Performing [18F]MFBG Long-Axial-Field-of-View PET/CT Without Sedation or General Anesthesia for Imaging of Children with Neuroblastoma.

Meta-[123I]iodobenzylguanidine ([123I]MIBG) scintigraphy with SPECT/CT is the standard of care for diagnosing and monitoring neuroblastoma. Replacing [123I]MIBG with the new PET tracer meta-[18F]fluorobenzylguanidine ([18F]MFBG) and further improving sensitivity and reducing noise in a new long-axial-field-of-view (LAFOV) PET/CT scanner enable increased image quality and a faster acquisition time, allowing examinations to be performed without sedation or general anesthesia (GA). Focusing on feasibility, we present our first experience with [18F]MFBG LAFOV PET/CT and compare it with [123I]MIBG scintigraphy plus SPECT/CT for imaging in neuroblastoma in children. Methods: A pilot of our prospective, single-center study recruited children with neuroblastoma who were referred for [123I]MIBG scintigraphy with SPECT/CT. Within 1 wk of [123I]MIBG scintigraphy and SPECT/low-dose CT, [18F]MFBG LAFOV PET/ultra-low-dose CT was performed 1 h after injection (1.5-3 MBq/kg) without sedation or GA, in contrast to the 24-h postinjection interval needed for scanning with [123I]MIBG, the 2- to 2.5-h acquisition time, and the GA often needed in children less than 6 y old. Based on the spirocyclic iodonium-ylide precursor, [18F]MFBG was produced in a fully automated good manufacturing practice-compliant procedure. We present the feasibility of the study. Results: In the first paired scans of the first 10 children included (5 at diagnosis, 2 during treatment, 2 during surveillance, and 1 at relapse), [18F]MFBG PET/CT scan showed a higher number of radiotracer-avid lesions in 80% of the cases and an equal number of lesions in 20% of the cases. The SIOPEN score was higher in 50% of the cases, and the Curie score was higher in 70% of the cases. In particular, intraspinal, retroperitoneal lymph node, and bone marrow involvement was diagnosed with much higher precision. None of the children (median age, 1.6 y; range, 0.1-7.9 y) had sedation or GA during the PET procedure, whereas 80% had GA during [123I]MIBG scintigraphy with SPECT/CT. A PET acquisition time of only 2 min without motion artifacts was the data requirement of the 10-min acquisition time for reconstruction to provide a clinically useful image. Conclusion: This pilot study demonstrates the feasibility of performing [18F]MFBG LAFOV PET/CT for imaging of neuroblastoma. Further, an increased number of radiotracer-avid lesions, an increased SIOPEN score, and an increased Curie score were seen on [18F]MFBG LAFOV PET/CT compared with [123I]MIBG scintigraphy with SPECT/CT, and GA and sedation was avoided in all patients. Thus, with a 1-d protocol, a significantly shorter scan time, a higher sensitivity, and the avoidance of GA and sedation, [18F]MFBG LAFOV PET/CT shows promise for future staging and response assessment and may also have a clinical impact on therapeutic decision-making for children with neuroblastoma.

Healthy tissue metabolism assessed by [18F]FDG PET/CT as a marker of prognosis and adverse events in advanced Hodgkin lymphoma patients.

The aim of the study was to assess healthy tissue metabolism (HTM) using 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) during chemotherapy in Hodgkin lymphoma (HL) and the association of HTM with baseline metabolic tumour volume (MTV), haematological parameters, adverse events (AEs), early response and progression-free survival (PFS). We retrospectively identified 200 patients with advanced HL from the RATHL trial with [18F]FDG-PET/CT before (PET0) and following 2 cycles of chemotherapy (PET2). [18F]FDG-uptake was measured in bone marrow (BM), spleen, liver and mediastinal blood pool (MBP). Deauville score (DS) 1-3 was used to classify responders and DS 4-5, non-responders. [18F]FDG-uptake decreased significantly in BM and spleen and increased in liver and MBP at PET2 (all p < 0.0001), but was not associated with MTV. Higher BM uptake at PET0 was associated with lower baseline haemoglobin and higher absolute neutrophil counts, platelets, and white blood cells. High BM, spleen, and liver uptake at PET0 was associated with neutropenia after cycles 1-2. BM uptake at PET0 was associated with treatment failure at PET2 and non-responders with higher BM uptake at PET2 had significantly inferior PFS (p = 0.023; hazard ratio = 2.31). Based on these results, we concluded that the change in HTM during chemotherapy was most likely a direct impact of chemotherapy rather than a change in MTV. BM uptake has prognostic value in HL.

Low incidence of malignancy in patients with suspected polymyalgia rheumatica or giant cell arteritis, examined with FDG-PET/CT.

Introduction: The need to systematically examine patients suspected of polymyalgia rheumatica (PMR) and giant cell arteritis (GCA) for malignancy is controversial. The aim of this study was to assess the frequency of malignancy in patients with suspected PMR and/or GCA who have been referred to a 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography with computed tomography (FDG-PET/CT) as part of the diagnostic investigation. Method: The records of all patients referred to FDG-PET/CT from Center for Rheumatology and Spine Diseases, Rigshospitalet, Glostrup with the suspicion of PMR and/or GCA during a two-year period, were retrospectively reviewed. Data was analyzed with descriptive statistics, and a standard incidence ratio was calculated based on background cancer incidences extracted from the NORDCAN database. Results: 220 patients were included in the study. Findings suspicious of malignancy were found in 19 of the examinations, and in seven cases (3.2%), malignancy was confirmed. In three out of the seven cases the patients were diagnosed with PMR concomitantly with malignancy. The estimated standardized incidence ratio (SIR) for cancer compared to the background incidence of cancer in Denmark was 1.58 (95% CI 0.63-2.97), i.e., not statistically significant. There were no statistically significant differences in characteristics of the patients that were diagnosed with malignancy compared with those that were not. Conclusion: The frequency of malignancy in this cohort of patients with suspected PMR/GCA who underwent PET/CT was low. Our results, though based on a small cohort, do not suggest that all patients with suspected PMR/GCA should systematically be examined with FDG-PET/CT for excluding malignancy.

Clinical Evaluation of Deep Learning for Tumor Delineation on 18F-FDG PET/CT of Head and Neck Cancer.

Artificial intelligence (AI) may decrease 18F-FDG PET/CT-based gross tumor volume (GTV) delineation variability and automate tumor-volume-derived image biomarker extraction. Hence, we aimed to identify and evaluate promising state-of-the-art deep learning methods for head and neck cancer (HNC) PET GTV delineation. Methods: We trained and evaluated deep learning methods using retrospectively included scans of HNC patients referred for radiotherapy between January 2014 and December 2019 (ISRCTN16907234). We used 3 test datasets: an internal set to compare methods, another internal set to compare AI-to-expert variability and expert interobserver variability (IOV), and an external set to compare internal and external AI-to-expert variability. Expert PET GTVs were used as the reference standard. Our benchmark IOV was measured using the PET GTV of 6 experts. The primary outcome was the Dice similarity coefficient (DSC). ANOVA was used to compare methods, a paired t test was used to compare AI-to-expert variability and expert IOV, an unpaired t test was used to compare internal and external AI-to-expert variability, and post hoc Bland-Altman analysis was used to evaluate biomarker agreement. Results: In total, 1,220 18F-FDG PET/CT scans of 1,190 patients (mean age ± SD, 63 ± 10 y; 858 men) were included, and 5 deep learning methods were trained using 5-fold cross-validation (n = 805). The nnU-Net method achieved the highest similarity (DSC, 0.80 [95% CI, 0.77-0.86]; n = 196). We found no evidence of a difference between expert IOV and AI-to-expert variability (DSC, 0.78 for AI vs. 0.82 for experts; mean difference of 0.04 [95% CI, -0.01 to 0.09]; P = 0.12; n = 64). We found no evidence of a difference between the internal and external AI-to-expert variability (DSC, 0.80 internally vs. 0.81 externally; mean difference of 0.004 [95% CI, -0.05 to 0.04]; P = 0.87; n = 125). PET GTV-derived biomarkers of AI were in good agreement with experts. Conclusion: Deep learning can be used to automate 18F-FDG PET/CT tumor-volume-derived imaging biomarkers, and the deep-learning-based volumes have the potential to assist clinical tumor volume delineation in radiation oncology.

Use of [18F]Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography after Curative Treatment of Non-Small-Cell Lung Cancer Patients: A Nationwide Cohort Study.

[¹8F]Fluorodeoxyglucose positron emission tomography/computed tomography ([¹8F]FDG PET/CT) is a valuable imaging tool in the post-treatment management of non-small-cell lung cancer (NSCLC). This study aimed to investigate the trends in utilization and factors associated with the use of [¹8F]FDG PET/CT after curative-intent treatment. Data from 13,758 NSCLC patients diagnosed between 2007 and 2020 identified in the Danish Lung Cancer Registry, who underwent curative-intent treatment, were analyzed using multivariable regression. The results showed a significant increase in the use of [¹8F]FDG PET/CT scans, from 10.4 per 100 patients per year in 2007 to 39.6 in 2013, followed by a period of stability. Higher utilization rates were observed in patients who received radiotherapy (22% increase compared to surgical resection) and in patients with stage II-III disease (14% and 20% increase compared to stage I, respectively). Additionally, utilization was increased when other diagnostic procedures were performed, such as MRI, ultrasound, endoscopy, and biopsy. These findings highlight an increasing reliance on [¹8F]FDG PET/CT in post-treatment NSCLC, especially after radiotherapy and in patients with locally advanced disease, where treatment-induced radiographic changes and an increased risk of recurrence present a significant diagnostic challenge.

Brain perfusion estimation by Tikhonov model-free deconvolution in a long axial field of view PET/CT scanner exploring five different PET tracers.

PURPOSE: New total-body PET scanners with a long axial field of view (LAFOV) allow for higher temporal resolution due to higher sensitivity, which facilitates perfusion estimation by model-free deconvolution. Fundamental tracer kinetic theory predicts that perfusion can be estimated for all tracers despite their different fates given sufficiently high temporal resolution of 1 s or better, bypassing the need for compartment modelling. The aim of this study was to investigate whether brain perfusion could be estimated using model-free Tikhonov generalized deconvolution for five different PET tracers, [15O]H2O, [11C]PIB, [18F]FE-PE2I, [18F]FDG and [18F]FET. To our knowledge, this is the first example of a general model-free approach to estimate cerebral blood flow (CBF) from PET data. METHODS: Twenty-five patients underwent dynamic LAFOV PET scanning (Siemens, Quadra). PET images were reconstructed with an isotropic voxel resolution of 1.65 mm3. Time framing was 40 × 1 s during bolus passage followed by increasing framing up to 60 min. AIF was obtained from the descending aorta. Both voxel- and region-based calculations of perfusion in the thalamus were performed using the Tikhonov method. The residue impulse response function was used to estimate the extraction fraction of tracer leakage across the blood-brain barrier. RESULTS: CBF ranged from 37 to 69 mL blood min-1 100 mL of tissue-1 in the thalamus. Voxelwise calculation of CBF resulted in CBF maps in the physiologically normal range. The extraction fractions of [15O]H2O, [18F]FE-PE2I, [11C]PIB, [18F]FDG and [18F]FET in the thalamus were 0.95, 0.78, 0.62, 0.19 and 0.03, respectively. CONCLUSION: The high temporal resolution and sensitivity associated with LAFOV PET scanners allow for noninvasive perfusion estimation of multiple tracers. The method provides an estimation of the residue impulse response function, from which the fate of the tracer can be studied, including the extraction fraction, influx constant, volume of distribution and transit time distribution, providing detailed physiological insight into normal and pathologic tissue.

Evaluation of manual and automated approaches for segmentation and extraction of quantitative indices from [18F]FDG PET-CT images.

Utilisation of whole organ volumes to extract anatomical and functional information from computed tomography (CT) and positron emission tomography (PET) images may provide key information for the treatment and follow-up of cancer patients. However, manual organ segmentation, is laborious and time-consuming. In this study, a CT-based deep learning method and a multi-atlas method were evaluated for segmenting the liver and spleen on CT images to extract quantitative tracer information from Fluorine-18 fluorodeoxyglucose ([18F]FDG) PET images of 50 patients with advanced Hodgkin lymphoma (HL). Manual segmentation was used as the reference method. The two automatic methods were also compared with a manually defined volume of interest (VOI) within the organ, a technique commonly performed in clinical settings. Both automatic methods provided accurate CT segmentations, with the deep learning method outperforming the multi-atlas with a DICE coefficient of 0.93 ± 0.03 (mean ± standard deviation) in liver and 0.87 ± 0.17 in spleen compared to 0.87 ± 0.05 (liver) and 0.78 ± 0.11 (spleen) for the multi-atlas. Similarly, a mean relative error of -3.2% for the liver and -3.4% for the spleen across patients was found for the mean standardized uptake value (SUVmean) using the deep learning regions while the corresponding errors for the multi-atlas method were -4.7% and -9.2%, respectively. For the maximum SUV (SUVmax), both methods resulted in higher than 20% overestimation due to the extension of organ boundaries to include neighbouring, high-uptake regions. The conservative VOI method which did not extend into neighbouring tissues, provided a more accurate SUVmaxestimate. In conclusion, the automatic, and particularly the deep learning method could be used to rapidly extract information of the SUVmeanwithin the liver and spleen. However, activity from neighbouring organs and lesions can lead to high biases in SUVmaxand current practices of manually defining a volume of interest in the organ should be considered instead.

Potential Clinical Impact of LAFOV PET/CT: A Systematic Evaluation of Image Quality and Lesion Detection.

We performed a systematic evaluation of the diagnostic performance of LAFOV PET/CT with increasing acquisition time. The first 100 oncologic adult patients referred for 3 MBq/kg 2-[18F]fluoro-2-deoxy-D-glucose PET/CT on the Siemens Biograph Vision Quadra were included. A standard imaging protocol of 10 min was used and scans were reconstructed at 30 s, 60 s, 90 s, 180 s, 300 s, and 600 s. Paired comparisons of quantitative image noise, qualitative image quality, lesion detection, and lesion classification were performed. Image noise (n = 50, 34 women) was acceptable according to the current standard of care (coefficient-of-varianceref < 0.15) after 90 s and improved significantly with increasing acquisition time (PB < 0.001). The same was seen in observer rankings (PB < 0.001). Lesion detection (n = 100, 74 women) improved significantly from 30 s to 90 s (PB < 0.001), 90 s to 180 s (PB = 0.001), and 90 s to 300 s (PB = 0.002), while lesion classification improved from 90 s to 180 s (PB < 0.001), 180 s to 300 s (PB = 0.021), and 90 s to 300 s (PB < 0.001). We observed improved image quality, lesion detection, and lesion classification with increasing acquisition time while maintaining a total scan time of less than 5 min, which demonstrates a potential clinical benefit. Based on these results we recommend a standard imaging acquisition protocol for LAFOV PET/CT of minimum 180 s to maximum 300 s after injection of 3 MBq/kg 2-[18F]fluoro-2-deoxy-D-glucose.

The value of a QALY towards the end of life and its determinants: Experimental evidence.

OBJECTIVES: Individual and societal willingness to pay (WTP) for end-of-life medical interventions continue to be subject to considerable uncertainty. This study aims at deriving both types of WTP estimates for an extension of survival time and an improvement of quality of life amounting to a QALY. METHODS: A discrete choice experiment (DCE) involving a hypothetical novel drug for the treatment of terminal cancer involving 1529 Swiss residents was performed in 2014. In its individual setting, respondents choose between the status quo and a hypothetical drug with varying characteristics and out-of-pocket payments, adopting the perspective of a terminal cancer patient. In the societal setting, participants are asked to choose between the status quo and a social health insurance contract with and without coverage of the novel drug and a varying insurance contribution. RESULTS: In the individual setting, respondents put a higher value on their quality of life than on their survival time whereas in the societal setting, they put a higher value on extra survival time. The combination of the two extensions results in a mean individual WTP per QALY of CHF 96,150 (1 CHF = 1 USD as of 2014). Mean societal WTP for a QALY even amounts to CHF 213,500 in favor of an adult patient, CHF 255,600 for a child, and CHF 153,600 for a person aged over 70 years, respectively. While estimated societal values consistently exceed their individual counterparts, they vary considerably with respondents' socioeconomic characteristics in both settings. CONCLUSIONS: This research finds that individual WTP for an extension of survival time to one year is dominated by WTP for health-related quality of life whereas for societal WTP, it is the other way round. Both individual and societal WTP values exhibit a great deal of heterogeneity, with the latter depending on the type of beneficiary.

Impact of Reduced Image Noise on Deauville Scores in Patients with Lymphoma Scanned on a Long-Axial Field-of-View PET/CT-Scanner.

BACKGROUND: Total body and long-axial field-of-view (LAFOV) PET/CT represent visionary innovations in imaging enabling either improved image quality, reduction in injected activity-dose or decreased acquisition time. An improved image quality may affect visual scoring systems, including the Deauville score (DS), which is used for clinical assessment of patients with lymphoma. The DS compares SUVmax in residual lymphomas with liver parenchyma, and here we investigate the impact of reduced image noise on the DS in patients with lymphomas scanned on a LAFOV PET/CT. METHODS: Sixty-eight patients with lymphoma underwent a whole-body scan on a Biograph Vision Quadra PET/CT-scanner, and images were evaluated visually with regard to DS for three different timeframes of 90, 300, and 600 s. SUVmax and SUVmean were calculated from liver and mediastinal blood pool, in addition to SUVmax from residual lymphomas and measures of noise. RESULTS: SUVmax in liver and in mediastinal blood pool decreased significantly with increasing acquisition time, whereas SUVmean remained stable. In residual tumor, SUVmax was stable during different acquisition times. As a result, the DS was subject to change in three patients. CONCLUSIONS: Attention should be drawn towards the eventual impact of improvements in image quality on visual scoring systems such as the DS.

Tumor volume definitions in head and neck squamous cell carcinoma - Comparing PET/MRI and histopathology.

BACKGROUND AND PURPOSE: In cancer treatment precise definition of the tumor volume is essential, but despite development in imaging modalities, this remains a challenge. Here, pathological tumor volumes from the surgical specimens were obtained and compared to tumor volumes defined from modern PET/MRI hybrid imaging. The purpose is to evaluate mismatch between the volumes defined from imaging and pathology was estimated and potential clinical impact. METHODS AND MATERIALS: Twenty-five patients with head and neck squamous cell carcinoma were scanned on an integrated PET/MRI system prior to surgery. Three gross tumor volumes (GTVs) from the primary tumor site were delineated defined from MRI (GTVMRI), PET (GTVPET) and one by utilizing both anatomical images and clinical information (GTVONCO). Twenty-five primary tumor specimens were extracted en bloc, scanned with PET/MRI and co-registered to the patient images. Each specimen was sectioned in blocks, sliced and stained with haematoxylin and eosin. All slices were digitalized and tumor delineated by a head and neck pathologist. The pathological tumor areas in all slices were interpolated yielding a pathological 3D tumor volume (GTVPATO). GTVPATOwas compared with the imaging GTV's and potential mismatch was estimated. RESULTS: Thirteen patients were included. The mean volume of GTVONCOwas larger than the GTV's defined from PET or MRI. The mean mismatch of the GTVPATOcompared to the GTVPET, GTVMRIand GTVONCOwas 31.9 %, 54.5 % and 27.9 % respectively, and the entire GTVPATO was only fully encompassed in GTVONCO in 1 of 13 patients. However, after the addition of a clinical 5 mm margin the GTVPATO was fully encompassed in GTVONCO in 11 out of 13 patients. CONCLUSIONS: Despite modern hybrid imaging modalities, a mismatch between imaging and pathological defined tumor volumes was observed in all patients.A 5 mm clinical margin was sufficient to ensure inclusion of the entire pathological volume in 11 out of 13 patients.

Innate immune function during antineoplastic treatment is associated with 12-months survival in non-small cell lung cancer.

Introduction: The immune system has proven to be a key player in the progression as well as containment of cancer with new treatment strategies based on immunotherapy targeting this interaction. Assessing immune function could reveal critical information about the immune response to therapeutic interventions, revealing predictive biomarkers for tailored care and precision medicine. Methods: We investigated immune function in 37 patients with inoperable non-small cell lung cancer (NSCLC) undergoing treatment with PD-L1 immune checkpoint inhibitor (ICI), chemotherapy (CT) or chemo-radiotherapy (CT/RT). Blood samples before (day 0) and during therapy (day 7, 21 and 80) were investigated by a standardized immunoassay, TruCulture®. Results: Outcomes revealed a developing innate immune response induced by both immunotherapy and chemotherapy. NSCLC-patients displayed evidence of chronic innate immune activation and exhaustion prior to treatment. This pattern was particularly pronounced during treatment in patients dying within 12-months follow-up. Compared to treatment with CT, ICI demonstrated a higher ex vivo-stimulated release of proinflammatory cytokines. Discussion: These preliminary findings may pave the way for tailored treatment and immune-monitoring.

Correction: Christensen et al. Impact of [18F]FDG-PET and [18F]FLT-PET-Parameters in Patients with Suspected Relapse of Irradiated Lung Cancer. Diagnostics 2021, 11, 279.

In the original publication [...].

New PET Tracers: Current Knowledge and Perspectives in Lung Cancer.

PET/CT with the tracer 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG) has improved diagnostic imaging in cancer and is routinely used for diagnosing, staging and treatment planning in lung cancer patients. However, pitfalls of [18F]FDG-PET/CT limit the use in specific settings. Additionally, lung cancer is still the leading cause of cancer associated death and has high risk of recurrence after curative treatment. These circumstances have led to the continuous search for more sensitive and specific PET tracers to optimize lung cancer diagnosis, staging, treatment planning and evaluation. The objective of this review is to present and discuss current knowledge and perspectives of new PET tracers for use in lung cancer. A literature search was performed on PubMed and clinicaltrials.gov, limited to the past decade, excluding case reports, preclinical studies and studies on established tracers such as [18F]FDG and DOTATE. The most relevant papers from the search were evaluated. Several tracers have been developed targeting specific tumor characteristics and hallmarks of cancer. A small number of tracers have been studied extensively and evaluated head-to-head with [18F]FDG-PET/CT, whereas others need further investigation and validation in larger clinical trials. At this moment, none of the tracers can replace [18F]FDG-PET/CT. However, they might serve as supplementary imaging methods to provide more knowledge about biological tumor characteristics and visualize intra- and inter-tumoral heterogeneity.

Multi-parametric PET/MRI for enhanced tumor characterization of patients with cervical cancer.

AIM: The concept of personalized medicine has brought increased awareness to the importance of inter- and intra-tumor heterogeneity for cancer treatment. The aim of this study was to explore simultaneous multi-parametric PET/MRI prior to chemoradiotherapy for cervical cancer for characterization of tumors and tumor heterogeneity. METHODS: Ten patients with histologically proven primary cervical cancer were examined with multi-parametric 68Ga-NODAGA-E[c(RGDyK)]2-PET/MRI for radiation treatment planning after diagnostic 18F-FDG-PET/CT. Standardized uptake values (SUV) of RGD and FDG, diffusion weighted MRI and the derived apparent diffusion coefficient (ADC), and pharmacokinetic maps obtained from dynamic contrast-enhanced MRI with the Tofts model (iAUC60, Ktrans, ve, and kep) were included in the analysis. The spatial relation between functional imaging parameters in tumors was examined by a correlation analysis and joint histograms at the voxel level. The ability of multi-parametric imaging to identify tumor tissue classes was explored using an unsupervised 3D Gaussian mixture model-based cluster analysis. RESULTS: Functional MRI and PET of cervical cancers appeared heterogeneous both between patients and spatially within the tumors, and the relations between parameters varied strongly within the patient cohort. The strongest spatial correlation was observed between FDG uptake and ADC (median r = - 0.7). There was moderate voxel-wise correlation between RGD and FDG uptake, and weak correlations between all other modalities. Distinct relations between the ADC and RGD uptake as well as the ADC and FDG uptake were apparent in joint histograms. A cluster analysis using the combination of ADC, FDG and RGD uptake suggested tissue classes which could potentially relate to tumor sub-volumes. CONCLUSION: A multi-parametric PET/MRI examination of patients with cervical cancer integrated with treatment planning and including estimation of angiogenesis and glucose metabolism as well as MRI diffusion and perfusion parameters is feasible. A combined analysis of functional imaging parameters indicates a potential of multi-parametric PET/MRI to contribute to a better characterization of tumor heterogeneity than the modalities alone. However, the study is based on small patient numbers and further studies are needed prior to the future design of individually adapted treatment approaches based on multi-parametric functional imaging.

Deep learning for Dixon MRI-based attenuation correction in PET/MRI of head and neck cancer patients.

BACKGROUND: Quantitative whole-body PET/MRI relies on accurate patient-specific MRI-based attenuation correction (AC) of PET, which is a non-trivial challenge, especially for the anatomically complex head and neck region. We used a deep learning model developed for dose planning in radiation oncology to derive MRI-based attenuation maps of head and neck cancer patients and evaluated its performance on PET AC. METHODS: Eleven head and neck cancer patients, referred for radiotherapy, underwent CT followed by PET/MRI with acquisition of Dixon MRI. Both scans were performed in radiotherapy position. PET AC was performed with three different patient-specific attenuation maps derived from: (1) Dixon MRI using a deep learning network (PETDeep). (2) Dixon MRI using the vendor-provided atlas-based method (PETAtlas). (3) CT, serving as reference (PETCT). We analyzed the effect of the MRI-based AC methods on PET quantification by assessing the average voxelwise error within the entire body, and the error as a function of distance to bone/air. The error in mean uptake within anatomical regions of interest and the tumor was also assessed. RESULTS: The average (± standard deviation) PET voxel error was 0.0 ± 11.4% for PETDeep and -1.3 ± 21.8% for PETAtlas. The error in mean PET uptake in bone/air was much lower for PETDeep (-4%/12%) than for PETAtlas (-15%/84%) and PETDeep also demonstrated a more rapidly decreasing error with distance to bone/air affecting only the immediate surroundings (less than 1 cm). The regions with the largest error in mean uptake were those containing bone (mandible) and air (larynx) for both methods, and the error in tumor mean uptake was -0.6 ± 2.0% for PETDeep and -3.5 ± 4.6% for PETAtlas. CONCLUSION: The deep learning network for deriving MRI-based attenuation maps of head and neck cancer patients demonstrated accurate AC and exceeded the performance of the vendor-provided atlas-based method both overall, on a lesion-level, and in vicinity of challenging regions such as bone and air.

Test-retest repeatability and interobserver variation of healthy tissue metabolism using 18F-FDG PET/CT of the thorax among lung cancer patients.

OBJECTIVES: The aim of this study was to assess the test-retest repeatability and interobserver variation in healthy tissue (HT) metabolism using 2-deoxy-2-[18F]fluoro-d-glucose (18F-FDG) PET/computed tomography (PET/CT) of the thorax in lung cancer patients. METHODS: A retrospective analysis was conducted in 22 patients with non-small cell lung cancer who had two PET/CT scans of the thorax performed 3 days apart with no interval treatment. The maximum, mean and peak standardized uptake values (SUVs) in different HTs were measured by a single observer for the test-retest analysis and two observers for interobserver variation. Bland-Altman plots were used to assess the repeatability and interobserver variation. Intrasubject variability was evaluated using within-subject coefficients of variation (wCV). RESULTS: The wCV of test-retest SUVmean measurements in mediastinal blood pool, bone marrow, skeletal muscles and lungs was less than 20%. The left ventricle (LV) showed higher wCV (>60%) in all SUV parameters with wide limits of repeatability. High interobserver agreement was found with wCV of less than 10% in SUVmean of all HT, but up to 22% was noted in the LV. CONCLUSION: HT metabolism is stable in a test-retest scenario and has high interobserver agreement. SUVmean was the most stable metric in organs with low FDG uptake and SUVpeak in HTs with moderate uptake. Test-retest measurements in LV were highly variable irrespective of the SUV parameters used for measurements.

Positron emission tomography-computed tomography (PET-CT) in suspected malignant pleural effusion. An updated systematic review and meta-analysis.

The role of PET and integrated PET-CT in the diagnostic workup of suspected malignant pleural effusions is unknown. Earlier systematic reviews (published 2014 and 2015) both included pleural pathology without effusion, and reached contradictory conclusions. Five studies have been published since the latest review. This systematic review and meta-analysis aims to summarise the evidence of PET and integrated PET-CT in predicting pleural malignancy in patients suspected of having malignant pleural effusions. A meta-analysis based on a systematic literature search in Cochrane Library, Medline, EMBASE and Clinicaltrials.gov was performed. Diagnostic studies evaluating the performance of PET or PET-CT in patients with suspected malignant pleural effusion, using pleural fluid cytology or histopathology as the reference test, and presenting sufficient data for constructing a 2x2 table were included. The quality of the studies was assessed by the Quality Assessment of Diagnostic Accuracy Studies-2 score. Subgroup analyses on image modality, interpretation method and known malignancy status pre index-test application were planned. Seven studies with low risk of bias were included. The pooled ability to separate benign from malignant effusions varied with image modality, interpretation method and known malignancy status pre index-test application. In studies using PET-CT, visual/qualitative image analysis was superior to semi-quantitative with positive (LR + ) and negative likelihood ratio (LR-) of 9.9 (4.5-15.3) respectively 0.1 (0.1-0.2). There was considerable heterogeneity among studies. In conclusion, visual/qualitative image analysis of integrated PET-CT seems to add relevant information in the work-up of suspected malignant pleural effusions with LR + and LR- close to rigorous pre-set cut-offs of > 10 and < 0.1. However, the quality of evidence was low due to inter-study heterogeneity, and inability to assess meta-bias. Clinical Trial Registration: The protocol was uploaded to the PROSPERO database (CRD42020213319) on the 13th of October 2020.

Robustness and Generalizability of Deep Learning Synthetic Computed Tomography for Positron Emission Tomography/Magnetic Resonance Imaging-Based Radiation Therapy Planning of Patients With Head and Neck Cancer.

PURPOSE: Radiotherapy planning based only on positron emission tomography/magnetic resonance imaging (PET/MRI) lacks computed tomography (CT) information required for dose calculations. In this study, a previously developed deep learning model for creating synthetic CT (sCT) from MRI in patients with head and neck cancer was evaluated in 2 scenarios: (1) using an independent external dataset, and (2) using a local dataset after an update of the model related to scanner software-induced changes to the input MRI. METHODS AND MATERIALS: Six patients from an external site and 17 patients from a local cohort were analyzed separately. Each patient underwent a CT and a PET/MRI with a Dixon MRI sequence over either one (external) or 2 (local) bed positions. For the external cohort, a previously developed deep learning model for deriving sCT from Dixon MRI was directly applied. For the local cohort, we adapted the model for an upgraded MRI acquisition using transfer learning and evaluated it in a leave-one-out process. The sCT mean absolute error for each patient was assessed. Radiotherapy dose plans based on sCT and CT were compared by assessing relevant absorbed dose differences in target volumes and organs at risk. RESULTS: The MAEs were 78 ± 13 HU and 76 ± 12 HU for the external and local cohort, respectively. For the external cohort, absorbed dose differences in target volumes were within ± 2.3% and within ± 1% in 95% of the cases. Differences in organs at risk were <2%. Similar results were obtained for the local cohort. CONCLUSIONS: We have demonstrated a robust performance of a deep learning model for deriving sCT from MRI when applied to an independent external dataset. We updated the model to accommodate a larger axial field of view and software-induced changes to the input MRI. In both scenarios dose calculations based on sCT were similar to those of CT suggesting a robust and reliable method.