Toward PET/MRI as one-stop shop for radiotherapy planning in cervical cancer patients.

BACKGROUND: Radiotherapy (RT) planning for cervical cancer patients entails the acquisition of both Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Further, molecular imaging by Positron Emission Tomography (PET) could contribute to target volume delineation as well as treatment response monitoring. The objective of this study was to investigate the feasibility of a PET/MRI-only RT planning workflow of patients with cervical cancer. This includes attenuation correction (AC) of MRI hardware and dedicated positioning equipment as well as evaluating MRI-derived synthetic CT (sCT) of the pelvic region for positioning verification and dose calculation to enable a PET/MRI-only setup. MATERIAL AND METHODS: 16 patients underwent PET/MRI using a dedicated RT setup after the routine CT (or PET/CT), including eight pilot patients and eight cervical cancer patients who were subsequently referred for RT. Data from 18 patients with gynecological cancer were added for training a deep convolutional neural network to generate sCT from Dixon MRI. The mean absolute difference between the dose distributions calculated on sCT and a reference CT was measured in the RT target volume and organs at risk. PET AC by sCT and a reference CT were compared in the tumor volume. RESULTS: All patients completed the examination. sCT was inferred for each patient in less than 5 s. The dosimetric analysis of the sCT-based dose planning showed a mean absolute error (MAE) of 0.17 ± 0.12 Gy inside the planning target volumes (PTV). PET images reconstructed with sCT and CT had no significant difference in quantification for all patients. CONCLUSIONS: These results suggest that multiparametric PET/MRI can be successfully integrated as a one-stop-shop in the RT workflow of patients with cervical cancer.

Immunohistochemical biomarkers and FDG uptake on PET/CT in head and neck squamous cell carcinoma.

BACKGROUND: There is an exciting complementarity between the spatial resolution provided by molecular imaging of a single, often unspecific, biomarker on one hand and the more detailed biological profile achievable from a diagnostic biopsy using a panel of immunohistochemical (IHC) markers on the other. A number of previous studies have shown a relationship between glucose transport protein expression and 18F-Fludeoxyglucose (FDG) PET uptake. Here, FDG uptake is analyzed in relation to expression of a selected panel of IHC cancer biomarkers in head and neck squamous cell carcinomas (HNSCC). MATERIAL AND METHODS: IHC staining for Bcl-2, ß-tubulin-1 and 2, p53, EGFR, Ki-67, glutathione-S-transferase-π and p16 was performed on formalin-fixed paraffin embedded diagnostic biopsies from 102 HNSCC cases treated at Rigshospitalet during 2005-2009. The proportion of positive cells was used for analyses, except p16, which was scored according to EORTC guidelines. In all cases, maximal FDG standardized uptake value (SUV) metrics were extracted for the primary tumor, TSUVmax. Univariate linear regression and multiple linear regression of TSUVmax versus IHC markers were performed. RESULTS: In univariate analyses, TSUVmax showed negative associations with Bcl-2 (p = 0.002) and p16 (p = 0.005) indices and positive association with ß-tubulin-1 index (p = 0.003). On multivariate analysis, TSUVmax remained associated with ß-tubulin-1 (p = 0.009), Bcl-2 (p = 0.03) and p16 (p = 0.03). All correlations had r-squared < 0.3. CONCLUSION: Statistically significant correlations were observed between the expression of IHC biomarkers and maximum FDG uptake in the primary tumor.

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.

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.

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.

Improved Positron Emission Tomography Quantification: Evaluation of a Maximum-Likelihood Scatter Scaling Algorithm.

Incorrect scatter scaling of positron emission tomography (PET) images can lead to halo artifacts, quantitative bias, or reconstruction failure. Tail-fitted scatter scaling (TFSS) possesses performance limitations in multiple cases. This study aims to investigate a novel method for scatter scaling: maximum-likelihood scatter scaling (MLSS) in scenarios where TFSS tends to induce artifacts or are observed to cause reconstruction abortion. [68Ga]Ga-RGD PET scans of nine patients were included in cohort 1 in the scope of investigating the reduction of halo artifacts relative to the scatter estimation method. PET scans of 30 patients administrated with [68Ga]Ga-uPAR were included in cohort 2, used for an evaluation of the robustness of MLSS in cases where TFSS-integrated reconstructions are observed to fail. A visual inspection of MLSS-corrected images scored higher than TFSS-corrected reconstructions of cohort 1. The quantitative investigation near the bladder showed a relative difference in tracer uptake of up to 94.7%. A reconstruction of scans included in cohort 2 resulted in failure in 23 cases when TFSS was used. The lesion uptake values of cohort 2 showed no significant difference. MLSS is suggested as an alternative scatter-scaling method relative to TFSS with the aim of reducing halo artifacts and a robust reconstruction process.

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.

The optimality of different strategies for supplemental staging of non-small-cell lung cancer: a health economic decision analysis.

OBJECTIVES: To assess the expected costs and outcomes of alternative strategies for staging of lung cancer to inform a Danish National Health Service perspective about the most cost-effective strategy. METHODS: A decision tree was specified for patients with a confirmed diagnosis of non-small-cell lung cancer. Six strategies were defined from relevant combinations of mediastinoscopy, endoscopic or endobronchial ultrasound with needle aspiration, and combined positron emission tomography-computed tomography with F18-fluorodeoxyglucose. Patients without distant metastases and central or contralateral nodal involvement (N2/N3) were considered to be candidates for surgical resection. Diagnostic accuracies were informed from literature reviews, prevalence and survival from the Danish Lung Cancer Registry, and procedure costs from national average tariffs. All parameters were specified probabilistically to determine the joint decision uncertainty. The cost-effectiveness analysis was based on the net present value of expected costs and life years accrued over a time horizon of 5 years. RESULTS: At threshold values of around €30,000 for cost-effectiveness, it was found to be cost-effective to send all patients to positron emission tomography-computed tomography with confirmation of positive findings on nodal involvement by endobronchial ultrasound. This result appeared robust in deterministic sensitivity analysis. The expected value of perfect information was estimated at €52 per patient, indicating that further research might be worthwhile. CONCLUSIONS: The policy recommendation is to make combined positron emission tomography-computed tomography and endobronchial ultrasound available for supplemental staging of patients with non-small-cell lung cancer. The effects of alternative strategies on patients' quality of life, however, should be examined in future studies.

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.

Attenuation Correction of Long Axial Field-of-View Positron Emission Tomography Using Synthetic Computed Tomography Derived from the Emission Data: Application to Low-Count Studies and Multiple Tracers.

Recent advancements in PET/CT, including the emergence of long axial field-of-view (LAFOV) PET/CT scanners, have increased PET sensitivity substantially. Consequently, there has been a significant reduction in the required tracer activity, shifting the primary source of patient radiation dose exposure to the attenuation correction (AC) CT scan during PET imaging. This study proposes a parameter-transferred conditional generative adversarial network (PT-cGAN) architecture to generate synthetic CT (sCT) images from non-attenuation corrected (NAC) PET images, with separate networks for [18F]FDG and [15O]H2O tracers. The study includes a total of 1018 subjects (n = 972 [18F]FDG, n = 46 [15O]H2O). Testing was performed on the LAFOV scanner for both datasets. Qualitative analysis found no differences in image quality in 30 out of 36 cases in FDG patients, with minor insignificant differences in the remaining 6 cases. Reduced artifacts due to motion between NAC PET and CT were found. For the selected organs, a mean average error of 0.45% was found for the FDG cohort, and that of 3.12% was found for the H2O cohort. Simulated low-count images were included in testing, which demonstrated good performance down to 45 s scans. These findings show that the AC of total-body PET is feasible across tracers and in low-count studies and might reduce the artifacts due to motion and metal implants.

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.

A Literature Review on the Use of Artificial Intelligence for the Diagnosis of COVID-19 on CT and Chest X-ray.

A COVID-19 diagnosis is primarily determined by RT-PCR or rapid lateral-flow testing, although chest imaging has been shown to detect manifestations of the virus. This article reviews the role of imaging (CT and X-ray), in the diagnosis of COVID-19, focusing on the published studies that have applied artificial intelligence with the purpose of detecting COVID-19 or reaching a differential diagnosis between various respiratory infections. In this study, ArXiv, MedRxiv, PubMed, and Google Scholar were searched for studies using the criteria terms 'deep learning', 'artificial intelligence', 'medical imaging', 'COVID-19' and 'SARS-CoV-2'. The identified studies were assessed using a modified version of the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD). Twenty studies fulfilled the inclusion criteria for this review. Out of those selected, 11 papers evaluated the use of artificial intelligence (AI) for chest X-ray and 12 for CT. The size of datasets ranged from 239 to 19,250 images, with sensitivities, specificities and AUCs ranging from 0.789-1.00, 0.843-1.00 and 0.850-1.00. While AI demonstrates excellent diagnostic potential, broader application of this method is hindered by the lack of relevant comparators in studies, sufficiently sized datasets, and independent testing.

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 [...].

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.

A deep learning-based whole-body solution for PET/MRI attenuation correction.

BACKGROUND: Deep convolutional neural networks have demonstrated robust and reliable PET attenuation correction (AC) as an alternative to conventional AC methods in integrated PET/MRI systems. However, its whole-body implementation is still challenging due to anatomical variations and the limited MRI field of view. The aim of this study is to investigate a deep learning (DL) method to generate voxel-based synthetic CT (sCT) from Dixon MRI and use it as a whole-body solution for PET AC in a PET/MRI system. MATERIALS AND METHODS: Fifteen patients underwent PET/CT followed by PET/MRI with whole-body coverage from skull to feet. We performed MRI truncation correction and employed co-registered MRI and CT images for training and leave-one-out cross-validation. The network was pretrained with region-specific images. The accuracy of the AC maps and reconstructed PET images were assessed by performing a voxel-wise analysis and calculating the quantification error in SUV obtained using DL-based sCT (PETsCT) and a vendor-provided atlas-based method (PETAtlas), with the CT-based reconstruction (PETCT) serving as the reference. In addition, region-specific analysis was performed to compare the performances of the methods in brain, lung, liver, spine, pelvic bone, and aorta. RESULTS: Our DL-based method resulted in better estimates of AC maps with a mean absolute error of 62 HU, compared to 109 HU for the atlas-based method. We found an excellent voxel-by-voxel correlation between PETCT and PETsCT (R2 = 0.98). The absolute percentage difference in PET quantification for the entire image was 6.1% for PETsCT and 11.2% for PETAtlas. The regional analysis showed that the average errors and the variability for PETsCT were lower than PETAtlas in all regions. The largest errors were observed in the lung, while the smallest biases were observed in the brain and liver. CONCLUSIONS: Experimental results demonstrated that a DL approach for whole-body PET AC in PET/MRI is feasible and allows for more accurate results compared with conventional methods. Further evaluation using a larger training cohort is required for more accurate and robust performance.

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.

Preoperative staging of lung cancer with PET/CT: cost-effectiveness evaluation alongside a randomized controlled trial.

PURPOSE: Positron emission tomography (PET)/CT has become a widely used technology for preoperative staging of non-small cell lung cancer (NSCLC). Two recent randomized controlled trials (RCT) have established its efficacy over conventional staging, but no studies have assessed its cost-effectiveness. The objective of this study was to assess the cost-effectiveness of PET/CT as an adjunct to conventional workup for preoperative staging of NSCLC. METHODS: The study was conducted alongside an RCT in which 189 patients were allocated to conventional staging (n = 91) or conventional staging + PET/CT (n = 98) and followed for 1 year after which the numbers of futile thoracotomies in each group were monitored. A full health care sector perspective was adapted for costing resource use. The outcome parameter was defined as the number needed to treat (NNT)-here number of PET/CT scans needed-to avoid one futile thoracotomy. All monetary estimates were inflated to 2010 . RESULTS: The incremental cost of the PET/CT-based regimen was estimated at 3,927 [95% confidence interval (CI) -3,331; 10,586] and the NNT at 4.92 (95% CI 3.00; 13.62). These resulted in an average incremental cost-effectiveness ratio of 19,314 , which would be cost-effective at a probability of 0.90 given a willingness to pay of 50,000 per avoided futile thoracotomy. When costs of comorbidity-related hospital services were excluded, the PET/CT regimen appeared dominant. CONCLUSION: Applying a full health care sector perspective, the cost-effectiveness of PET/CT for staging NSCLC seems to depend on the willingness to pay in order to avoid a futile thoracotomy. However, given that four outliers in terms of extreme comorbidity were all randomized to the PET/CT arm, there is uncertainty about the conclusion. When hospital costs of comorbidity were excluded, the PET/CT regimen was found to be both more accurate and cost saving.

Artificial Intelligence for the Characterization of Pulmonary Nodules, Lung Tumors and Mediastinal Nodes on PET/CT.

Lung cancer is the leading cause of cancer related death around the world although early diagnosis remains vital to enabling access to curative treatment options. This article briefly describes the current role of imaging, in particular 2-deoxy-2-[18F]fluoro-D-glucose (FDG) PET/CT, in lung cancer and specifically the role of artificial intelligence with CT followed by a detailed review of the published studies applying artificial intelligence (ie, machine learning and deep learning), on FDG PET or combined PET/CT images with the purpose of early detection and diagnosis of pulmonary nodules, and characterization of lung tumors and mediastinal lymph nodes. A comprehensive search was performed on Pubmed, Embase, and clinical trial databases. The studies were analyzed with a modified version of the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) and Prediction model Risk Of Bias Assessment Tool (PROBAST) statement. The search resulted in 361 studies; of these 29 were included; all retrospective; none were clinical trials. Twenty-two records evaluated standard machine learning (ML) methods on imaging features (ie, support vector machine), and 7 studies evaluated new ML methods (ie, deep learning) applied directly on PET or PET/CT images. The studies mainly reported positive results regarding the use of ML methods for diagnosing pulmonary nodules, characterizing lung tumors and mediastinal lymph nodes. However, 22 of the 29 studies were lacking a relevant comparator and/or lacking independent testing of the model. Application of ML methods with feature and image input from PET/CT for diagnosing and characterizing lung cancer is a relatively young area of research with great promise. Nevertheless, current published studies are often under-powered and lacking a clinically relevant comparator and/or independent testing.