0.022 ml/g/min, it had a high diagnostic value in the differential diagnosis between metastasis and non-metastasis in FDG-avid LNs of lung cancer, especially in improving the specificity. The combination of SUVmax and Ki is expected to be a reliable metabolic parameter for N-staging of lung cancer.

Total-body dynamic PET/CT imaging reveals kinetic distribution of [13N]NH3 in normal organs

PURPOSE

To systematically investigate kinetic metrics and metabolic trapping of [13N]NH3 in organs.

METHODS

Eleven participants performed total-body [13N]NH3 dynamic positron emission tomography (PET). Regions of interest were drawn in organs to obtain time-to-activity curves (TACs), which were fitted with an irreversible two-tissue compartment model (2TC) to investigate constant rates K1, k2 and k3, and to calculate Ki. Additionally, one-tissue compartment model using full data (1TCfull) and the first four minutes of data (1TC4min) were fitted to TAC data. K1 and k2 were compared among different models to assess [13N]NH3 trapping in organs.

RESULTS

Kinetic rates of [13N]NH3 varied significantly among organs. The mean K1 ranged from 0.049 mL/cm3/min in the muscle to 2.936 mL/cm3/min in the kidney. The k2 and k3 were lowest in the liver (0.001 min- 1) and in the pituitary (0.009 min- 1), while highest in the kidney (0.587 min- 1) and in the liver (0.800 min- 1), respectively. The Ki was largest in the myocardium (0.601 ± 0.259 mL/cm3/min) while smallest in the bone marrow (0.028 ± 0.022 mL/cm3/min). Three groups of organs with similar kinetic characteristics were revealed: (1) the thyroid, the lung, the spleen, the pancreas, and the kidney; (2) the liver and the muscle; and (3) the cortex, the white matter, the cerebellum, the pituitary, the parotid, the submandibular gland, the myocardium, the bone, and the bone marrow. Obvious k3 was identified in multiple organs, and significant changes of K1 in multiple organs and k2 in most organs were found between 2TC and 1TCfull, but both K1 and k2 were comparable between 2TC and 1TC4min.

CONCLUSION

The kinetic rates of [13N]NH3 differed among organs with some have obvious 13N-anmmonia trapping. The normal distribution of kinetic metrics of 13N-anmmonia in organs can serve as a reference for its potential use in tumor imaging.

Greybox: A hybrid algorithm for direct estimation of tracer kinetic parameters from undersampled DCE-MRI data

BACKGROUND

A variety of deep learning-based and iterative approaches are available to predict Tracer Kinetic (TK) parameters from fully sampled or undersampled dynamic contrast-enhanced (DCE) MRI data. However, both the methods offer distinct benefits and drawbacks.

PURPOSE

To propose a hybrid algorithm (named as 'Greybox'), using both model- as well as DL-based, for solving a multi-parametric non-linear inverse problem of directly estimating TK parameters from undersampled DCE MRI data, which is invariant to undersampling rate.

METHODS

The proposed algorithm was inspired by plug-and-play algorithms used for solving linear inverse imaging problems. This technique was tested for its effectiveness in solving the nonlinear ill-posed inverse problem of generating 3D TK parameter maps from four-dimensional (4D; Spatial + Temporal) retrospectively undersampled k-space data. The algorithm learns a deep learning-based prior using UNET to estimate theK trans $\mathbf {K_{trans}}$ andV p $\mathbf {V_{p}}$ parameters based on the Patlak pharmacokinetic model, and this trained prior was utilized to estimate the TK parameter maps using an iterative gradient-based optimization scheme. Unlike the existing DL models, this network is invariant to the undersampling rate of the input data. The proposed method was compared with the total variation-based direct reconstruction technique on brain, breast, and prostate DCE-MRI datasets for various undersampling rates using the Radial Golden Angle (RGA) scheme. For the breast dataset, an indirect estimation using the Fast Composite Splitting algorithm was utilized for comparison. Undersampling rates of 8 × $\times$ , 12 × $\times$ and 20 × $\times$ were used for the experiments, and the results were compared using the PSNR and SSIM as metrics. For the breast dataset of 10 patients, data from four patients were utilized for training (1032 samples), two for validation (752 samples), and the entire volume of four patients for testing. Similarly, for the prostate dataset of 18 patients, 10 patients were utilized for training (720 samples), five for validation (216 samples), and the whole volume of three patients for testing. For the brain dataset of nineteen patients, ten patients were used for training (3152 samples), five for validation (1168 samples), and the whole volume of four patients for testing. Statistical tests were also conducted to assess the significance of the improvement in performance.

RESULTS

The experiments showed that the proposed Greybox performs significantly better than other direct reconstruction methods. The proposed algorithm improved the estimatedK trans $\mathbf {K_{trans}}$ andV p $\mathbf {V_{p}}$ in terms of the peak signal-to-noise ratio by up to 3 dB compared to other standard reconstruction methods.

CONCLUSION

The proposed hybrid reconstruction algorithm, Greybox, can provide state-of-the-art performance in solving the nonlinear inverse problem of DCE-MRI. This is also the first of its kind to utilize convolutional neural network-based encodings as part of the plug-and-play priors to improve the performance of the reconstruction algorithm.

The value of dynamic FDG PET/CT in the differential diagnosis of lung cancer and predicting EGFR mutations

OBJECTIVES

18F-fluorodeoxyglucose (FDG) PET/CT has been widely used for the differential diagnosis of cancer. Semi-quantitative standardized uptake value (SUV) is known to be affected by multiple factors and may make it difficult to differentiate between benign and malignant lesions. It is crucial to find reliable quantitative metabolic parameters to further support the diagnosis. This study aims to evaluate the value of the quantitative metabolic parameters derived from dynamic FDG PET/CT in the differential diagnosis of lung cancer and predicting epidermal growth factor receptor (EGFR) mutation status.

METHODS

We included 147 patients with lung lesions to perform FDG PET/CT dynamic plus static imaging with informed consent. Based on the results of the postoperative pathology, the patients were divided into benign/malignant groups, adenocarcinoma (AC)/squamous carcinoma (SCC) groups, and EGFR-positive (EGFR+)/EGFR-negative (EGFR-) groups. Quantitative parameters including K1, k2, k3, and Ki of each lesion were obtained by applying the irreversible two-tissue compartmental modeling using an in-house Matlab software. The SUV analysis was performed based on conventional static scan data. Differences in each metabolic parameter among the group were analyzed. Wilcoxon rank-sum test, independent-samples T-test, and receiver-operating characteristic (ROC) analysis were performed to compare the diagnostic effects among the differentiated groups. P < 0.05 were considered statistically significant for all statistical tests.

RESULTS

In the malignant group (N = 124), the SUVmax, k2, k3, and Ki were higher than the benign group (N = 23), and all had-better performance in the differential diagnosis (P < 0.05, respectively). In the AC group (N = 88), the SUVmax, k3, and Ki were lower than in the SCC group, and such differences were statistically significant (P < 0.05, respectively). For ROC analysis, Ki with cut-off value of 0.0250 ml/g/min has better diagnostic specificity than SUVmax (AUC = 0.999 vs. 0.70). In AC group, 48 patients further underwent EGFR testing. In the EGFR (+) group (N = 31), the average Ki (0.0279 ± 0.0153 ml/g/min) was lower than EGFR (-) group (N = 17, 0.0405 ± 0.0199 ml/g/min), and the difference was significant (P < 0.05). However, SUVmax and k3 did not show such a difference between EGFR (+) and EGFR (-) groups (P>0.05, respectively). For ROC analysis, the Ki had a cut-off value of 0.0350 ml/g/min when predicting EGFR status, with a sensitivity of 0.710, a specificity of 0.588, and an AUC of 0.674 [0.523-0.802].

CONCLUSION

Although both techniques were specific, Ki had a greater specificity than SUVmax when the cut-off value was set at 0.0250 ml/g/min for the differential diagnosis of lung cancer. At a cut-off value of 0.0350 ml/g/min, there was a 0.710 sensitivity for EGFR status prediction. If EGFR testing is not available for a patient, dynamic imaging could be a valuable non-invasive screening method.

Dual time-point [18F]FDG PET imaging for quantification of metabolic uptake rate: Evaluation of a simple, clinically feasible method

PURPOSE

We aimed to investigate whether a clinically feasible dual time-point (DTP) approach can accurately estimate the metabolic uptake rate constant (Ki) and to explore reliable acquisition times through simulations and clinical assessment considering patient comfort and quantification accuracy.

METHODS

We simulated uptake kinetics in different tumors for four sets of DTP PET images within the routine clinical static acquisition at 60-min post-injection (p.i.). We determined Ki for a total of 81 lesions. Ki quantification from full dynamic PET data (Patlak-Ki) and Ki from DTP (DTP-Ki) were compared. In addition, we scaled a population-based input function (PBIFscl) with the image-derived blood pool activity sampled at different time points to assess the best scaling time-point for Ki quantifications in the simulation data.

RESULTS

In the simulation study, Ki estimated using DTP via (30,60-min), (30,90-min), (60,90-min), and (60,120-min) samples showed strong correlations (r ≥ 0.944, P < 0.0001) with the true value of Ki. The DTP results with the PBIFscl at 60-min time-point in (30,60-min), (60,90-min), and (60,120-min) were linearly related to the true Ki with a slope of 1.037, 1.008, 1.013 and intercept of -6 × 10-4, 2 × 10-5, 5 × 10-5, respectively. In a clinical study, strong correlations (r ≥ 0.833, P < 0.0001) were observed between Patlak-Ki and DTP-Ki. The Patlak-derived mean values of Ki, tumor-to-background-ratio, signal-to-noise-ratio, and contrast-to-noise-ratio were linearly correlated with the DTP method.

CONCLUSIONS

Besides calculating the retention index as a commonly used quantification parameter inDTP imaging,our DTP method can accurately estimate Ki.

Patlak Slope versus Standardized Uptake Value Image Quality in an Oncologic PET/CT Population: A Prospective Cross-Sectional Study

Patlak slope (PS) images have the potential to improve lesion conspicuity compared with standardized uptake value (SUV) images but may be more artifact-prone. This study compared PS versus SUV image quality and hepatic tumor-to-background ratios (TBRs) at matched time points. Early and late SUV and PS images were reconstructed from dynamic positron emission tomography (PET) data. Two independent, blinded readers scored image quality metrics (a four-point Likert scale) and counted tracer-avid lesions. Hepatic lesions and parenchyma were segmented and quantitatively analyzed. Differences were assessed via the Wilcoxon signed-rank test (alpha, 0.05). Forty-three subjects were included. For overall quality and lesion detection, early PS images were significantly inferior to other reconstructions. For overall quality, late PS images (reader 1 [R1]: 3.95, reader 2 [R2]: 3.95) were similar (p > 0.05) to early SUV images (R1: 3.88, R2: 3.84) but slightly superior (p ≤ 0.002) to late SUV images (R1: 2.97, R2: 3.44). For lesion detection, late PS images were slightly inferior to late SUV images (R1 only) but slightly superior to early SUV images (both readers). PS-based TBRs were significantly higher than SUV-based TBRs at the early time point, with opposite findings at the late time point. In conclusion, late PS images are similar to early/late SUV images in image quality and lesion detection; the superiority of SUV versus PS hepatic TBRs is time-dependent.

PET KinetiX-A Software Solution for PET Parametric Imaging at the Whole Field of View Level

Kinetic modeling represents the ultimate foundations of PET quantitative imaging, a unique opportunity to better characterize the diseases or prevent the reduction of drugs development. Primarily designed for research, parametric imaging based on PET kinetic modeling may become a reality in future clinical practice, enhanced by the technical abilities of the latest generation of commercially available PET systems. In the era of precision medicine, such paradigm shift should be promoted, regardless of the PET system. In order to anticipate and stimulate this emerging clinical paradigm shift, we developed a constructor-independent software package, called PET KinetiX, allowing a faster and easier computation of parametric images from any 4D PET DICOM series, at the whole field of view level. The PET KinetiX package is currently a plug-in for Osirix DICOM viewer. The package provides a suite of five PET kinetic models: Patlak, Logan, 1-tissue compartment model, 2-tissue compartment model, and first pass blood flow. After uploading the 4D-PET DICOM series into Osirix, the image processing requires very few steps: the choice of the kinetic model and the definition of an input function. After a 2-min process, the PET parametric and error maps of the chosen model are automatically estimated voxel-wise and written in DICOM format. The software benefits from the graphical user interface of Osirix, making it user-friendly. Compared to PMOD-PKIN (version 4.4) on twelve 18F-FDG PET dynamic datasets, PET KinetiX provided an absolute bias of 0.1% (0.05-0.25) and 5.8% (3.3-12.3) for KiPatlak and Ki2TCM, respectively. Several clinical research illustrative cases acquired on different hybrid PET systems (standard or extended axial fields of view, PET/CT, and PET/MRI), with different acquisition schemes (single-bed single-pass or multi-bed multipass), are also provided. PET KinetiX is a very fast and efficient independent research software that helps molecular imaging users easily and quickly produce 3D PET parametric images from any reconstructed 4D-PET data acquired on standard or large PET systems.

Automated extraction of the arterial input function from brain images for parametric PET studies

BACKGROUND

Accurate measurement of the arterial input function (AIF) is crucial for parametric PET studies, but the AIF is commonly derived from invasive arterial blood sampling. It is possible to use an image-derived input function (IDIF) obtained by imaging a large blood pool, but IDIF measurement in PET brain studies performed on standard field of view scanners is challenging due to lack of a large blood pool in the field-of-view. Here we describe a novel automated approach to estimate the AIF from brain images.

RESULTS

Total body 18F-FDG PET data from 12 subjects were split into a model adjustment group (n = 6) and a validation group (n = 6). We developed an AIF estimation framework using wavelet-based methods and unsupervised machine learning to distinguish arterial and venous activity curves, compared to the IDIF from the descending aorta. All of the automatically extracted AIFs in the validation group had similar shape to the IDIF derived from the descending aorta IDIF. The average area under the curve error and normalised root mean square error across validation data were - 1.59 ± 2.93% and 0.17 ± 0.07.

CONCLUSIONS

Our automated AIF framework accurately estimates the AIF from brain images. It reduces operator-dependence, and could facilitate the clinical adoption of parametric PET.

Improvement of motion artifacts using dynamic whole-body 18F-FDG PET/CT imaging

PURPOSE

Serial dynamic whole-body PET imaging is valuable for assessing serial changes in tracer uptake. The purpose of this study was to evaluate the improvement of motion artifacts in patients using serial dynamic whole-body 18F-fluorodeoxyglyucose (FDG) PET/CT imaging.

MATERIALS AND METHODS

In 797 consecutive patients, serial 3-min dynamic whole-body FDG PET imaging was performed seven times, at 60 or 90 min after FDG administration. In cases with large body motion during imaging, we tried to improve the images by summing the images before body motion. An image quality study was performed on another 50 patients without obvious body motion using the same acquisition mode.

RESULTS

Obvious body movement was observed in 106 of 797 cases (13.3%), and severe motion artifacts which interfered image interpretation were observed in 18 (2.3%). In these 18 cases, summation of the images before the body movement enabled us to obtain images that excluded the effect of the body motion. In the visual evaluation of the image quality in another 50 patients studied, acceptable image quality was obtained when 2 or more times the serial 3-min image data were added.

CONCLUSION

Serial dynamic whole-body FDG PET imaging can minimize body motion artifacts by summation of the images before the body motion. Such serial dynamic study may be a choice for PET imaging to eliminate motion artifacts.

Test-Retest Repeatability of Patlak Slopes versus Standardized Uptake Values for Hypermetabolic Lesions and Normal Organs in an Oncologic PET/CT Population

PURPOSE

We aimed to determine the test-retest repeatability of quantitative metrics based on the Patlak slope (PS) versus the standardized uptake value (SUV) among lesions and normal organs on oncologic [18F]FDG-PET/CT.

PROCEDURES

This prospective, single-center study enrolled adults undergoing standard-of-care oncologic [18F]FDG-PET/CTs. Early (35-50 min post-injection) and late (75-90 min post-injection) SUV and PS images were reconstructed from dynamic whole-body PET data. Repeat imaging occurred within 7 days. Relevant quantitative metrics were extracted from lesions and normal organs. Repeatability was assessed via mean test-retest percent changes [T-RT %Δ], within-subject coefficients of variation (wCVs), and intra-class correlation coefficients (ICCs).

RESULTS

Nine subjects (mean age, 61.7 ± 6.2 years; 6 females) completed the test-retest protocol. Four subjects collectively had 17 [18F]FDG-avid lesions. Lesion wCVs were higher (i.e., worse repeatability) for PS-early-max (16.2%) and PS-early-peak (15.6%) than for SUV-early-max (8.9%) and SUV-early-peak (8.1%), with similar early metric ICCs (0.95-0.98). Lesion wCVs were similar for PS-late-max (8.5%) and PS-late-peak (6.4%) relative to SUV-late-max (9.7%) and SUV-late-peak (7.2%), with similar late metric ICCs (0.93-0.98). There was a significant bias toward higher retest SUV and PS values in the lesion analysis (T-RT %Δ [95% CI]: SUV-late-max, 10.0% [2.6%, 17.0%]; PS-late-max, 20.4% [14.3%, 26.4%]) but not in the normal organ analysis.

CONCLUSIONS

Among [18F]FDG-avid lesions, the repeatability of PS-based metrics is similar to equivalent SUV-based metrics at late post-injection time points, indicating that PS-based metrics may be suitable for tracking response to oncologic therapies. However, further validation is required in light of our study's limitations, including small sample size and bias toward higher retest values for some metrics.

Radionuclide-Labeled Antisilencing Function 1a Inhibitory Peptides for Tumor Identification and Individualized Therapy

Immune checkpoint blockade (ICB) therapy is promising to revolutionize cancer regimens, but the low response rate and the lack of a suitable patient stratification method have impeded universal profit to cancer patients. Noninvasive positron emission tomography (PET) imaging in the whole body, upon coupling with specific biomarkers closely related to the immune response, could provide spatiotemporal information to prescribe cancer therapy. Herein, we demonstrate that antisilencing function 1a (ASF1a) could serve as a biomarker target to delineate tumor immune microenvironments by immune PET (iPET). The iPET radiotracer (68Ga-AP1) is designed to target ASF1a in tumors and predict immune response, and the signal intensity predicts anti-PD-1 (αPD-1) therapy response in a negative correlation manner. The ICB-resistant tumors with a high level of ASF1a as revealed by iPET (ASF1aHigh-iPET) are prescribed to be treated by either the combined 177Lu-labeled AP1 and αPD-1 or the standalone α particle-emitting 225Ac-labeled AP1, both achieving enhanced therapeutic efficacy and prolonged survival time. Our study not only replenishes the iPET arsenal for immune-related response evaluation by designing a reliable biomarker and a facile radiotracer but also provides optional therapeutic strategies for ICB-resistant tumors with versatile radionuclide-labeled AP1 peptides, which is promising for real-time clinical diagnosis and individualized therapy planning simultaneously.

The detection instrumentation and geometric design of clinical PET scanner: towards better performance and broader clinical applications

Positron emission tomography (PET) is a powerful medical imaging modality used in nuclear medicine to diagnose and monitor various clinical diseases in patients. It is more sensitive and produces a highly quantitative mapping of the three-dimensional biodistribution of positron-emitting radiotracers inside the human body. The underlying technology is constantly evolving, and recent advances in detection instrumentation and PET scanner design have significantly improved the medical diagnosis capabilities of this imaging modality, making it more efficient and opening the way to broader, innovative, and promising clinical applications. Some significant achievements related to detection instrumentation include introducing new scintillators and photodetectors as well as developing innovative detector designs and coupling configurations. Other advances in scanner design include moving towards a cylindrical geometry, 3D acquisition mode, and the trend towards a wider axial field of view and a shorter diameter. Further research on PET camera instrumentation and design will be required to advance this technology by improving its performance and extending its clinical applications while optimising radiation dose, image acquisition time, and manufacturing cost. This article comprehensively reviews the various parameters of detection instrumentation and PET system design. Firstly, an overview of the historical innovation of the PET system has been presented, focusing on instrumental technology. Secondly, we have characterised the main performance parameters of current clinical PET and detailed recent instrumental innovations and trends that affect these performances and clinical practice. Finally, prospects for this medical imaging modality are presented and discussed. This overview of the PET system's instrumental parameters enables us to draw solid conclusions on achieving the best possible performance for the different needs of different clinical applications.

Clinical feasibility study of early 30-minute dynamic FDG-PET scanning protocol for patients with lung lesions

PURPOSE

This study aimed to evaluate the clinical feasibility of early 30-minute dynamic 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) positron emission tomography (PET) scanning protocol for patients with lung lesions in comparison to the standard 65-minute dynamic FDG-PET scanning as a reference.

METHODS

Dynamic 18F-FDG PET images of 146 patients with 181 lung lesions (including 146 lesions confirmed by histology) were analyzed in this prospective study. Dynamic images were reconstructed into 28 frames with a specific temporal division protocol for the scan data acquired 65 min post-injection. Ki images and quantitative parameters Ki based on two different acquisition durations [the first 30 min (Ki-30 min) and 65 min (Ki-65 min)] were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. The two acquisition durations were compared for Ki image quality (including visual score analysis and number of lesions detected) and Ki value (including accuracy of Ki, the value of differential diagnosis of lung lesions and prediction of PD-L1 status) by Wilcoxon's rank sum test, Spearman's rank correlation analysis, receiver operating characteristic (ROC) curve, and the DeLong test. The significant testing level (alpha) was set to 0.05.

RESULTS

The quality of the Ki-30 min images was not significantly different from the Ki-65 min images based on visual score analysis (P > 0.05). In terms of Ki value, among 181 lesions, Ki-65 min was statistically higher than Ki-30 min (0.027 ± 0.017 ml/g/min vs. 0.026 ± 0.018 ml/g/min, P < 0.05), while a very high correlation was obtained between Ki-65 min and Ki-30 min (r = 0.977, P < 0.05). In the differential diagnosis of lung lesions, ROC analysis was performed on 146 histologically confirmed lesions, the area under the curve (AUC) of Ki-65 min, Ki-30 min, and SUVmax was 0.816, 0.816, and 0.709, respectively. According to the Delong test, no significant differences in the diagnostic accuracies were found between Ki-65 min and Ki-30 min (P > 0.05), while the diagnostic accuracies of Ki-65 min and Ki-30 min were both significantly higher than that of SUVmax (P < 0.05). In 73 (NSCLC) lesions with definite PD-L1 expression results, the Ki-65 min, Ki-30 min, and SUVmax in PD-L1 positivity were significantly higher than that in PD-L1 negativity (P < 0.05). And no significant differences in predicting PD-L1 positivity were found among Ki-65 min, Ki-30 min, and SUVmax (AUC = 0.704, 0.695, and 0.737, respectively, P > 0.05), according to the results of ROC analysis and Delong test.

CONCLUSIONS

This study indicates that an early 30-minute dynamic FDG-PET acquisition appears to be sufficient to provide quantitative images with good-quality and accurate Ki values for the assessment of lung lesions and prediction of PD-L1 expression. Protocols with a shortened early 30-minute acquisition time may be considered for patients who have difficulty with prolonged acquisitions to improve the efficiency of clinical acquisitions.

Estimation of kinetic parameters in dynamic FDG PET imaging based on shortened protocols: a virtual clinical study

This study investigated the estimation of kinetic parameters and production of related parametric Ki images in FDG PET imaging using the proposed shortened protocol (three 3-min/bed routine static images) by means of the simulated annealing (SA) algorithm. Six realistic heterogeneous tumors and various levels of [18F] FDG uptake were simulated by the XCAT phantom. An irreversible two-tissue compartment model (2TCM) using population-based input function was employed. By keeping two routine clinical scans fixed (60-min and 90-min post injection), the effect of the early scan time on optimizing the estimation of the pharmacokinetic parameters was investigated. The SA optimization algorithm was applied to estimate micro- and macro-parameters (K1, k2, k3, Ki). The minimum bias for most parameters was observed at a scan time of 20-min, which was < 10%. A highly significant correlation (> 0.9) as well as limited bias (< 10%) were observed between kinetic parameters generated from two methods [two-tissue compartment full dynamic scan (2TCM-full) and two-tissue compartment by SA algorithm (2TCM-SA)]. The analysis showed a strong correlation (> 0.8) between (2TCM-SA) Ki and SUV images. In addition, the tumor-to-background ratio (TBR) metric in the parametric (2TCM-SA) Ki images was significantly higher than SUV, although the SUV images provide better Contrast-to-noise ratio relative to parametric (2TCM-SA) Ki images. The proposed shortened protocol by the SA algorithm can estimate the kinetic parameters in FDG PET scan with high accuracy and robustness. It was also concluded that the parametric Ki images obtained from the 2TCM-SA as a complementary image of the SUV possess more quantification information than SUV images and can be used by the nuclear medicine specialist. This method has the potential to be an alternative to a full dynamic PET scan.

Total-Body PET/CT Applications in Cardiovascular Diseases: A Perspective Document of the SNMMI Cardiovascular Council

Digital PET/CT systems with a long axial field of view have become available and are emerging as the current state of the art. These new camera systems provide wider anatomic coverage, leading to major increases in system sensitivity. Preliminary results have demonstrated improvements in image quality and quantification, as well as substantial advantages in tracer kinetic modeling from dynamic imaging. These systems also potentially allow for low-dose examinations and major reductions in acquisition time. Thereby, they hold great promise to improve PET-based interrogation of cardiac physiology and biology. Additionally, the whole-body coverage enables simultaneous assessment of multiple organs and the large vascular structures of the body, opening new opportunities for imaging systemic mechanisms, disorders, or treatments and their interactions with the cardiovascular system as a whole. The aim of this perspective document is to debate the potential applications, challenges, opportunities, and remaining challenges of applying PET/CT with a long axial field of view to the field of cardiovascular disease.

Application of Nuclear Medicine Techniques in Musculoskeletal Infection: Current Trends and Future Prospects

Nuclear medicine has become an indispensable discipline in the diagnosis and management of musculoskeletal infections. Radionuclide tests serve as a valuable diagnostic tool for patients suspected of having osteomyelitis, spondylodiscitis, or prosthetic joint infections. The choice of the most suitable imaging modality depends on various factors, including the affected area, potential extra osseous involvement, or the impact of previous bone/joint conditions. This review provides an update on the use of conventional radionuclide imaging tests and recent advancements in fusion imaging scans for the differential diagnosis of musculoskeletal infections. Furthermore, it examines the role of radionuclide scans in monitoring treatment responses and explores current trends in their application. We anticipate that this update will be of significant interest to internists, rheumatologists, radiologists, orthopedic surgeons, rehabilitation physicians, and other specialists involved in musculoskeletal pathology.

Motion-correction strategies for enhancing whole-body PET imaging

Positron Emission Tomography (PET) is a powerful medical imaging technique widely used for detection and monitoring of disease. However, PET imaging can be adversely affected by patient motion, leading to degraded image quality and diagnostic capability. Hence, motion gating schemes have been developed to monitor various motion sources including head motion, respiratory motion, and cardiac motion. The approaches for these techniques have commonly come in the form of hardware-driven gating and data-driven gating, where the distinguishing aspect is the use of external hardware to make motion measurements vs. deriving these measures from the data itself. The implementation of these techniques helps correct for motion artifacts and improves tracer uptake measurements. With the great impact that these methods have on the diagnostic and quantitative quality of PET images, much research has been performed in this area, and this paper outlines the various approaches that have been developed as applied to whole-body PET imaging.

Patlak Reconstruction Using Dynamic 18 F-FDG PET Imaging for Evaluation of Malignant Liver Tumors : A Comparison of HCC, ICC, and Metastatic Liver Tumors

PURPOSE OF THE REPORT

The aim of this study was to explore the different patterns of dynamic whole-body (D-WB) FDG PET/CT parameters among liver malignancy types as potential diagnostic clues and investigate the association between static and dynamic PET/CT parameters for each tumor histology.

PATIENTS AND METHODS

Seventy-one patients with intrahepatic cholangiocarcinoma (ICC), metastatic liver tumor (MLT), or hepatocellular carcinoma (HCC) who underwent D-WB and static dual-time-point FDG PET/CT were enrolled. We obtained Pearson correlation coefficients between the metabolic rate of FDG (MR FDG ; mg/min/ 100ml) or distribution volume of free FDG (DV FDG , %) and static PET/CT parameters. We compared MR FDG and DV FDG values by tumor type and performed receiver operating characteristic analyses for MR FDG and static images.

RESULTS

A total of 12 ICC, 116 MLT, and 36 HCC lesions were analyzed. MR FDG and DV FDG showed excellent correlation with early (SUV e ) and delayed SUV max (SUV d ) ( r = 0.71~0.97), but DV FDG in the HCC lesions did not ( r = 0.62 and 0.69 for SUV e and SUV d , respectively) ( P < 0.001 for all). HCC lesions showed significantly lower MR FDG (2.43 ± 1.98) and DV FDG (139.95 ± 62.58) than ICC (5.02 ± 3.56, 207.06 ± 97.13) and MLT lesions (4.51 ± 2.47, 180.13 ± 75.58) ( P < 0.01 for all). The optimal MR FDG could differentiate HCC from ICC and MLT with areas under the curve of 0.84 and 0.80, respectively. Metastatic liver tumor lesions showed the widest distribution of MR FDG and DV FDG values but with no significant difference among most primary sites.

CONCLUSIONS

MR FDG was strongly correlated with SUV max in the 3 malignancies and showed utility for differentiating HCC from ICC and MLT. Each tumor type has a different glucose metabolism, and D-WB FDG PET/CT imaging has the potential to visualize those differences.

Assessing dynamic metabolic heterogeneity in prostate cancer patients via total-body [68Ga]Ga-PSMA-11 PET/CT imaging: quantitative analysis of [68Ga]Ga-PSMA-11 uptake in pathological lesions and normal organs

PURPOSE

This study aimed to quantitatively assess [68Ga]Ga-PSMA-11 uptake in pathological lesions and normal organs in prostate cancer using the total-body [68Ga]Ga-PSMA-11 PET/CT and to characterize the dynamic metabolic heterogeneity of prostate cancer.

METHODS

Dynamic total-body [68Ga]Ga-PSMA-11 PET/CT scans were performed on ten prostate cancer patients. Manual delineation of volume-of-interests (VOIs) was performed on multiple normal organs displaying high [68Ga]Ga-PSMA-11 uptake, as well as pathological lesions. Time-to-activity curves (TACs) were generated, and the four compartment models including one-tissue compartmental model (1T1k), reversible one-tissue compartmental model (1T2k), irreversible two-tissue compartment model (2T3k) and reversible two-tissue compartmental model (2T4k) were fitted to each tissue TAC. Various rate constants, including K1 (forward transport rate from plasma to the reversible compartment), k2 (reverse transport rate from the reversible compartment to plasma), k3 (tracer binding on the PSMA-receptor and its internalization), k4 (the externalization rate of the tracer) and Ki (net influx rate), were obtained. The selection of the optimal model for describing the uptake of both lesions and normal organs was determined using the Akaike information criteria (AIC). Receiver operating characteristic (ROC) curve analysis was performed to determine the cut-off values for differentiating physiological and pathological [68Ga]Ga-PSMA-11 uptake.

RESULTS

Both 1T1k and 1T2k models showed relatively high AIC values compared to the 2T3k and 2T4k models in both pathological lesions and normal organs. The kinetic behavior of pathological lesions was better described by the 2T3k model compared to the 2T4k model, while the normal organs were better described by the 2T4k model. Significant variations in kinetic metrics, such as K1, k2, and k3, and Ki, were observed among normal organs with high [68Ga]Ga-PSMA-11 uptake and pathological lesions. The high Ki value in normal organs was primarily determined by elevated K1 and low k3, rather than k2. Conversely, the high Ki value in pathological lesions, ranking second to the kidney and similar to salivary glands and spleen, was predominantly determined by the highest k3 value. Notably, k3 exhibited the highest performance in distinguishing between physiological and pathological [68Ga]Ga-PSMA-11 uptake, with an area under the curve (AUC) of 0.844 (95% CI, 0.773-0.915), sensitivity of 82.9%, and specificity of 74.1%. The k3 values showed better performance than SUVmean (AUC, 0.659), SUVmax (AUC, 0.637), and other kinetic parameter including K1 (AUC, 0.604), k2 (AUC, 0.634), and Ki (AUC, 0.651).

CONCLUSIONS

Significant discrepancies in kinetic metrics were detected between pathological lesions and normal organs, despite their shared high uptake of [68Ga]Ga-PSMA-11. Notably, the k3 value exhibits a noteworthy capability to distinguish between pathological lesions and normal organs with elevated [68Ga]Ga-PSMA-11 uptake. This discovery implies that k3 holds promise as a prospective imaging biomarker for distinguishing between pathologic and non-specific [68Ga]Ga-PSMA-11 uptake in patients with prostate cancer.

A short 18F-FDG imaging window triple injection neuroimaging protocol for parametric mapping in PET

BACKGROUND

In parametric PET, kinetic parameters are extracted from dynamic PET images. It is not commonly used in clinical practice because of long scan times and the requirement for an arterial input function (AIF). To address these limitations, we designed an 18F-fluorodeoxyglucose (18F-FDG) triple injection dynamic PET protocol for brain imaging with a standard field of view PET scanner using a 24-min imaging window and an input function modeled using measurements from a region of interest placed over the left ventricle.

METHODS

To test the protocol in 6 healthy participants, we examined the quality of voxel-based maps of kinetic parameters in the brain generated using the two-tissue compartment model and compared estimated parameter values with previously published values. We also utilized data from a 36-min validation imaging window to compare (1) the modeled AIF against the input function measured in the validation window; and (2) the net influx rate ([Formula: see text]) computed using parameter estimates from the short imaging window against the net influx rate obtained using Patlak analysis in the validation window.

RESULTS

Compared to the AIF measured in the validation window, the input function estimated from the short imaging window achieved a mean area under the curve error of 9%. The voxel-wise Pearson's correlation between [Formula: see text] estimates from the short imaging window and the validation imaging window exceeded 0.95.

CONCLUSION

The proposed 24-min triple injection protocol enables parametric 18F-FDG neuroimaging with noninvasive estimation of the AIF from cardiac images using a standard field of view PET scanner.

Comparison of parametric imaging and SUV imaging with [68 Ga]Ga-PSMA-11 using dynamic total-body PET/CT in prostate cancer

PURPOSE

Standardized uptake value (SUV) has been prevalently used to measure [68 Ga]Ga-PSMA-11 activity in prostate cancer, but it is susceptible to multiple factors. Parametric imaging allows for absolute quantification of tracer uptake and provides a better diagnostic accuracy that is crucial for lesion detection. However, the clinical significance of total-body parametric imaging of [68 Ga]Ga-PSMA-11 remains to be fully assessed. Therefore, the aim of our study is to delve into the diagnostic implications of total-body parametric imaging of [68 Ga]Ga-PSMA-11 PET/CT for patients with prostate cancer.

METHODS

Twenty prostate cancer patients were included and underwent a dynamic total-body [68 Ga]Ga-PSMA-11 PET/CT scan. An irreversible two-tissue compartment model (2T3k) was fitted for each tissue time-to-activity curve, and the net influx rate (Ki) was obtained. The image quality and semi-quantitative analysis of lesion-to-background ratio (LBR), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared between parametric images and SUV images.

RESULTS

Kinetic modeling using 2T3k demonstrated favorable model fitting in both normal organs and lesions. All of the lesions detected on SUV images (55-60 min) could be detected on Ki images. The correlation between Ki, SUVmean, and SUVmax in both normal organs and pathological lesions was found to be positive and statistically significant. Conversely, a moderate positive correlations were found between Ki and K1 (R = 0.69, P < 0.001; R = 0.61, P < 0.001) and Ki and k3 (R = 0.69, P < 0.001; R = 0.62, P < 0.001), in normal organs and pathological lesions, respectively. Visual assessment in Ki images showed less image noise and higher lesions conspicuity compared to SUV images. Ki image-derived LBR, SNR, and CBR of pathological lesions including primary tumors (PTs), lymph node metastases (LNMs) and bone metastases (BMs), exhibited remarkably higher folds (1.4-3.6 folds) compared to those derived from SUV of corresponding lesions.

CONCLUSIONS

Total-body parametric imaging of [68 Ga]Ga-PSMA-11 enhanced lesion contrast and improved lesion detectability compared to SUV images. This may potentially serve as an imaging biomarker and theranostic tool for precise diagnosis and treatment evaluation in prostate cancer patients.

Impact of patient characteristic factors on the dynamics of liver glucose metabolism: Evaluation of multiparametric imaging with dynamic whole-body 18 F-fluorodeoxyglucose-positron emission tomography

AIMS

To assess the impact of various patient characteristics on the dynamics of liver glucose metabolism using automated multiparametric imaging with whole-body dynamic 18 F-fluorodeoxyglucose (FDG)-positron emission tomography (PET).

MATERIALS AND METHODS

We retrospectively enrolled 540 patients who underwent whole-body dynamic FDG-PET. Three quantitative indices representing hepatic glucose metabolism [mean standardized uptake value normalized by lean body mass (SULmean), metabolic glucose rate (kinetic index) and distribution volume (DV)] were measured from multiparametric PET images produced automatically based on the Patlak plot model. Patient characteristics including age, sex, body mass index, fasting time, blood glucose level, and the presence of diabetes mellitus (DM) or hepatic steatosis (HS) were collected. We examined the correlations between the characteristic factors and three quantitative indices using multiple regression analysis.

RESULTS

The success rate of kinetic analysis using multiparametric PET imaging was 93.3% (504/540). Hepatic SULmean was significantly correlated with age (p < .001), sex (p < .001) and blood glucose level (p = .002). DV was significantly correlated with age (p = .033), sex (p < .001), body mass index (p = .002), fasting time (p = .043) and the presence of HS (p = .002). The kinetic index was significantly correlated with age (p < .001) and sex (p = .004). In the comparison of the healthy, DM and HS groups, patients with DM had a significantly increased SULmean, whereas patients with HS had a significantly decreased DV.

CONCLUSIONS

Our results showed that liver glucose metabolism was influenced by various patient characteristic factors. Multiparametric FDG-PET imaging can be used to analyse the kinetics of liver glucose metabolism in routine clinical practice.

An update on the use of image-derived input functions for human PET studies: new hopes or old illusions?

BACKGROUND

The need for arterial blood data in quantitative PET research limits the wider usability of this imaging method in clinical research settings. Image-derived input function (IDIF) approaches have been proposed as a cost-effective and non-invasive alternative to gold-standard arterial sampling. However, this approach comes with its own limitations-partial volume effects and radiometabolite correction among the most important-and varying rates of success, and the use of IDIF for brain PET has been particularly troublesome.

MAIN BODY

This paper summarizes the limitations of IDIF methods for quantitative PET imaging and discusses some of the advances that may make IDIF extraction more reliable. The introduction of automated pipelines (both commercial and open-source) for clinical PET scanners is discussed as a way to improve the reliability of IDIF approaches and their utility for quantitative purposes. Survey data gathered from the PET community are then presented to understand whether the field's opinion of the usefulness and validity of IDIF is improving. Finally, as the introduction of next-generation PET scanners with long axial fields of view, ultra-high sensitivity, and improved spatial and temporal resolution, has also brought IDIF methods back into the spotlight, a discussion of the possibilities offered by these state-of-the-art scanners-inclusion of large vessels, less partial volume in small vessels, better description of the full IDIF kinetics, whole-body modeling of radiometabolite production-is included, providing a pathway for future use of IDIF.

CONCLUSION

Improvements in PET scanner technology and software for automated IDIF extraction may allow to solve some of the major limitations associated with IDIF, such as partial volume effects and poor temporal sampling, with the exciting potential for accurate estimation of single kinetic rates. Nevertheless, until individualized radiometabolite correction can be performed effectively, IDIF approaches remain confined at best to a few tracers.

Metabolic Imaging as a Tool to Characterize Chemoresistance and Guide Therapy in Triple-Negative Breast Cancer (TNBC)

After an initial response to chemotherapy, tumor relapse is frequent. This event is reflective of both the spatiotemporal heterogeneities of the tumor microenvironment as well as the evolutionary propensity of cancer cell populations to adapt to variable conditions. Because the cause of this adaptation could be genetic or epigenetic, studying phenotypic properties such as tumor metabolism is useful as it reflects molecular, cellular, and tissue-level dynamics. In triple-negative breast cancer (TNBC), the characteristic metabolic phenotype is a highly fermentative state. However, during treatment, the spatial and temporal dynamics of the metabolic landscape are highly unstable, with surviving populations taking on a variety of metabolic states. Thus, longitudinally imaging tumor metabolism provides a promising approach to inform therapeutic strategies, and to monitor treatment responses to understand and mitigate recurrence. Here we summarize some examples of the metabolic plasticity reported in TNBC following chemotherapy and review the current metabolic imaging techniques available in monitoring chemotherapy responses clinically and preclinically. The ensemble of imaging technologies we describe has distinct attributes that make them uniquely suited for a particular length scale, biological model, and/or features that can be captured. We focus on TNBC to highlight the potential of each of these technological advances in understanding evolution-based therapeutic resistance.

A novel objective method for discriminating pathological and physiological colorectal uptake in the lower abdominal region using whole-body dynamic 18F-FDG-PET

OBJECTIVES

To investigate whether the center-of-mass shift distance (CMSD) analysis on whole-body dynamic positron emission tomography (WBD-PET) with continuous bed motion is an objective index for discriminating pathological and physiological uptake in the lower abdominal colon.

METHODS

We retrospectively analyzed the CMSD in 39 patients who underwent delayed imaging to detect incidental focal uptake that was difficult to determine as pathological and physiological on a conventional early-PET (early) image reconstructed by 5-phase WBD-PET images. The CMSD between each phase of WBD-PET images and between conventional early and delayed (two-phase) PET images were classified into pathological and physiological uptake groups based on endoscopic histology or other imaging diagnostics. The diagnostic performance of CMSD analysis on WBD-PET images was evaluated by receiver operator characteristic (ROC) analysis and compared to that of two-phase PET images.

RESULTS

A total of 66 incidental focal uptake detected early image were classified into 19 and 47 pathological and physiological uptake groups, respectively. The CMSD on WBD-PET and two-phase PET images in the pathological uptake group was significantly lower than that in the physiological uptake group (p < 0.01), respectively. The sensitivity, specificity, and accuracy in CMSD analysis on WBD-PET images at the optimal cutoff of 5.2 mm estimated by the Youden index were 94.7%, 89.4%, and 89.4%, respectively, which were not significantly different (p = 0.74) from those of two-phase PET images.

CONCLUSIONS

The CMSD analysis on WBD-PET was useful in discriminating pathological and physiological colorectal uptake in the lower abdominal region, and its diagnostic performance was comparable to that of two-phase PET images. We suggested that CMSD analysis on WBD-PET images would be a novel objective method to omit unnecessary additional delayed imaging.

Quantitation of dynamic total-body PET imaging: recent developments and future perspectives

BACKGROUND

Positron emission tomography (PET) scanning is an important diagnostic imaging technique used in disease diagnosis, therapy planning, treatment monitoring, and medical research. The standardized uptake value (SUV) obtained at a single time frame has been widely employed in clinical practice. Well beyond this simple static measure, more detailed metabolic information can be recovered from dynamic PET scans, followed by the recovery of arterial input function and application of appropriate tracer kinetic models. Many efforts have been devoted to the development of quantitative techniques over the last couple of decades.

CHALLENGES

The advent of new-generation total-body PET scanners characterized by ultra-high sensitivity and long axial field of view, i.e., uEXPLORER (United Imaging Healthcare), PennPET Explorer (University of Pennsylvania), and Biograph Vision Quadra (Siemens Healthineers), further stimulates valuable inspiration to derive kinetics for multiple organs simultaneously. But some emerging issues also need to be addressed, e.g., the large-scale data size and organ-specific physiology. The direct implementation of classical methods for total-body PET imaging without proper validation may lead to less accurate results.

CONCLUSIONS

In this contribution, the published dynamic total-body PET datasets are outlined, and several challenges/opportunities for quantitation of such types of studies are presented. An overview of the basic equation, calculation of input function (based on blood sampling, image, population or mathematical model), and kinetic analysis encompassing parametric (compartmental model, graphical plot and spectral analysis) and non-parametric (B-spline and piece-wise basis elements) approaches is provided. The discussion mainly focuses on the feasibilities, recent developments, and future perspectives of these methodologies for a diverse-tissue environment.

Guided block matching and 4-D transform domain filter projection denoising method for dynamic PET image reconstruction

PURPOSE

Dynamic PET is an essential tool in oncology due to its ability to visualize and quantify radiotracer uptake, which has the potential to improve imaging quality. However, image noise caused by a low photon count in dynamic PET is more significant than in static PET. This study aims to develop a novel denoising method, namely the Guided Block Matching and 4-D Transform Domain Filter (GBM4D) projection, to enhance dynamic PET image reconstruction.

METHODS

The sinogram was first transformed using the Anscombe method, then denoised using a combination of hard thresholding and Wiener filtering. Each denoising step involved guided block matching and grouping, collaborative filtering, and weighted averaging. The guided block matching was performed on accumulated PET sinograms to prevent mismatching due to low photon counts. The performance of the proposed denoising method (GBM4D) was compared to other methods such as wavelet, total variation, non-local means, and BM3D using computer simulations on the Shepp-Logan and digital brain phantoms. The denoising methods were also applied to real patient data for evaluation.

RESULTS

In all phantom studies, GBM4D outperformed other denoising methods in all time frames based on the structural similarity and peak signal-to-noise ratio. Moreover, GBM4D yielded the lowest root mean square error in the time-activity curve of all tissues and produced the highest image quality when applied to real patient data.

CONCLUSION

GBM4D demonstrates excellent denoising and edge-preserving capabilities, as validated through qualitative and quantitative assessments of both temporal and spatial denoising performance.

Prognostic value of whole-body dynamic 18F-FDG PET/CT Patlak in diffuse large B-cell lymphoma

Objective

This study aims to investigate the significance of interim whole-body dynamic 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) Patlak parameters for predicting the prognosis of patients with diffuse large B-cell lymphoma. To estimate the predictive value of the whole-body dynamic 18F-FDG PET/CT Patlak parameter for 2-year progression-free survival (PFS) and 2-year overall survival (OS).

Methods

This study reports the findings of 67 patients with diffuse large B-cell lymphoma (DLBCL). These patients underwent interim whole-body dynamic 18F-FDG PET/CT scans from June 2021 to January 2023 at the Department of Nuclear Medicine, First Affiliated Hospital of Anhui Medical University. The predictive values of maximum standard uptake value (SUVmax), maximum of net glucose uptake rate (Kimax) and the predictive model combining Kimax and interim treatment response on the prognosis of patients was analyzed using receiver operating characteristic (ROC) curves. Kaplan-Meier survival curves and log-rank tests were used for survival analysis. Univariate and multivariate analyses were performed to screen for independent prognostic risk factors.

Results

After a median follow-up of 18 months, 21 patients (31.3%) experienced disease recurrence or death. The cut-off values for the SUVmax and the Kimax were 6.1 and 0.13 μmol min-1·ml-1, respectively. Ann Arbor stage, IPI, SUVmax, Kimax and interim treatment response were associated with PFS and OS in the univariate analysis. However, only Kimax and interim treatment response were independent influences on PFS and OS in multivariate analysis.

Conclusion

Interim whole-body dynamic 18F-FDG PET/CT Patlak imaging has significant prognostic value in patients with DLBCL. Among them, the interim dynamic parameter Kimax showed the best predictive value for prognosis compared with the interim SUVmax and interim treatment response. The predictive model established by Kimax and the interim treatment response allowed for the accurate stratification of the prognostic risk of DLBCL.

Improved accuracy of the biodistribution and internal radiation dosimetry of 13 N-ammonia using a total-body PET/CT scanner

BACKGROUND

Conventional short-axis PET typically utilizes multi-bed multi-pass acquisition to produce quantitative whole-body dynamic images and cannot record all the uptake information simultaneously, resulting in errors when fitting the time-activity curves (TACs) and calculating radiation doses.

PURPOSE

The aim of this study is to evaluate the 13 N-ammonia biodistribution and the internal radiation doses using a 194 cm long total-body PET/CT scanner (uEXPLORER), and make a comparison with the previous short-axis PET results.

METHODS

Ten subjects (age 40-74 years) received 13 N-NH3 injection (418.1-670.81 MBq) and were under a dynamic scan for about 60 min with using a 3-dimensional whole-body protocol. ROIs were drawn visually on 11 major organs (brain, thyroid, gallbladder, heart wall, kidneys, liver, pancreas, spleen, lungs, bone marrow, and urinary bladder content) for each subject. TACs were generated using Pmod and the absorbed radiation doses were calculated using Olinda 2.2. To compare with the conventional PET/CT, five points were sampled on uEXPLORER's TACs to mimic the result of a short-axis PET/CT (15 cm axial FOV, consisted of 9 or 10 bed positions). Then the TACs were obtained using the multi-exponential fitting method, and the residence time and radiation dose were also calculated and compared with uEXPLORER.

RESULTS

The highest absorbed organ doses were the pancreas, thyroid, spleen, heart wall, and kidneys for the male. For the female, the first five highest absorbed organ dose coefficients were the pancreas, heart wall, spleen, lungs, and kidneys. The lowest absorbed dose was found in red marrow both for male and female. The simulated short-axis PET can fit TACs well for the gradually-changed uptake organs but typically underestimated for the rapid-uptake organs during the first-10 min, resulting in errors in the calculated radiation dose.

CONCLUSION

uEXPLORER PET/CT can measure 13 N-ammonia's TACs simultaneously in all organs of the whole body, which can provide more accurate biodistribution and radiation dose estimation compared with the conventional short-axis scanners.

Druggability of Targets for Diagnostic Radiopharmaceuticals

Targets play an indispensable and pivotal role in the development of radiopharmaceuticals. However, the initial stages of drug discovery projects are often plagued by frequent failures due to inadequate information on druggability and suboptimal target selection. In this context, we aim to present a comprehensive review of the factors that influence target druggability for diagnostic radiopharmaceuticals. Specifically, we explore the crucial determinants of target specificity, abundance, localization, and positivity rate and their respective implications. Through a detailed analysis of existing protein targets, we elucidate the significance of each factor. By carefully considering and balancing these factors during the selection of targets, more efficacious and targeted radiopharmaceuticals are expected to be designed for the diagnosis of a wide range of diseases in the future.

MCP-Net: Introducing Patlak Loss Optimization to Whole-body Dynamic PET Inter-frame Motion Correction

In whole-body dynamic positron emission tomography (PET), inter-frame subject motion causes spatial misalignment and affects parametric imaging. Many of the current deep learning inter-frame motion correction techniques focus solely on the anatomy-based registration problem, neglecting the tracer kinetics that contains functional information. To directly reduce the Patlak fitting error for 18F-FDG and further improve model performance, we propose an interframe motion correction framework with Patlak loss optimization integrated into the neural network (MCP-Net). The MCP-Net consists of a multiple-frame motion estimation block, an image-warping block, and an analytical Patlak block that estimates Patlak fitting using motion-corrected frames and the input function. A novel Patlak loss penalty component utilizing mean squared percentage fitting error is added to the loss function to reinforce the motion correction. The parametric images were generated using standard Patlak analysis following motion correction. Our framework enhanced the spatial alignment in both dynamic frames and parametric images and lowered normalized fitting error when compared to both conventional and deep learning benchmarks. MCP-Net also achieved the lowest motion prediction error and showed the best generalization capability. The potential of enhancing network performance and improving the quantitative accuracy of dynamic PET by directly utilizing tracer kinetics is suggested.

The Prognostic and therapeutic value and clinical implications of fibroblast activation protein-α as a novel biomarker in colorectal cancer

The identification of contributing factors leading to the development of Colorectal Cancer (CRC), as the third fatal malignancy, is crucial. Today, the tumor microenvironment has been shown to play a key role in CRC progression. Fibroblast-Activation Protein-α (FAP) is a type II transmembrane cell surface proteinase expressed on the surface of cancer-associated fibroblasts in tumor stroma. As an enzyme, FAP has di- and endoprolylpeptidase, endoprotease, and gelatinase/collagenase activities in the Tumor Microenvironment (TME). According to recent reports, FAP overexpression in CRC contributes to adverse clinical outcomes such as increased lymph node metastasis, tumor recurrence, and angiogenesis, as well as decreased overall survival. In this review, studies about the expression level of FAP and its associations with CRC patients' prognosis are reviewed. High expression levels of FAP and its association with clinicopathological factors have made as a potential target. In many studies, FAP has been evaluated as a therapeutic target and diagnostic factor into which the current review tries to provide a comprehensive insight. Video Abstract.

Dynamic and Static 18F-FDG PET/CT Imaging in SMARCA4-Deficient Non-Small Cell Lung Cancer and Response to Therapy: A Case Report

SMARCA4-deficient non-small cell lung cancer (NSCLC) is a more recently recognized subset of NSCLC. We describe the ¹⁸F-fluorodeoxyglucose (FDG) PET/CT findings in a rare case of SMARCA4-deficient NSCLC and response to therapy. A 45-year-old male patient with a history of heavy smoking (10 years) underwent an ¹⁸F-fluorodeoxyglucose (FDG) PET/CT dynamic (chest) + static (whole-body) scan for diagnosis and pre-treatment staging. ¹⁸F-FDG PET/CT showed an FDG-avid mass in the upper lobe of the left lung (SUV_max of 22.4) and FDG-avid lymph nodes (LN) in the left pulmonary hilar region (SUV_max of 5.7). In addition, there were multiple metastases throughout the body, including in the distant LNs, adrenal glands, bone, left subcutaneous lumbar region, and brain. Pathological findings confirmed SMARCA4-deficient NSCLC. After four cycles of chemotherapy and immune checkpoint inhibitors (ICI), the patient underwent again an ¹⁸F-FDG PET/CT scan (including a dynamic scan) for efficacy evaluation. We report a case that deepens the understanding of the ¹⁸F-FDG PET/CT presentation of SMARCA4-deficient NSCLC as well as dynamic imaging features and parametric characteristics.

Diagnostic Performance of Dynamic Whole-Body Patlak [18F]FDG-PET/CT in Patients with Indeterminate Lung Lesions and Lymph Nodes

BACKGROUND

Static [¹⁸F]FDG-PET/CT is the imaging method of choice for the evaluation of indeterminate lung lesions and NSCLC staging; however, histological confirmation of PET-positive lesions is needed in most cases due to its limited specificity. Therefore, we aimed to evaluate the diagnostic performance of additional dynamic whole-body PET.

METHODS

A total of 34 consecutive patients with indeterminate pulmonary lesions were enrolled in this prospective trial. All patients underwent static (60 min p.i.) and dynamic (0-60 min p.i.) whole-body [¹⁸F]FDG-PET/CT (300 MBq) using the multi-bed-multi-timepoint technique (Siemens mCT FlowMotion). Histology and follow-up served as ground truth. Kinetic modeling factors were calculated using a two-compartment linear Patlak model (FDG influx rate constant = Ki, metabolic rate = MR-FDG, distribution volume = DV-FDG) and compared to SUV using ROC analysis.

RESULTS

MR-FDG_mean provided the best discriminatory power between benign and malignant lung lesions with an AUC of 0.887. The AUC of DV-FDG_mean (0.818) and SUV_mean (0.827) was non-significantly lower. For LNM, the AUCs for MR-FDG_mean (0.987) and SUV_mean (0.993) were comparable. Moreover, the DV-FDG_mean in liver metastases was three times higher than in bone or lung metastases.

CONCLUSIONS

Metabolic rate quantification was shown to be a reliable method to detect malignant lung tumors, LNM, and distant metastases at least as accurately as the established SUV or dual-time-point PET scans.

Multiparametric dynamic whole-body PSMA PET/CT using [68Ga]Ga-PSMA-11 and [18F]PSMA-1007

BACKGROUND

Routine prostate-specific membrane antigen (PSMA) positron emission tomography (PET) performed for primary staging or restaging of prostate cancer patients is usually done as a single static image acquisition 60 min after tracer administration. In this study, we employ dynamic whole-body (D-WB) PET imaging to compare the pharmacokinetics of [⁶⁸Ga]Ga-PSMA-11 and [¹⁸F]PSMA-1007 in various tissues and lesions, and to assess whether Patlak parametric images are quantitative and improve lesion detection and image readability.

METHODS

Twenty male patients with prostate cancer were examined using a D-WB PSMA PET protocol. Ten patients were scanned with [⁶⁸Ga]Ga-PSMA-11 and ten with [¹⁸F]PSMA-1007. Kinetic analyses were made using time-activity curves (TACs) extracted from organs (liver, spleen, bone, and muscle) and lesions. For each patient, three images were produced: SUV + Patlak parametric images (K_i and DV). All images were reviewed visually to compare lesion detection, image readability was quantified using target-to-background ratios (TBR), and Ki and DV values were compared.

RESULTS

The two PSMA tracers exhibited markedly different pharmacokinetics in organs: reversible for [⁶⁸Ga]Ga-PSMA-11 and irreversible for [¹⁸F]PSMA-1007. For both tracers, lesions kinetics were best described by an irreversible model. All parametric images were of good visual quality using both radiotracers. In general, Ki images were characterized by reduced vascular signal and increased lesion TBR compared with SUV images. No additional malignant lesions were identified on the parametric images.

CONCLUSION

D-WB PET/CT is feasible for both PSMA tracers allowing for direct reconstruction of parametric Ki images. The use of multiparametric PSMA images increased TBR but did not lead to the detection of more lesions. For quantitative whole-body Ki imaging, [¹⁸F]PSMA-1007 should be preferred over [⁶⁸Ga]Ga-PSMA-11 due to its irreversible kinetics in organs and lesions.

Developing a novel positronium biomarker for cardiac myxoma imaging

PURPOSE

Cardiac myxoma (CM), the most common cardiac tumor in adults, accounts for 50-75% of benign cardiac tumors. The diagnosis of CM is often elusive, especially in young stroke survivors and transthoracic echocardiography (TTE) is the initial technique for the differential diagnostics of CM. Less invasive cardiac computed tomography (CT) and magnetic resonance imaging (MRI) are not available for the majority of cardiac patients. Here, a robust imaging approach, ortho-Positronium (o-Ps) imaging, is presented to determine cardiac myxoma extracted from patients undergoing urgent cardiac surgery due to unexpected atrial masses. We aimed to assess if the o-Ps atom, produced copiously in intramolecular voids during the PET imaging, serves as a biomarker for CM diagnosing.

METHODS

Six perioperative CM and normal (adipose) tissue samples from patients, with primary diagnosis confirmed by the histopathology examination, were examined using positron annihilation lifetime spectroscopy (PALS) and micro-CT. Additionally, cell cultures and confocal microscopy techniques were used to picture cell morphology and origin.

RESULTS

We observed significant shortening in the mean o-Ps lifetime in tumor with compare to normal tissues: an average value of 1.92(02) ns and 2.72(05) ns for CM and the adipose tissue, respectively. Microscopic differences between tumor samples, confirmed in histopathology examination and micro-CT, did not influenced the major positronium imaging results.

CONCLUSIONS

Our findings, combined with o-Ps lifetime analysis, revealed the novel emerging positronium imaging marker (o-PS) for cardiovascular imaging. This method opens the new perspective to facilitate the quantitative in vivo assessment of intracardiac masses on a molecular (nanoscale) level.

Four-dimensional quantitative analysis using FDG-PET in clinical oncology

Positron emission tomography (PET) with F-18 fluorodeoxyglucose (FDG) has been commonly used in many oncological areas. High-resolution PET permits a three-dimensional analysis of FDG distributions on various lesions in vivo, which can be applied for tissue characterization, risk analysis, and treatment monitoring after chemoradiotherapy and immunotherapy. Metabolic changes can be assessed using the tumor absolute FDG uptake as standardized uptake value (SUV) and metabolic tumor volume (MTV). In addition, tumor heterogeneity assessment can potentially estimate tumor aggressiveness and resistance to chemoradiotherapy. Attempts have been made to quantify intratumoral heterogeneity using radiomics. Recent reports have indicated the clinical feasibility of a dynamic FDG PET-computed tomography (CT) in pilot cohort studies of oncological cases. Dynamic imaging permits the assessment of temporal changes in FDG uptake after administration, which is particularly useful for differentiating pathological from physiological uptakes with high diagnostic accuracy. In addition, several new parameters have been introduced for the in vivo quantitative analysis of FDG metabolic processes. Thus, a four-dimensional FDG PET-CT is available for precise tissue characterization of various lesions. This review introduces various new techniques for the quantitative analysis of FDG distribution and glucose metabolism using a four-dimensional FDG analysis with PET-CT. This elegant study reveals the important role of tissue characterization and treatment strategies in oncology.

Comparison of cardiac image-derived input functions for quantitative whole body [18F]FDG imaging with arterial blood sampling

Introduction: Dynamic positron emission tomography (PET) and the application of kinetic models can provide important quantitative information based on its temporal information. This however requires arterial blood sampling, which can be challenging to acquire. Nowadays, state-of-the-art PET/CT systems offer fully automated, whole-body (WB) kinetic modelling protocols using image-derived input functions (IDIF) to replace arterial blood sampling. Here, we compared the validity of an automatic WB kinetic model protocol to the reference standard arterial input function (AIF) for both clinical and research settings. Methods: Sixteen healthy participants underwent dynamic WB [18F]FDG scans using a continuous bed motion PET/CT system with simultaneous arterial blood sampling. Multiple processing pipelines that included automatic and manually generated IDIFs derived from the aorta and left ventricle, with and without motion correction were compared to the AIF. Subsequently generated quantitative images of glucose metabolism were compared to evaluate performance of the different input functions. Results: We observed moderate to high correlations between IDIFs and the AIF regarding area under the curve (r = 0.49-0.89) as well as for the cerebral metabolic rate of glucose (CMRGlu) (r = 0.68-0.95). Manual placing of IDIFs and motion correction further improved their similarity to the AIF. Discussion: In general, the automatic vendor protocol is a feasible approach for the quantification of CMRGlu for both, clinical and research settings where expertise or time is not available. However, we advise on a rigorous inspection of the placement of the volume of interest, the resulting IDIF, and the quantitative values to ensure valid interpretations. In protocols requiring longer scan times or where cohorts are prone to involuntary movement, manual IDIF definition with additional motion correction is recommended, as this has greater accuracy and reliability.

Long-axial field-of-view PET/CT: perspectives and review of a revolutionary development in nuclear medicine based on clinical experience in over 7000 patients

Recently introduced long-axial field-of-view (LAFOV) PET/CT systems represent one of the most significant advancements in nuclear medicine since the advent of multi-modality PET/CT imaging. The higher sensitivity exhibited by such systems allow for reductions in applied activity and short duration scans. However, we consider this to be just one small part of the story: Instead, the ability to image the body in its entirety in a single FOV affords insights which standard FOV systems cannot provide. For example, we now have the ability to capture a wider dynamic range of a tracer by imaging it over multiple half-lives without detrimental image noise, to leverage lower radiopharmaceutical doses by using dual-tracer techniques and with improved quantification. The potential for quantitative dynamic whole-body imaging using abbreviated protocols potentially makes these techniques viable for routine clinical use, transforming PET-reporting from a subjective analysis of semi-quantitative maps of radiopharmaceutical uptake at a single time-point to an accurate and quantitative, non-invasive tool to determine human function and physiology and to explore organ interactions and to perform whole-body systems analysis. This article will share the insights obtained from 2 years' of clinical operation of the first Biograph Vision Quadra (Siemens Healthineers) LAFOV system. It will also survey the current state-of-the-art in PET technology. Several technologies are poised to furnish systems with even greater sensitivity and resolution than current systems, potentially with orders of magnitude higher sensitivity. Current barriers which remain to be surmounted, such as data pipelines, patient throughput and the hindrances to implementing kinetic analysis for routine patient care will also be discussed.

Harmonization of standard uptake values across different positron emission tomography/computed tomography systems and different reconstruction algorithms: validation in oncology patients

BACKGROUND

EQ.PET is a software package that overcomes the reconstruction-dependent variation of standard uptake values (SUV). In this study, we validated the use of EQ.PET for harmonizing SUVs between different positron emission tomography/computed tomography (PET/CT) systems and reconstruction algorithms.

METHODS

In this retrospective study, 49 patients with various cancers were scanned on a Biograph mCT (mCT) or Gemini TF 16 (Gemini) after [¹⁸F]FDG injections. Three groups of patient data were collected: Group 1, patients scanned on mCT or Gemini with data reconstructed using two parameters; Group 2, patients scanned twice on different PET scanners (interval between two scans, 68.9 ± 41.4 days); and Group 3, patients scanned twice using mCT with data reconstructed using different algorithms (interval between two scans, 109.5 ± 60.6 days). The SUVs of the lesions and background were measured, and the tumor-to-background ratios (TBRs) were calculated. In addition, the consistency between the two reconstruction algorithms and confounding factors were evaluated.

RESULTS

In Group 1, the consistency of SUV and TBR between different reconstruction algorithms improved when the EQ.PET filter was applied. In Group 2, by comparing ΔSUV, ΔSUV%, ΔTBR, and ΔTBR% with and without the EQ.PET, the results showed significant differences (P < 0.05). In Group 3, Bland-Altman analysis of ΔSUV with EQ.PET showed an improved consistency relative to that without EQ.PET.

CONCLUSIONS

EQ.PET is an efficient tool to harmonize SUVs and TBRs across different reconstruction algorithms. Patients could benefit from the harmonized SUV, ΔSUV, and ΔSUV% for therapy responses and follow-up evaluations.

Does consensus contours improve robustness and accuracy on [Formula: see text]F-FDG PET imaging tumor delineation?

PURPOSE

The aim of this study is to explore the robustness and accuracy of consensus contours with 225 nasopharyngeal carcinoma (NPC) clinical cases and 13 extended cardio-torso simulated lung tumors (XCAT) based on 2-deoxy-2-[[Formula: see text]F]fluoro-D-glucose ([Formula: see text]F-FDG) PET imaging.

METHODS

Primary tumor segmentation was performed with two different initial masks on 225 NPC [Formula: see text]F-FDG PET datasets and 13 XCAT simulations using methods of automatic segmentation with active contour, affinity propagation (AP), contrast-oriented thresholding (ST), and 41% maximum tumor value (41MAX), respectively. Consensus contours (ConSeg) were subsequently generated based on the majority vote rule. The metabolically active tumor volume (MATV), relative volume error (RE), Dice similarity coefficient (DSC) and their respective test-retest (TRT) metrics between different masks were adopted to analyze the results quantitatively. The nonparametric Friedman and post hoc Wilcoxon tests with Bonferroni adjustment for multiple comparisons were performed with [Formula: see text] 0.05 considered to be significant.

RESULTS

AP presented the highest variability for MATV in different masks, and ConSeg presented much better TRT performances in MATV compared with AP, and slightly poorer TRT in MATV compared with ST or 41MAXin most cases. Similar trends were also found in RE and DSC with the simulated data. The average of four segmentation results (AveSeg) showed better or comparable results in accuracy for most cases with respect to ConSeg. AP, AveSeg and ConSeg presented better RE and DSC in irregular masks as compared with rectangle masks. Additionally, all methods underestimated the tumour boundaries in relation to the ground truth for XCAT including respiratory motion.

CONCLUSIONS

The consensus method could be a robust approach to alleviate segmentation variabilities, but did not seem to improve the accuracy of segmentation results on average. Irregular initial masks might be at least in some cases attributable to mitigate the segmentation variability as well.

VTDCE-Net: A time invariant deep neural network for direct estimation of pharmacokinetic parameters from undersampled DCE MRI data

PURPOSE

To propose a robust time and space invariant deep learning (DL) method to directly estimate the pharmacokinetic/tracer kinetic (PK/TK) parameters from undersampled dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data.

METHODS

DCE-MRI consists of 4D (3D-spatial + temporal) data and has been utilized to estimate 3D (spatial) tracer kinetic maps. Existing DL architecture for this task needs retraining for variation in temporal and/or spatial dimensions. This work proposes a DL algorithm that is invariant to training and testing in both temporal and spatial dimensions. The proposed network was based on a 2.5-dimensional Unet architecture, where the encoder consists of a 3D convolutional layer and the decoder consists of a 2D convolutional layer. The proposed VTDCE-Net was evaluated for solving the ill-posed inverse problem of directly estimating TK parameters from undersampled k - t $k-t$ space data of breast cancer patients, and the results were systematically compared with a total variation (TV) regularization based direct parameter estimation scheme. In the breast dataset, the training was performed on patients with 32 time samples, and testing was carried out on patients with 26 and 32 time samples. Translation of the proposed VTDCE-Net for brain dataset to show the generalizability was also carried out. Undersampling rates (R) of 8× , 12× , and 20× were utilized with PSNR and SSIM as the figures of merit in this evaluation. TK parameter maps estimated from fully sampled data were utilized as ground truth.

RESULTS

Experiments carried out in this work demonstrate that the proposed VTDCE-Net outperforms the TV scheme on both breast and brain datasets across all undersampling rates. For K trans $\mathbf {K_{trans}}$ and V p $\mathbf {V_{p}}$ maps, the improvement over TV is as high as 2 and 5 dB, respectively, using the proposed VTDCE-Net.

CONCLUSION

Temporal points invariant DL network that was proposed in this work to estimate the TK-parameters using DCE-MRI data has provided state-of-the-art performance compared to standard image reconstruction methods and is shown to work across all undersampling rates.

High Interobserver Agreement on PSMA PET/CT Even in the Absence of Clinical Data

BACKGROUND

Recommended by current guidelines, prostate-specific membrane antigen (PSMA)-directed PET/CT is increasingly used in men with prostate cancer (PC). We aimed to provide concordance rates using the PSMA reporting and data system (RADS) for scan interpretation and also determine whether such agreement rates are affected by available patient characteristics at time of scan.

PATIENTS AND METHODS

Sixty men with PC, who all underwent 68Ga-PSMA-11 PET/CT, were included. Three independent, experienced readers indicated general scan parameters (including overall scan result, organ or lymph node [LN] involvement, and appropriateness of radioligand therapy). Applying PSMA-RADS 1.0, observers also had to conduct RADS scoring on a target lesion (TL) and overall scan level. During the first read, observers were masked to all relevant clinical information, whereas on a second read, relevant patient characteristics were displayed, thereby allowing for determination of impact of available clinical information for scan interpretation. We used intraclass correlation coefficients (ICCs; with 95% confidence intervals [CIs]), which were then rated according to Cicchetti (0.4-0.59 fair, 0.6-0.74 good, and 0.75-1 excellent agreement).

RESULTS

For general parameters, agreement rates were excellent, including an overall scan result (ICC, 0.85; 95% CI, 0.76-0.90), LN metastases (ICC, 0.89; 95% CI, 0.83-0.93), organ involvement (ICC, 0.82; 95% CI, 0.72-0.89), and indication for radioligand therapy (ICC, 0.94; 95% CI, 0.90-0.96). Overall RADS scoring was also excellent with an ICC of 0.91 (95% CI, 0.96-09.4). On a TL-based level, 251 different lesions were selected by the 3 observers (with 73 chosen by all 3 readers). RADS-based concordance rates were fair to excellent: all lesions, ICC of 0.78 (95% CI, 0.67-0.85); LN, ICC of 0.81 (95% CI, 0.63-0.92); skeleton, ICC of 0.55 (95% CI, 0-0.84); and prostate, ICC of 0.48 (95% CI, 0.17-0.78). When performing a second read displaying patient's characteristics, there were only minor modifications to the previously applied RADS scoring on a TL-based level (overall, n = 8): each reader 1 and 2 in 3/60 (5%) instances, and reader 3 in 2/60 (3.3%) instances. The main reason for recategorization (mainly upstaging) was provided information on PSA levels (4/8, 50%).

CONCLUSIONS

Applying PSMA-RADS, concordance rates were fair to excellent, whereas relevant modifications were rarely observed after providing clinical data. As such, even in the absence of patient information, standardized frameworks still provide guidance for reading PSMA PETs. Those findings may have implications for a high throughput in a busy PET practice, where patient details cannot always be retrieved at time of scan interpretation or in the context of clinical trials or central reviews in which readers may be blinded to clinical data.

Value of whole-body dynamic 18F-FMISO PET/CT Patlak multi-parameter imaging for evaluating the early radiosensitizing effect of oleanolic acid on C6 rat gliomas

The purpose of this study was to investigate the value of tumour-to-muscle (T/M) ratios and Patlak Ki images extracted from whole-body dynamic ¹⁸F-fluoromisonidazole (FMISO) PET/CT Patlak multi-parameter imaging for evaluating the early radiosensitizing effect of oleanolic acid (OA). Twenty-four rats with C6 gliomas were divided into 4 groups and treated with OA (group B), radiotherapy (group C), both (group D) or neither (group A). Whole-body dynamic ¹⁸F-FMISO PET/CT scans were performed for 120 min before treatment and 24 h following the treatment course. The tumour samples were dissected for hematoxylin and eosin staining, and HIF-1α, Ki-67 and GLUT-1 immunohistochemical staining. PET images were analysed using kinetic modelling (Patlak Ki) and static analysis (T/M ratios), and correlated with immunohistochemical results. The changes in T/M ratios, Ki values and tumour volume before treatment and 24 h following the treatment course were compared, and the survival time of tumour-bearing rats was recorded. Kaplan-Meier analysis showed that OA combined with radiotherapy can inhibit tumour growth and prolong the survival time of tumour-bearing rats. Whole-body dynamic ¹⁸F-FMISO PET/CT showed that the Ki values in group D were significantly lower than those in group C, whilst there was no significant difference in T/M ratios between groups C and D. The Pearson correlation coefficient analysis showed that Ki values were significantly related to immunohistochemical results. Our study suggests that Patlak Ki images may add value to PET/CT static images for evaluating the early radio-sensitizing effect of OA.

Ultralow-dose [18F]FDG PET/CT imaging: demonstration of feasibility in dynamic and static images

OBJECTIVES

Validation of [¹⁸F]FDG PET/CT at ultralow-dose (0.37 MBq/kg) and compared to imaging at half-dose (1.85 MBq/kg).

METHODS

This prospective head-to-head intraindividual study compared dynamic and static parameters of ultralow-dose with half-dose [¹⁸F]FDG total-body PET/CT. In static imaging, the ultralow-dose groups of PET images were denoted ULD5, 60-65 min; ULD8, 60-68 min; ULD10, 60-70 min; and ULD15, 60-75 min. The half-dose group images were reconstructed to 60-61, 60-62, 60-63, and 60-75 min, defined as LD1, LD2, LD3, and LD15, respectively. A 5-point Likert scale was used to subjectively evaluate the quality of static PET images, with a score greater than 3 considered to meet the requirements for clinical diagnosis.

RESULTS

Thirty participants were included in this study, and in terms of kinetic indicators, no special differences were found between the two groups of normal organs and lesions. In static images, those in groups ULD8 and LD2 achieved scores of [Formula: see text] 3.0, meeting the requirements for clinical diagnosis. In static imaging, four lesions were missed in the LD1 group with a lesion detectability of 89.7% (35/39). In the meantime, lesions were not missed in the whole ultra-low dose group (ULD5, ULD8, ULD10, and ULD15) and half-dose groups (LD2 and LD3).

CONCLUSIONS

Compared with half-dose imaging, ultralow-dose [¹⁸F]FDG total-body PET/CT imaging is clinically feasible, and there was no meaningful difference between the two groups of quantitative and qualitative analysis either dynamic or static images. Total-body PET/CT with ultralow-dose activity, the corresponding acquisition time of 8 min provides acceptable image quality and lesion detection.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: ChiCTR2000036487 KEY POINTS: • A prospective single-center study showed that the total-body PET scanner allows ultralow-dose [¹⁸F]FDG imaging with acceptable image quality and lesion detectability. • For the participant, radiation exposure can be reduced with ultralow-dose [¹⁸F]FDG total-body PET/CT imaging.

Non-invasive kinetic modelling approaches for quantitative analysis of brain PET studies

Pharmacokinetic modelling with arterial sampling is the gold standard for analysing dynamic PET data of the brain. However, the invasive character of arterial sampling prevents its widespread clinical application. Several methods have been developed to avoid arterial sampling, in particular reference region methods. Unfortunately, for some tracers or diseases, no suitable reference region can be defined. For these cases, other potentially non-invasive approaches have been proposed: (1) a population based input function (PBIF), (2) an image derived input function (IDIF), or (3) simultaneous estimation of the input function (SIME). This systematic review aims to assess the correspondence of these non-invasive methods with the gold standard. Studies comparing non-invasive pharmacokinetic modelling methods with the current gold standard methods using an input function derived from arterial blood samples were retrieved from PubMed/MEDLINE (until December 2021). Correlation measurements were extracted from the studies. The search yielded 30 studies that correlated outcome parameters (V_T, DVR, or BP_ND for reversible tracers; K_i or CMR_glu for irreversible tracers) from a potentially non-invasive method with those obtained from modelling using an arterial input function. Some studies provided similar results for PBIF, IDIF, and SIME-based methods as for modelling with an arterial input function (R² = 0.59-1.00, R² = 0.71-1.00, R² = 0.56-0.96, respectively), if the non-invasive input curve was calibrated with arterial blood samples. Even when the non-invasive input curve was calibrated with venous blood samples or when no calibration was applied, moderate to good correlations were reported, especially for the IDIF and SIME (R² = 0.71-1.00 and R² = 0.36-0.96, respectively). Overall, this systematic review illustrates that non-invasive methods to generate an input function are still in their infancy. Yet, IDIF and SIME performed well, not only with arterial blood calibration, but also with venous or no blood calibration, especially for some tracers without plasma metabolites, which would potentially make these methods better suited for clinical application. However, these methods should still be properly validated for each individual tracer and application before implementation.