Fully automated computational measurement of noise in positron emission tomography.

OBJECTIVES: To introduce an automated computational algorithm that estimates the global noise level across the whole imaging volume of PET datasets. METHODS: [18F]FDG PET images of 38 patients were reconstructed with simulated decreasing acquisition times (15-120 s) resulting in increasing noise levels, and with block sequential regularized expectation maximization with beta values of 450 and 600 (Q.Clear 450 and 600). One reader performed manual volume-of-interest (VOI) based noise measurements in liver and lung parenchyma and two readers graded subjective image quality as sufficient or insufficient. An automated computational noise measurement algorithm was developed and deployed on the whole imaging volume of each reconstruction, delivering a single value representing the global image noise (Global Noise Index, GNI). Manual noise measurement values and subjective image quality gradings were compared with the GNI. RESULTS: Irrespective of the absolute noise values, there was no significant difference between the GNI and manual liver measurements in terms of the distribution of noise values (p = 0.84 for Q.Clear 450, and p = 0.51 for Q.Clear 600). The GNI showed a fair to moderately strong correlation with manual noise measurements in liver parenchyma (r = 0.6 in Q.Clear 450, r = 0.54 in Q.Clear 600, all p < 0.001), and a fair correlation with manual noise measurements in lung parenchyma (r = 0.52 in Q.Clear 450, r = 0.33 in Q.Clear 600, all p < 0.001). Classification performance of the GNI for subjective image quality was AUC 0.898 for Q.Clear 450 and 0.919 for Q.Clear 600. CONCLUSION: An algorithm provides an accurate and meaningful estimation of the global noise level encountered in clinical PET imaging datasets. CLINICAL RELEVANCE STATEMENT: An automated computational approach that measures the global noise level of PET imaging datasets may facilitate quality standardization and benchmarking of clinical PET imaging within and across institutions. KEY POINTS: • Noise is an important quantitative marker that strongly impacts image quality of PET images. • An automated computational noise measurement algorithm provides an accurate and meaningful estimation of the global noise level encountered in clinical PET imaging datasets. • An automated computational approach that measures the global noise level of PET imaging datasets may facilitate quality standardization and benchmarking as well as protocol harmonization.

Fluoro-deoxy-glucose uptake in the mylohyoid muscle: a common misconception.

AIM: The mylohyoid muscle is often believed to exhibit high physiologic fluoro-deoxy-glucose (FDG) uptake. Aim of this study was to use PET/MR for adequately assessing the normal FDG distribution in floor of the mouth (FOM) muscles and neighboring major salivary glands. MATERIALS AND METHODS: Patients scanned with a simultaneous PET/MRI system for initial staging or follow-up of head and neck tumors, with no malignant lesions in salivary glands or in FOM, were included. Volumes-of-interest (VOIs) were positioned separately for bilateral mylohyoid, digastric, genioglossus, and geniohyoid muscles, based on T2-weighted and T1-weighted images, and for bilateral parotid, submandibular, and sublingual glands in the same way. SUVmax was measured for each VOI. RESULTS: Six hundred and ninety-two VOIs were positioned. FDG uptake in mylohyoid (SUVmax = 1.94 ± 0.37) and digastric muscles (SUVmax = 2.01 ± 0.37) were significantly higher compared to that in geniohyoid (SUVmax = 1.67 ± 0.53) and genioglossus muscles (SUVmax = 1.75 ± 0.54) (Friedman's test; P < 0.001). FDG uptake in the sublingual glands (SUVmax = 3.77 ± 1.63) was significantly higher compared to the parotid glands (SUVmax = 2.34 ± 0.60) and submandibular glands (SUVmax = 2.51 ± 0.59) (Wilcoxon signed-ranks test; P < 0.001). FDG uptake in sublingual glands was significantly higher than FDG uptake in the mylohyoid muscles (P < 0.001). FDG uptake in the parotid, submandibular, and sublingual glands was inversely correlated to the age of subjects (Spearman' rho coefficient: -0.397/P = 0.004; -0.329/P = 0.021; -0.535/P < 0.001, respectively). CONCLUSION: The sublingual glands yield the highest physiologic FDG uptake in the FOM. High FDG uptake in the mylohyoid muscle is a common misconception.

Artificial intelligence for detecting small FDG-positive lung nodules in digital PET/CT: impact of image reconstructions on diagnostic performance.

OBJECTIVES: To evaluate the diagnostic performance of a deep learning algorithm for automated detection of small 18F-FDG-avid pulmonary nodules in PET scans, and to assess whether novel block sequential regularized expectation maximization (BSREM) reconstruction affects detection accuracy as compared to ordered subset expectation maximization (OSEM) reconstruction. METHODS: Fifty-seven patients with 92 18F-FDG-avid pulmonary nodules (all ≤ 2 cm) undergoing PET/CT for oncological (re-)staging were retrospectively included and a total of 8824 PET images of the lungs were extracted using OSEM and BSREM reconstruction. Per-slice and per-nodule sensitivity of a deep learning algorithm was assessed, with an expert readout by a radiologist/nuclear medicine physician serving as standard of reference. Receiver-operator characteristic (ROC) curve of OSEM and BSREM were assessed and the areas under the ROC curve (AUC) were compared. A maximum standardized uptake value (SUVmax)-based sensitivity analysis and a size-based sensitivity analysis with subgroups defined by nodule size was performed. RESULTS: The AUC of the deep learning algorithm for nodule detection using OSEM reconstruction was 0.796 (CI 95%; 0.772-0.869), and 0.848 (CI 95%; 0.828-0.869) using BSREM reconstruction. The AUC was significantly higher for BSREM compared to OSEM (p = 0.001). On a per-slice analysis, sensitivity and specificity were 66.7% and 79.0% for OSEM, and 69.2% and 84.5% for BSREM. On a per-nodule analysis, the overall sensitivity of OSEM was 81.5% compared to 87.0% for BSREM. CONCLUSIONS: Our results suggest that machine learning algorithms may aid detection of small 18F-FDG-avid pulmonary nodules in clinical PET/CT. AI performed significantly better on images with BSREM than OSEM. KEY POINTS: • The diagnostic value of deep learning for detecting small lung nodules (≤ 2 cm) in PET images using BSREM and OSEM reconstruction was assessed. • BSREM yields higher SUVmaxof small pulmonary nodules as compared to OSEM reconstruction. • The use of BSREM translates into a higher detectability of small pulmonary nodules in PET images as assessed with artificial intelligence.

Impact of different image reconstructions on PET quantification in non-small cell lung cancer: a comparison of adenocarcinoma and squamous cell carcinoma.

OBJECTIVE:: Positron emission tomography (PET) using 18F-fludeoxyglucose (18F-FDG) is an established imaging modality for tumor staging in patients with non-small cell lung cancer (NSCLC). There is a growing interest in using 18F-FDG PET for therapy response assessment in NSCLC which relies on quantitative PET parameters such as standardized uptake values (SUV). Different reconstruction algorithms in PET may affect SUV. We sought to determine the variation of SUV in patients with NSCLC when using ordered subset expectation maximization (OSEM) and block sequential regularized expectation maximization (BSREM) in latest-generation digital PET/CT, including a subanalysis for adenocarcinoma and squamous cell carcinoma. METHODS:: A total of 58 patients (34 = adenocarcinoma, 24 = squamous cell carcinoma) who underwent a clinically indicated 18F-FDG PET/CT for staging were reviewed. PET images were reconstructed with OSEM and BSREM reconstruction with noise penalty strength ß-levels of 350, 450, 600, 800 and 1200. Lung tumors maximum standardized uptake value (SUVmax) were compared. RESULTS:: Lung tumors SUVmax were significantly lower in adenocarcinomas compared to squamous cell carcinomas in all reconstructions evaluated (all p < 0.01). Comparing BSREM to OSEM, absolute SUVmax differences were highest in lower ß-levels of BSREM with + 2.9 ± 1.6 in adenocarcinoma and + 4.0 ± 2.9 in squamous cell carcinoma (difference between histology; p-values > 0.05). There was a statistically significant difference of the relative increase of SUVmax in adenocarcinoma (mean + 34.8%) and squamous cell carcinoma (mean 23.4%), when using BSREM350 instead of OSEMTOF (p < 0.05). CONCLUSION:: In NSCLC the relative change of SUV when using BSREM instead of OSEM is significantly higher in adenocarcinoma as compared to squamous cell carcinoma. ADVANCES IN KNOWLEDGE:: The impact of BSREM on SUV may vary in different histological subtypes of NSCLC. This highlights the importance for careful standardization of ß-value used for serial 18F-FDG PET scans when following-up NSCLC patients.

Clinical impact of 68Ga-PSMA-11 PET on patient management and outcome, including all patients referred for an increase in PSA level during the first year after its clinical introduction.

PURPOSE: The fast-increasing use of positron emission tomography (PET) with prostate-specific membrane antigen (PSMA) ligand for the imaging of prostate cancer (PCA) biochemical recurrence has led to a rapid change in treatment concepts. Since the superiority of 68Ga-PSMA-11 PET in detecting recurrent PCA is well established, the aim of our study was to assess its effect on management and outcome in all patients imaged during the first year after its introduction into clinical routine. METHODS: Of 327 patients imaged, 223 were referred for recurrent PCA and gave written informed consent for further analysis of their data for this retrospective consecutive cohort analysis. Twenty patients were lost to further follow-up. The rate of detection of recurrence by 68Ga-PSMA-11 PET was based on the clinical reports. Management before the availability of PET diagnostic information was assessed according to guidelines (therapy option without 68Ga-PSMA-11 PET). In the 203 patients with follow-up 6 months after 68Ga-PSMA-11 PET, the therapies effectively implemented as well as follow-up PSA levels were evaluated, with a PSA value of <0.2 ng/ml representing a complete response and a decrease in PSA value of at least 50% from baseline representing a partial response. RESULTS: 68Ga-PSMA-11 PET was positive and identified recurrence in 166 of the 223 patients (74%), with a detection rate of 50% for recurrent disease at low PSA values of <0.5 ng/ml. 68Ga-PSMA-11 PET led to a change in management in 122 of the 203 patients (60%). A substantial increase in the use of metastasis-targeted treatment and a reduction in the use of systemic treatment were observed, with 59 of the 203 patients (29%) undergoing targeted radiotherapy (RTXa) only, and 20 patients (10%) undergoing RTXa with hormonal therapy as the two most frequently selected therapy options. The proportion of patients in whom systemic therapy was selected decreased from 60% (133 of 223 patients) to 34% (70 of 203 patients) on the basis of the information provided by the 68Ga-PSMA-11 PET scan. PSMA PET-directed metastasis-targeted treatment led to a complete response after 6 months in 45% of patients. CONCLUSION: The high rate of recurrence detection by PSMA PET was confirmed and PSMA PET led to a change in management in 60% of patients. Focal therapy for PSMA-positive lesions is a promising approach with complete responses in 45% of patients.

Automated detection of lung cancer at ultralow dose PET/CT by deep neural networks - Initial results.

OBJECTIVES: We evaluated whether machine learning may be helpful for the detection of lung cancer in FDG-PET imaging in the setting of ultralow dose PET scans. MATERIALS AND METHODS: We studied the performance of an artificial neural network discriminating lung cancer patients (n = 50) from controls (n = 50) without pulmonary malignancies. A total of 3936 PET slices including images in which the lung tumor is visually present and image slices of patients with no lung cancer were exported. The diagnostic performance of the artificial neural network based on clinical standard dose PET images (PET100%) as well as with a tenfold (PET10%) and thirtyfold (PET3.3%) reduced radiation dose (∼0.11 mSv) was assessed. RESULTS: The area under the curve of the deep learning algorithm for lung cancer detection was 0.989, 0.983 and 0.970 for standard dose images (PET100%), and reduced dose PET10%, and PET3.3% reconstruction, respectively. The artificial neural network achieved a sensitivity of 95.9% and 91.5% and a specificity of 98.1% and 94.2%, at standard dose and ultralow dose PET3.3%, respectively. CONCLUSION: Our results suggest that machine learning algorithms may aid fully automated lung cancer detection even at very low effective radiation doses of 0.11 mSv. Further improvement of this technology might improve the specificity of lung cancer screening efforts and could lead to new applications of FDG-PET.

Impact of a Bayesian penalized likelihood reconstruction algorithm on image quality in novel digital PET/CT: clinical implications for the assessment of lung tumors.

BACKGROUND: The aim of this study was to evaluate and compare PET image reconstruction algorithms on novel digital silicon photomultiplier PET/CT in patients with newly diagnosed and histopathologically confirmed lung cancer. A total of 45 patients undergoing 18F-FDG PET/CT for initial lung cancer staging were included. PET images were reconstructed using ordered subset expectation maximization (OSEM) with time-of-flight and point spread function modelling as well as Bayesian penalized likelihood reconstruction algorithm (BSREM) with different ß-values yielding a total of 7 datasets per patient. Subjective and objective image assessment with all image datasets was carried out, including subgroup analyses for patients with high dose (> 2.0 MBq/kg) and low dose (≤ 2.0 MBq/kg) of 18F-FDG injection regimen. RESULTS: Subjective image quality ratings were significantly different among all different reconstruction algorithms as well as among BSREM using different ß-values only (both p < 0.001). BSREM with a ß-value of 600 was assigned the highest score for general image quality, image sharpness, and lesion conspicuity. BSREM reconstructions resulted in higher SUVmax of lung tumors compared to OSEM of up to + 28.0% (p < 0.001). BSREM reconstruction resulted in higher signal-/ and contrast-to-background ratios of lung tumor and higher signal-/ and contrast-to-noise ratio compared to OSEM up to a ß-value of 800. Lower ß-values (BSREM450) resulted in the best image quality for high dose 18F-FDG injections, whereas higher ß-values (BSREM600) lead to the best image quality in low dose 18F-FDG PET/CT (p < 0.05). CONCLUSIONS: BSREM reconstruction algorithm used in digital detector PET leads to significant increases of lung tumor SUVmax, signal-to-background ratio, and signal-to-noise ratio, which translates into a higher image quality, tumor conspicuity, and image sharpness.

Local resectability assessment of head and neck cancer: Positron emission tomography/MRI versus positron emission tomography/CT.

BACKGROUND: The purpose of this study was to compare the diagnostic accuracy of positron emission tomography (PET)/MRI with PET/CT for local resectability of head and neck cancer. METHODS: Sequential contrast-enhanced PET/CT-MRI was performed in 58 patients referred for the staging or restaging of head and neck cancer. Tumors were assessed with PET/CT and PET/MRI for the presence of resectability-defining factors: T4b status (mediastinal invasion, invasion of the prevertebral space, and vascular encasement), and another 8 findings that would imply obstacles for surgical cure (invasion of the laryngeal cartilage, invasion of the preepiglottic fat pad, perineural spread, orbital invasion, bone infiltration, skull base invasion, dural infiltration, and invasion of the brachial plexus). RESULTS: The sensitivity/specificity/accuracy of local resectability-defining factors of PET/CT and PET/MRI was 0.92/0.99/0.98 and 0.98/0.99/0.99 (P = .727), respectively, per lesion, and 0.96/0.87/0.91 and 0.96/0.90/0.93 (P = .687), respectively, per patient. CONCLUSION: Both contrast-enhanced PET/MRI and contrast-enhanced PET/CT can serve as reliable examinations for defining local resectability of head and neck cancer.

PET+MR versus PET/CT in the initial staging of head and neck cancer, using a trimodality PET/CT+MR system.

PURPOSE: To compare the diagnostic accuracy of PET+MR with PET/CT in the initial staging of head and neck cancer. MATERIALS AND METHODS: Contrast-enhanced PET/CT+MR was performed in 27 patients with newly diagnosed head and neck cancer. PET/CT and PET+MR were evaluated separately, and the TNM stage and factors influencing treatment were assessed. RESULTS: The TNM staging by PET+MR was comparable to PET/CT (T: p=0.331, N: p=0.453, M: p=0.034). The sensitivity/specificity/accuracy of treatment-influencing factors by PET/CT and PET+MR were 0.68/0.99/0.97, and 1.00/1.00/0.99, respectively. CONCLUSIONS: Whole-body staging with PET+MR yields at least equal diagnostic accuracy as PET/CT in head and neck cancer.

PET/MR Outperforms PET/CT in Suspected Occult Tumors.

BACKGROUND: To compare the diagnostic accuracy of PET/MR and PET/CT in patients with suspected occult primary tumors. METHODS: This prospective study was approved by the institutional review board. Sequential PET/CT-MR was performed in 43 patients (22 male subjects; median age, 58 years; range, 20-86 years) referred for suspected occult primary tumors. Patients were assessed with PET/CT and PET/MR for the presence of a primary tumor, lymph node metastases, and distant metastases. Wilcoxon signed-rank test was performed to compare the diagnostic accuracy of PET/CT and PET/MR. RESULT: According to the standard of reference, a primary lesion was found in 14 patients. In 16 patients, the primary lesion remained occult. In the remaining 13 patients, lesions proved to be benign. PET/MR was superior to PET/CT for primary tumor detection (sensitivity/specificity, 0.85/0.97 vs 0.69/0.73; P = 0.020) and comparable to PET/CT for the detection of lymph node metastases (sensitivity/specificity, 0.93/1.00 vs 0.93/0.93; P = 0.157) and distant metastases (sensitivity/specificity, 1.00/0.97 vs 0.82/1.00; P = 0.564). PET/CT tended to misclassify physiologic FDG uptake as malignancy compared with PET/MR (8 patients vs 1 patient). CONCLUSIONS: PET/MR outperforms PET/CT in the workup of suspected occult malignancies. PET/MR may replace PET/CT to improve clinical workflow.

Clinical evaluation of a block sequential regularized expectation maximization reconstruction algorithm in 18F-FDG PET/CT studies.

PURPOSE: To investigate the clinical performance of a block sequential regularized expectation maximization (BSREM) penalized likelihood reconstruction algorithm in oncologic PET/computed tomography (CT) studies. METHODS: A total of 410 reconstructions of 41 fluorine-18 fluorodeoxyglucose-PET/CT studies of 41 patients with a total of 2010 lesions were analyzed by two experienced nuclear medicine physicians. Images were reconstructed with BSREM (with four different ß values) or ordered subset expectation maximization (OSEM) algorithm with/without time-of-flight (TOF/non-TOF) corrections. OSEM reconstruction postfiltering was 4.0 mm full-width at half-maximum; BSREM did not use postfiltering. Evaluation of general image quality was performed with a five-point scale using maximum intensity projections. Artifacts (category 1), image sharpness (category 2), noise (category 3), and lesion detectability (category 4) were analyzed using a four-point scale. Size and maximum standardized uptake value (SUVmax) of lesions were measured by a third reader not involved in the image evaluation. RESULTS: BSREM-TOF reconstructions showed the best results in all categories, independent of different body compartments. In all categories, BSREM non-TOF reconstructions were significantly better than OSEM non-TOF reconstructions (P<0.001). In almost all categories, BSREM non-TOF reconstruction was comparable to or better than the OSEM-TOF algorithm (P<0.001 for general image quality, image sharpness, noise, and P=1.0 for artifact). Only in lesion detectability was OSEM-TOF significantly better than BSREM non-TOF (P<0.001). Both BSREM-TOF and BSREM non-TOF showed a decreasing SUVmax with increasing ß values (P<0.001) and TOF reconstructions showed a significantly higher SUVmax than non-TOF reconstructions (P<0.001). CONCLUSION: The BSREM reconstruction algorithm showed a relevant improvement compared with OSEM reconstruction in PET/CT studies in all evaluated categories. BSREM might be used in clinical routine in conjunction with TOF to achieve better/higher image quality and lesion detectability or in PET/CT-systems without TOF-capability for enhancement of overall image quality as well.

TNM Staging of Non-Small Cell Lung Cancer: Comparison of PET/MR and PET/CT.

UNLABELLED: The purpose of this study was to compare the diagnostic accuracy of whole-body unenhanced PET/MR with that of PET/CT in determining the stage of non-small cell lung cancer. METHODS: This study was approved by the institutional review board and by national government authorities. Forty-two consecutive patients referred for the initial staging of non-small cell lung cancer underwent whole-body imaging with a sequential trimodality PET/CT/MR system. PET/MR and PET/CT datasets were evaluated separately, and a TNM stage was assigned on the basis of the image analysis. Nodal stations in the chest were identified according to the mapping system of the American Thoracic Society. The standard of reference was histopathology for the tumor stage in 20 subjects, for the nodal stage in 22 patients, and for extrathoracic metastases in 5 subjects. All other lesions were confirmed by at least 1 different imaging method. A Wilcoxon signed-ranks test was used for comparing PET/MR with PET/CT. RESULTS: PET/MR did not provide additional information compared with PET/CT. The diagnostic accuracy of both imaging modalities was equal (T staging, P = 0.177; N staging, P = 0.114; M staging, P = 0.465), however, with advantages for PET/CT by trend. In the subgroup with histopathologic confirmation of T and N stages, the situation was similar (T staging, P = 0.705; N staging, P = 0.334). CONCLUSION: This study indicates that PET/MR using a fast MR protocol does not improve the diagnostic accuracy of the staging of non-small cell lung cancer.

18F-FDG-PET/MR increases diagnostic confidence in detection of bone metastases compared with 18F-FDG-PET/CT.

PURPOSE: The aim of this study was to compare detection, lesion conspicuity and reader confidence of F-fluorodeoxyglucose (F-FDG)-PET/MR and F-FDG-PET/computed tomography (CT) in patients with F-FDG avid bone metastases. MATERIALS AND METHODS: In this prospective study, a total of 30 PET/CT and PET/MRI data sets were performed in 24 patients. Each examination was evaluated for the presence of PET-positive bone lesions consistent with metastatic involvement. Conspicuity of PET-positive bone lesions was evaluated on the corresponding PET/CT and PET/MR images and compared using the Wilcoxon signed-ranks test. Reader confidence was determined to evaluate whether PET/CT or PET/MR was more useful for the assessment of the bone metastases and was compared using Student's t-test. RESULTS: Overall, in both examinations, PET/CT and PET/MRI detected 86 F-FDG-positive bone lesions. On all 30 PET/MRI examinations, at least one morphological correlate for F-FDG-positive bone lesions was found on the MR component (82 out of 86 lesions). PET/CT imaging allowed identification of corresponding structural changes on the CT component in 23 out of 30 studies (65 out of 86 lesions). In lesion-by-lesion analysis, the mean lesion conspicuity was significantly better on T1 fat MR imaging compared with CT imaging (P=0.005). In seven out of 30 studies, a significant increase in reader confidence of PET/MRI compared with PET/CT was found. CONCLUSION: PET/MRI offers higher reader confidence and improved conspicuity in bone metastases compared with PET/CT. However, the overall detection rate was not different. The highest possible clinical impact of PET/MRI appears to be in patients with limited, early bone metastatic disease.

Dose Optimization in TOF-PET/MR Compared to TOF-PET/CT.

PURPOSE: To evaluate the possible activity reduction in FDG-imaging in a Time-of-Flight (TOF) PET/MR, based on cross-evaluation of patient-based NECR (noise equivalent count rate) measurements in PET/CT, cross referencing with phantom-based NECR curves as well as initial evaluation of TOF-PET/MR with reduced activity. MATERIALS AND METHODS: A total of 75 consecutive patients were evaluated in this study. PET/CT imaging was performed on a PET/CT (time-of-flight (TOF) Discovery D 690 PET/CT). Initial PET/MR imaging was performed on a newly available simultaneous TOF-PET/MR (Signa PET/MR). An optimal NECR for diagnostic purposes was defined in clinical patients (NECRP) in PET/CT. Subsequent optimal activity concentration at the acquisition time ([A]0) and target NECR (NECRT) were obtained. These data were used to predict the theoretical FDG activity requirement of the new TOF-PET/MR system. Twenty-five initial patients were acquired with (retrospectively reconstructed) different imaging times equivalent for different activities on the simultaneous PET/MR for the evaluation of clinically realistic FDG-activities. RESULTS: The obtained values for NECRP, [A]0 and NECRT were 114.6 (± 14.2) kcps (Kilocounts per second), 4.0 (± 0.7) kBq/mL and 45 kcps, respectively. Evaluating the NECRT together with the phantom curve of the TOF-PET/MR device, the theoretical optimal activity concentration was found to be approximately 1.3 kBq/mL, which represents 35% of the activity concentration required by the TOF-PET/CT. Initial evaluation on patients in the simultaneous TOF-PET/MR shows clinically realistic activities of 1.8 kBq/mL, which represent 44% of the required activity. CONCLUSION: The new TOF-PET/MR device requires significantly less activity to generate PET-images with good-to-excellent image quality, due to improvements in detector geometry and detector technologies. The theoretically achievable dose reduction accounts for up to 65% but cannot be fully translated into clinical routine based on the coils within the FOV and MR-sequences applied at the same time. The clinically realistic reduction in activity is slightly more than 50%. Further studies in a larger number of patients are needed to confirm our findings.

Workflow in Simultaneous PET/MRI.

The advent of simultaneous PET/MRI brought a large amount of possibilities in research and clinical applications into hybrid imaging. Unlike in PET/CT protocols, the MR component provides an almost unlimited number of pulse sequences and possibilities of different protocols in PET/MRI. Nevertheless, there is an imperative to reduce excessive imaging protocols to realistic clinical practice imaging acquisition. The design of a concise and indication-adapted protocol that provides an efficient workflow in a clinical reality is necessary to transform PET/MRI to a cost-effective imaging modality in addition to PET/CT. The aim of the current article is to point out the main considerations regarding workflow, imaging protocols, and image analysis in simultaneous PET/MRI system in oncology and share our thoughts and experience in acquisition optimization compared with the current literature.

PET/MRI and PET/CT in advanced gynaecological tumours: initial experience and comparison.

PURPOSE: To compare the diagnostic accuracy of PET/MRI and PET/CT for staging and re-staging advanced gynaecological cancer patients as well as identify the potential benefits of each method in such a population. MATERIAL AND METHODS: Twenty-six patients with suspicious or proven advanced gynaecological cancer (12 ovarian, seven cervical, one vulvar and four endometrial tumours, one uterine metastasis, and one primary peritoneal cancer) underwent whole-body imaging with a sequential trimodality PET/CT/MR system. Images were analysed regarding primary tumour detection and delineation, loco-regional lymph node staging, and abdominal/extra-abdominal distant metastasis detection (last only by PET/CT). RESULTS: Eighteen (69.2 %) patients underwent PET/MRI for primary staging and eight patients (30.8 %) for re-staging their gynaecological malignancies. For primary tumour delineation, PET/MRI accuracy was statistically superior to PET/CT (p < 0.001). Among the different types of cancer, PET/MRI presented better tumour delineation mainly for cervical (6/7) and endometrial (2/3) cancers. PET/MRI for local evaluation as well as PET/CT for extra-abdominal metastases had therapeutic consequences in three and one patients, respectively. PET/CT detected 12 extra-abdominal distant metastases in 26 patients. CONCLUSION: PET/MRI is superior to PET/CT for primary tumour delineation. No differences were found in detection of regional lymph node involvement and abdominal metastases detection. KEY POINTS: • PET/MRI is superior to PET/CT for primary tumour delineation • PET/CT represents a reliable tool to detect extra-abdominal distant metastasis • PET/MRI might be the preferred imaging modality for staging cervical and endometrial tumours • Whole-body staging for detection and evaluation of extra-abdominal metastases is mandatory.

Intra-individual comparison of PET/CT with different body weight-adapted FDG dosage regimens.

BACKGROUND: 18F-2-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET)/ computed tomography (CT) imaging demands guidelines to safeguard sufficient image quality at low radiation exposure. Various FDG dose regimes have been investigated; however, body weight-adapted dose regimens and related image quality (IQ) have not yet been compared in the same patient. PURPOSE: To investigate the relationship between FDG dosage and image quality in PET/CT in the same patient and determine prerequisites for low dosage scanning. MATERIAL AND METHODS: This study included 61 patients undergoing a clinically indicated PET/CT imaging study and follow-up with a normal (NDS, 5 MBq/kg body weight [BW]) and low dosage scanning protocol (LDS, 4 MBq/kg BW), respectively, using a Discovery VCT64 scanner. Two blinded and independent readers randomly assessed IQ of PET using a 5-point Likert scale and signal-to-noise ratio (SNR) of the liver. RESULTS: Body mass index (BMI) was significantly lower at LDS (P = 0.021) and represented a significant predictor of SNR at both NDS (P < 0.001) and LDS (P = 0.005). NDS with a mean administered activity of 340 MBq resulted in significantly higher IQ (P < 0.001) and SNR as compared with LDS with a mean of 264 MBq (F-value = 23.5, P < 0.001, mixed model ANOVA adjusted for covariate BMI). Non-diagnostic IQ at LDS was associated with a BMI > 22 kg/m(2). CONCLUSION: FDG dosage significantly predicts IQ and SNR in PET/CT imaging as demonstrated in the same patient with optimal IQ achieved at 5 MBq/kg BM. PET/CT imaging at 4 MBq/kg BW may only be recommended in patients with a BMI ≤ 22 kg/m(2) to maintain diagnostic IQ.

Image registration accuracy of an in-house developed patient transport system for PET/CT+MR and SPECT+CT imaging.

OBJECTIVE: The aim of this study was to investigate the registration accuracy of a newly developed patient shuttle system that can integrate different scanners by patient transfer without repositioning for 'hardware'-based image fusion. We aimed to assess the registration accuracy of image fusion in two different settings: a trimodality PET/CT+MR system and a SPECT+CT system. MATERIALS AND METHODS: In this prospective study, 43 patients underwent either sequential PET/CT and MR (n=31) or sequential SPECT and diagnostic CT (D-CT) (n=12). A side-loading patient shuttle system was used for patient transport. For PET/CT+MR, hardware-only coregistration was performed and then validated with anatomical landmarks on CT and MR. SPECT+D-CT image fusion was performed with external cobalt-57 markers and manual fusion. Registration accuracy was analysed by anatomical landmarks on the attenuation correction CT and the D-CT. RESULTS: For the PET/CT+MR system, the mean offset between original CT and MR images in all 31 patients was 8.1±5.7 mm in the X-axis, 5±4 mm in the Y-axis and 4.9±5.6 mm in the Z-axis. The validation of the cobalt-57 marker-assisted SPECT+D-CT fusion yielded offsets of 0.7±1.7 mm in the X-axis, 2.1±1.7 mm in the Y-axis and 0.8±1.8 mm in the Z-axis. CONCLUSION: Sequential PET/CT+MR and SPECT+D-CT imaging using a dedicated patient shuttle system is feasible, resulting in mean offsets between data sets of 10.7 mm using the gantry laser system and 2.4 mm with fiducial markers.

First clinical results of (D)-18F-Fluoromethyltyrosine (BAY 86-9596) PET/CT in patients with non-small cell lung cancer and head and neck squamous cell carcinoma.

UNLABELLED: (D)-(18)F-fluoromethyltyrosine (d-(18)F-FMT), or BAY 86-9596, is a novel (18)F-labeled tyrosine derivative rapidly transported by the l-amino acid transporter (LAT-1), with a faster blood pool clearance than the corresponding l-isomer. The aim of this study was to demonstrate the feasibility of tumor detection in patients with non-small cell lung cancer (NSCLC) or head and neck squamous cell cancer (HNSCC) compared with inflammatory and physiologic tissues in direct comparison to (18)F-FDG. METHODS: 18 patients with biopsy-proven NSCLC (n = 10) or HNSCC (n = 8) were included in this Institutional Review Board-approved, prospective multicenter study. All patients underwent (18)F-FDG PET/CT scans within 21 d before d-(18)F-FMT PET/CT. For all patients, safety and outcome data were assessed. RESULTS: No adverse reactions were observed related to d-(18)F-FMT. Fifty-two lesions were (18)F-FDG-positive, and 42 of those were malignant (34 histologically proven and 8 with clinical reference). Thirty-two of the 42 malignant lesions were also d-(18)F-FMT-positive, and 10 lesions had no tracer uptake above the level of the blood pool. Overall there were 34 true-positive, 8 true-negative, 10 false-negative, and only 2 false-positive lesions for d-(18)F-FMT, whereas (18)F-FDG was true-positive in 42 lesions, with 10 false-positive and only 2 false-negative, resulting in a lesion-based detection rate for d-(18)F-FMT and (18)F-FDG of 77% and 95%, respectively, with an accuracy of 78% for both tracers. A high d-(18)F-FMT tumor-to-blood pool ratio had a negative correlation with overall survival (P = 0.050), whereas the (18)F-FDG tumor-to-blood pool ratio did not correlate with overall survival. CONCLUSION: d-(18)F-FMT imaging in patients with NSCLC and HNSCC is safe and feasible. The presented preliminary results suggest a lower sensitivity but higher specificity for d-(18)F-FMT over (18)F-FDG, since there is no d-(18)F-FMT uptake in inflammation. This increased specificity may be particularly beneficial in areas with endemic granulomatous disease and may improve clinical management. Further clinical investigations are needed to determine its clinical value and relevance for the prediction of survival prognosis.