Full-Dose PET Image Estimation from Low-Dose PET Image Using Deep Learning: a Pilot Study.

Positron Emission Tomography (PET) has been a commonly used imaging modality in broad clinical applications. One of the most important tradeoffs in PET imaging is between image quality and radiation dose: high image quality comes with high radiation exposure. Improving image quality is desirable for all clinical applications while minimizing radiation exposure is needed to reduce risk to patients. We introduce PET Consistency Model (PET-CM), an efficient diffusion-based method for generating high-quality full-dose PET images from low-dose PET images. It employs a two-step process, adding Gaussian noise to full-dose PET images in the forward diffusion, and then denoising them using a PET Shifted-window Vision Transformer (PET-VIT) network in the reverse diffusion. The PET-VIT network learns a consistency function that enables direct denoising of Gaussian noise into clean full-dose PET images. PET-CM achieves state-of-the-art image quality while requiring significantly less computation time than other methods. Evaluation with normalized mean absolute error (NMAE), peak signal-to-noise ratio (PSNR), multi-scale structure similarity index (SSIM), normalized cross-correlation (NCC), and clinical evaluation including Human Ranking Score (HRS) and Standardized Uptake Value (SUV) Error analysis shows its superiority in synthesizing full-dose PET images from low-dose inputs. In experiments comparing eighth-dose to full-dose images, PET-CM demonstrated impressive performance with NMAE of 1.278±0.122%, PSNR of 33.783±0.824dB, SSIM of 0.964±0.009, NCC of 0.968±0.011, HRS of 4.543, and SUV Error of 0.255±0.318%, with an average generation time of 62 s per patient. This is a significant improvement compared to the state-of-the-art diffusion-based model with PET-CM reaching this result 12× faster. Similarly, in the quarter-dose to full-dose image experiments, PET-CM delivered competitive outcomes, achieving an NMAE of 0.973±0.066%, PSNR of 36.172±0.801dB, SSIM of 0.984±0.004, NCC of 0.990±0.005, HRS of 4.428, and SUV Error of 0.151±0.192% using the same generation process, which underlining its high quantitative and clinical precision in both denoising scenario. We propose PET-CM, the first efficient diffusion-model-based method, for estimating full-dose PET images from low-dose images. PET-CM provides comparable quality to the state-of-the-art diffusion model with higher efficiency. By utilizing this approach, it becomes possible to maintain high-quality PET images suitable for clinical use while mitigating the risks associated with radiation. The code is availble at https://github.com/shaoyanpan/Full-dose-Whole-body-PET-Synthesis-from-Low-dose-PET-Using-Consistency-Model.

Small-animal positron emission tomography as a tool for neuropharmacology

Respiratory motion blurs positron emission tomography (PET) images in thorax and abdominal regions, and can cause attenuation-related errors in quantitative parameters. In addition, this motion can cause localization error and disappearance of tumor(s) near the diaphragm. Respiratory gated PET imaging, or 4D PET imaging, is an attractive solution. For 4D PET, a surrogate measurement of the patient's breathing is made during the scan, and based on this measurement the list-mode PET data are sorted and reconstructed into multiple images. In several studies, it has been reported that 4D PET imaging recovers tumor volume more accurately than 3D PET imaging, and yields more accurate standard uptake values. In spite of its promise, 4D PET images suffer from statistical noise because only a fraction of the acquired data can be used in each image. Moreover, they also suffer from inconsistent attenuation correction due to mismatches between PET and CT images. In this paper, we propose a novel framework for phased attenuation correction and respiratory motion compensation for a 3D PET image by using a 3D CT image and multiple respiratory-phase 3D MR images. For phased attenuation correction, we generate and utilize 4D CT image obtained via non-rigid registrations among a 3D CT image and multiple respiratory-phase 3D MR images. A 3D PET image at a selected respiratory phase is then obtained by adding attenuation corrected multiple 3D PET images through non-rigid transformation. Experimental result for a clinical dataset shows that the proposed algorithm can provide much clearer organ boundary with improved quality than the conventional method in a 3D PET image.

In the management of brainstem lesions, the place of stereotactic biopsy sampling remains debatable. The authors compared the results of magnetic resonance (MR) imaging, positron emission tomography (PET) scanning, and histological studies obtained in 30 patients who underwent MR imaging- and PET-guided stereotactic biopsy procedures for a brainstem mass lesion. Between July 1991 and December 1998, 30 patients harboring brainstem mass lesions underwent a stereotactic procedure in which combined MR imaging and PET scanning guidance were used. Positron emission tomography scanning was performed using [18F]fluorodeoxyglucose in 16 patients, methionine in two patients, and both tracers in 12 patients. Definite diagnosis was established on histological examination of the biopsy samples. Interpretation of MR imaging findings only or PET findings only was in agreement with the histological diagnosis in 63% and 73% of cases, respectively. Magnetic resonance imaging and PET findings were concordant in 19 of the 30 cases; in those cases, imaging data correlated with histological findings in 79%. Treatment based on information derived from MR imaging was concordant with therapy based on histological findings in only 17 patients (57%). Combining MR imaging and PET scanning data, the concordance between the neuroimaging-based treatment and treatments based on histological findings increased to 19 patients (63%). In seven patients who underwent biopsy procedures with one PET-defined and one MR imaging-defined trajectory, at histological examination the PET-guided samples were more representative of the tumor's nature and grade than the MR imaging-guided samples in four cases (57%). In 18 patients PET scanning was used to define a biopsy target and provided a diagnostic yield in 100% of the cases. Although the use of combined PET and MR imaging improves radiological interpretation of a mass lesion in the brainstem, it does not accurately replace histological diagnosis that is provided by a stereotactically obtained biopsy sample. Combining information provided by MR imaging and PET scanning in stereotactic conditions improves the accuracy of targeting and the diagnostic yield of the biopsy sample; an MR imaging- and PET-guided stereotactic biopsy procedure is a safe and efficient modality for the management of mass lesions of the brainstem.

To evaluate a new iterative reconstruction (IR) algorithm for radiation dose, image quality (IQ), signal-to-noise-ratio (SNR), and contrast-to-noise-ratio (CNR) in multidetector computed tomography (MDCT) dynamic myocardial perfusion imaging (MPI). ECG-gated 256-slice MDCT dynamic MPI was performed in six pigs after subtotal balloon occlusion of one artery. Two 100 kVp protocols were compared: high dose (HD): 150 mAs; low dose (LD): 100 mAs. HD images were reconstructed with filtered back projection (FBP), LD images with FBP and different strengths of IR (L1, L4, and L7). IQ (5-point scale), SNR, and CNR (ischemic vs. normal myocardium) values derived from the HD (FBP) images and the different LD images were compared. Mean SNR values for myocardium were 16.3, 11.3, 13.1, 17.1, and 28.9 for the HD, LD (FBP), LD (L1), LD (L4), and LD (L7) reconstructions, respectively. Mean CNR values were 8.9, 6.3, 7.8, 9.3, and 12.8. IQ was scored as 4.6, 3.3, 4.4, 4.7, and 3.4, respectively. A significant loss of IQ was observed for the LD (L7) images compared to the HD (FBP) images (P < 0.05). Appropriate levels of iterative reconstruction can improve SNR and CNR, facilitating radiation dose savings in CT-MPI without influencing diagnostic quality. Iterative reconstruction (IR) can reduce radiation dose in myocardial perfusion CT. Our study also demonstrated improvements in image quality (noise, SNR, and CNR). Dynamic CT-MPI could help determine the hemodynamic significance of coronary artery disease. With dynamic CT MPI, myocardial blood flow can be determined quantitatively.

A wide array of positron emission tomography (PET) ligands have been developed that provide information relevant to multiple aspects of addiction (1-3).Locations of targets are approximated on this diagram, which is color-coded by functional roles.On the presynaptic side (pink), targets include neurotransmitter precursors (orange, example [ 18 F]-fluorodopa, FDOPA), modulatory receptors (yellow, examples [ 11 C] GR103545, [ 11 C] LY27950509 and [ 18 F] LY2459989 for kappa opioid receptors, KOR; [ 18 F]FMPEP for cannabinoid 1 receptors, CB1), and neurotransmitter reuptake transporters (light green, examples [ 11 C] PE2I and [ 18 F] FE-PE2I for the dopamine transporter, DAT).On the postsynaptic side (purple), targets include neurotransmitter receptors (blue, examples [ 11 C] raclopride and [ 11 C]-(1)-PHNO for dopamine D 2 and D 3 receptors, D 2 R; [ 11 C] carfentanil for mu opioid receptors, MOR; [ 18 F] LY2459989 for both mu and kappa opioid receptors; 2-[ 18 F]fluoro-3-(2(S)-azetidinylmethoxy) pyridine for nicotinic acetylcholine receptors, nAChR).Some PET ligands target more generic functions.[ 18 F]-fluoro-deoxy-glucose (FDG) PET provides a measure of cerebral metabolic rate.

The Case Against Heavy PETing

612 Background: Breast Conservation Therapy (BCT) for early breast cancer is an effective option in selected patients with primary breast cancer. Mammographic evaluation of breast abnormalities developing after BCT can be difficult. Positron Emission Tomography (PET) is a valuable imaging tool in oncology. We investigated the efficacy of PET imaging in predicting the nature of suspicious breast changes following BCT. Methods: All patients with prior BCT with suspicious mammographic or breast examination findings necessitating biopsy evaluation were offered participation. After signed informed consent, PET imaging was performed using F-18 FDG General Electric PET scanner. Breast biopsy was obtained following the PET scan. Pathologic findings were correlated with the PET findings. Results: 33 patients were enrolled in the study between 6/1997 and 11/2003 with 31 patients completing both PET imaging and breast biopsy. The population characteristics at the time of the original breast cancer diagnosis were as follows: (1) Race and age: African Americans 21 (68%) (mean age = 46.8), Caucasian 10(32%) (mean age = 52.8). (2) Tumor size: 7 tumors ≤ 10mm, 11 between 11–20mm, 11 between 21–30mm, and 2 between 31–50mm. (3) Nodal Status: 21(68%) node negative, 10(32%) node positive. (4) Hormone receptor status: 51% negative, 49% positive.Biopsy/PET Results: 58% of the surgical biopsies were negative while 42% were positive (recurrent disease). 58% of PET scans were negative while 42% were positive. There was 1 false negative PET scans and 1 false positive scan. Overall the sensitivity of PET was 92.31%;while specificity was 94.44%. Positive predictive value of PET was 92.31%. PET scan was highly consistent with biopsy results (Kappa Co-efficient k=0.92). The single patient with a negative biopsy following a positive PET scan was found to have wide spread metastatic disease. The single patient with negative PET, but positive disease by biopsy had DCIS. Conclusions: PET imaging appears to be a reliable radiographic approach for the initial evaluation of suspicious breast lesions developing after BCT. No significant financial relationships to disclose.

612 Background: Breast Conservation Therapy (BCT) for early breast cancer is an effective option in selected patients with primary breast cancer. Mammographic evaluation of breast abnormalities developing after BCT can be difficult. Positron Emission Tomography (PET) is a valuable imaging tool in oncology. We investigated the efficacy of PET imaging in predicting the nature of suspicious breast changes following BCT. Methods: All patients with prior BCT with suspicious mammographic or breast examination findings necessitating biopsy evaluation were offered participation. After signed informed consent, PET imaging was performed using F-18 FDG General Electric PET scanner. Breast biopsy was obtained following the PET scan. Pathologic findings were correlated with the PET findings. Results: 33 patients were enrolled in the study between 6/1997 and 11/2003 with 31 patients completing both PET imaging and breast biopsy. The population characteristics at the time of the original breast cancer diagnosis were as follows: (1) Race and age: African Americans 21 (68%) (mean age = 46.8), Caucasian 10(32%) (mean age = 52.8). (2) Tumor size: 7 tumors ≤ 10mm, 11 between 11–20mm, 11 between 21–30mm, and 2 between 31–50mm. (3) Nodal Status: 21(68%) node negative, 10(32%) node positive. (4) Hormone receptor status: 51% negative, 49% positive.Biopsy/PET Results: 58% of the surgical biopsies were negative while 42% were positive (recurrent disease). 58% of PET scans were negative while 42% were positive. There was 1 false negative PET scans and 1 false positive scan. Overall the sensitivity of PET was 92.31%;while specificity was 94.44%. Positive predictive value of PET was 92.31%. PET scan was highly consistent with biopsy results (Kappa Co-efficient k=0.92). The single patient with a negative biopsy following a positive PET scan was found to have wide spread metastatic disease. The single patient with negative PET, but positive disease by biopsy had DCIS. Conclusions: PET imaging appears to be a reliable radiographic approach for the initial evaluation of suspicious breast lesions developing after BCT. No significant financial relationships to disclose.

Positive Positron Emission Tomography (PET) Scan in Non-Hodgkin Lymphoma Pre-Transplant Had No Impact On Relapse and Survival After Allogenenic Transplantation

Multiplexed Positron Emission Tomography (PET) imaging allows simultaneous acquisition of multiple radiotracer signals, thus enhancing diagnostic capabilities, reducing scan times, and improving patient comfort. Traditional methods often require significant delays between tracer injections, leading to physiological changes and noise interference. Recent advancements, including multi-tracer compartment modeling and machine learning, provide promising solutions. This study explores the deep learning (DL)-based single-session triple-tracer brain PET imaging protocol, aiming at simplifying multi-tracer PET imaging, while reducing radiation exposure. The study uses the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, which includes cognitively normal (CN) patients, as well as patients with mild cognitive impairment (MCI) and dementia. The dataset also includes PET scans acquired with amyloid (18F-florbetaben [FBB] or 18F-florbetapir [FBP]), 18F-Fluorodeoxyglucose (FDG), and tau 18F-flortaucipir (FTP). To mimic the effect of simultaneous acquisition of multiple PET tracers, we generated synthetic dual- and triple-tracer images by summing FBP/FBB, FTP, and FDG scans. A DL model based on Swin Transformer architecture was developed to separate these signals, using five-fold cross-validation and mean squared error (MSE) loss. The synthetic PET images were evaluated using established image quality metrics, including MSE, structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR). In addition, clinical evaluation was conducted by two nuclear medicine specialists to assess the amyloid and tau status in the synthetic and reference images. The proposed DL model effectively synthesized realistic FBB/FBP and FDG images from dual- and triple-tracer PET images. Although the proposed DL model's performance in generating FTP images was less successful, it remains promising. The clinical evaluation revealed that the amyloid status estimated from the synthetic images led to a sensitivity of 92% and specificity of 86% for FBB, while it showed a sensitivity of 93% and specificity of 67% for tau status using FBP extracted from the triple-tracer images. The calculated quantitative metrics showed that the mean error for synthetic amyloid images (FBB: 0.03 SUV, FBP: 0.00 SUV) was higher than FDG for FBB (0.02 SUV) but lower than FDG for FBP (-0.01 SUV), and comparable to FTP (FBB: 0.03 SUV, FBP: 0.00 SUV). Voxel-wise correlation analysis demonstrated strong correlation between synthetic and reference images, particularly for amyloid images (FBB: y = 0.98x + 0.00, R² = 0.85; FBP: y = 1.11x + 0.04, R² = 0.73), while FTP (FBB: y = 0.87x + 0.14, R² = 0.51; FBP: y = 0.98x + 0.09, R² = 0.59) and FDG images (FBB: y = 1.01x + 0.18, R² = 0.85; FBP: y = 0.96x + 1.37, R² = 0.77) showed moderate correlations. Our study demonstrates that the suggested DL model can separate the signals belonging to three different radiotracers from simultaneous triple-tracer PET scans. This method may make multiplex scanning feasible in the clinic, hence reducing the scanning time, radiation hazard and improving patient comfort.

Whole-body positron emission tomography (PET) with F-fluorodeoxyglucose (FDG) has proven to be a very effective staging imaging modality in manymalignant tumours, particularly in lung cancer, malignant melanoma, lymphoma, colorectal cancer and head and neck tumours [1–7]. Since PET images have a fairly high resolution (,6 mm), even small lesions with an increased FDG uptake can be detected. This represents a critical advantage of PET over the conventional cross-sectional imaging modalities CT and MRI. PET can be used to identify tumour tissue on the basis of FDG uptake, rather than on the basis of morphological appearance or size, and thus also in lesions with a size less than 1 cm. Unfortunately, FDG–PET provides little anatomical information, and therefore it is sometimes difficult to determine where the lesions detected are located and what they represent. It is important for the surgeon to know precisely where lesions are located, especially for small tumours. Currently, comparison and juxtaposition of PET images and CT images serves to define the localization of the lesions. Owing to the different image slice thickness, the different positioning of the patient during the two examinations and the different states of nutrition, i.e. fasting for 4 h prior to FDG–PET, it is often very difficult and time consuming to match the images for exact anatomical localization. Image co-registration has been used to overcome these problems [8]. It has been recognized that proper image co-registration is rather difficult for whole-body examinations with separate scanners. For identical patient positioning during PET and CT scanning, special ‘‘cast forming’’ vacuum mattresses or other immobilization methods should be used. However, patients frequently find these methods of immobilization uncomfortable. Logistic problems also limit the use of image co-registration of PET and CT with separate scanners. Scheduling problems arise when performing the two examinations one after the other. These limitations restrict image co-registration with separate scanners to individual cases. In our experience, the exact localization of lesions is often not possible when juxtaposing PET and CT images. Examinations had to be repeated for exact image co-registration. As a result, image co-registration with separate scanners has never become routine in our practice. To overcome the problems related to software fusion, various prototype systems combining molecular and morphologic imaging have been developed. Hasegawa and colleagues proposed an integrated SPECT/CT scanner [9], and in 1999 Townsend and his colleagues at the University of Pittsburgh presented a prototype integrated PET/CT scanner by combining a CT scanner and a partial ring, rotating PET scanner in a single gantry [10, 11]. Such systems are attractive not only because of the ‘‘hardware’’ image coregistration capabilities but also because the CT data can be used to correct PET scans for patient self-absorption of the PET emission rays. This decreases the acquisition time for the correcting attenuation scans by an order of magnitude compared with the conventional techniques used in PET for this purpose, and decreases the overall imaging time by up to 30% depending on the CT system used. In March 2001, the first clinical integrated PET/ CT device (Discovery LS, GE Medical Systems, Milwaukee, USA) was installed at the University Hospital of Zurich in Switzerland. This novel inline system consists of a dedicated high resolution/ high sensitivity full-ring PET scanner (Advance Nxi) and a very fast high-end multi-detector spiral CT scanner (Light Speed Plus). The axes of both systems are mechanically aligned so that simple translation of the patient table by 60 cm moves the patient from the CT into the PET gantry. The resulting PET and CT images are ‘‘hardware’’ coregistered to an accuracy in the range of 1 mm. Data acquisition in the combined system is as follows. At 45–55 min post-injection of FDG and after bladder emptying a multidetector computed tomography scan is performed from the pelvic floor to the head (scan length, 86.7 cm) and normal end-expiration. Immediately after CT scanning, a PET emission scan is obtained covering the identical axial field of view using six PET fields of view. The acquisition time is 4 min at each table position. With this protocol it is The British Journal of Radiology, 75 (2002), S36–S38 E 2002 The British Institute of Radiology

Accurate identification of eloquent cortex is important to ensure that resective surgery in the region surrounding the central sulcus is performed with minimum risk of permanent neurological deficit. Functional localization has traditionally been accomplished using intraoperative cortical stimulation (ICS). However, this technique suffers from several disadvantages that make the development and validation of noninvasive methods desirable. Functional localization accomplished by activation studies in which positron emission tomography (PET) scanning and the tracer [15O]H2O have been used has been shown to correlate well with the results of ICS. Another noninvasive method for functional localization is functional magnetic resonance (fMR) imaging. We compared the locations of activation peaks obtained in individual patients using fMR and [15O]H2O PET imaging. Twenty-six combined PET activation-fMR imaging studies were performed in 11 patients who were admitted for evaluation before undergoing surgery in the region surrounding the central sulcus. The PET scans were obtained using bolus injections of the cerebral blood flow tracer [15O]H2O (10 mCi). Multislice T2*-weighted gradient-echo echoplanar images were acquired using a 1.5-tesla MR imaging system. Activation maps were aligned with anatomical MR images and transformed into stereotactic space, after which the locations of activation peaks obtained using both modalities were compared. The average distance between activation peaks obtained using fMR imaging and those obtained using PET imaging was 7.9+/-4.8 mm (p>0.05), with 96% of the peaks being located on either the same or adjacent sulci and gyri. Overlapping of voxels activated by each modality occurred in 92% of the studies. Functional MR imaging failed to activate the primary sensorimotor cortex in one study and produced results that were ambiguous in the clinical setting in three cases. Overall, fMR imaging produced activation that correlated well with that obtained using PET scanning. Discrepancies between the sites of activation identified using these two techniques may reflect differences in their physiological bases.

What Is the Role of Positron Emission Tomography in Osteonecrosis of the Jaws?

17113 Background: MPM is a rapidly progressive malignancy with a median survival of 6 to 9 months. Studies in non-small cell lung cancer, gastrointestinal stromal tumours, and breast cancer suggest that Positron Emission Tomography (PET) scanning may predict the clinical outcome of chemotherapy at an early stage of treatment. The role of PET in predicting and monitoring response to treatment in MPM is unclear. In this study we assessed if baseline and early interval PET scanning could be of benefit in MPM, correlating the results with standard Computerised Tomography (CT) assessment using the modified Response Evaluation Criteria In Solid Tumours (RECIST) of Byrne and Nowak. Methods: 10 patients with histologically proven MPM proceeded to baseline PET and CT scanning prior to chemotherapy. In 8 patients a second PET scan was performed within three weeks of commencing treatment. The following PET derived parameters were calculated: Standard Uptake Value (SUV)maximum, SUVaverage, PETvolume, and Total Lesion Glycolysis (TLG). Baseline SUVmaximum and early PET response was compared with CT response and survival. Results: Baseline SUVmaximum predicted subsequent CT response in the 10 patients studied. Four out of 5 patients with baseline SUVmaximum of &lt;15 showed a subsequent partial response on CT, whilst the 5th patient had resolution of a pleural effusion. All 5 patients with baseline SUVmaximum of &gt;15 had stable or progressive disease on CT. In contrast change in early SUVmaximum from baseline to 3 weeks did not predict subsequent CT response (Kappa value 0.07) in the 8 patients evaluated. Change in PET volume and TLG correlated with subsequent CT response (Kappa value= 0.80 for both). Only 1 patient with a partial response on % PETvolume and %TLG has died 14 months after commencing treatment. The other 3 patients are alive at 17+, 19+ and 20+ months. The 4 patients with stable or progressive disease using these parameters were deceased at 5, 6, 10, and 12 months respectively. Conclusion: PET may be useful in predicting and evaluating response to treatment in MPM. Furthermore, the results suggest that PET response may be a useful prognostic tool in this disease. It is important to use the appropriate PET derived parameters. Further study with a larger patient population is warranted. No significant financial relationships to disclose.