Adjuvant holmium-166 radioembolization after radiofrequency ablation in early-stage hepatocellular carcinoma patients: a dose-finding study (HORA EST HCC trial).

PURPOSE: The aim of this study was to investigate the biodistribution of (super-)selective trans-arterial radioembolization (TARE) with holmium-166 microspheres (166Ho-MS), when administered as adjuvant therapy after RFA of HCC 2-5 cm. The objective was to establish a treatment volume absorbed dose that results in an absorbed dose of ≥ 120 Gy on the hyperemic zone around the ablation necrosis (i.e., target volume). METHODS: In this multicenter, prospective dose-escalation study in BCLC early stage HCC patients with lesions 2-5 cm, RFA was followed by (super-)selective infusion of 166Ho-MS on day 5-10 after RFA. Dose distribution within the treatment volume was based on SPECT-CT. Cohorts of up to 10 patients were treated with an incremental dose (60 Gy, 90 Gy, 120 Gy) of 166Ho-MS to the treatment volume. The primary endpoint was to obtain a target volume dose of ≥ 120 Gy in 9/10 patients within a cohort. RESULTS: Twelve patients were treated (male 10; median age, 66.5 years (IQR, [64.3-71.7])) with a median tumor diameter of 2.7 cm (IQR, [2.1-4.0]). At a treatment volume absorbed dose of 90 Gy, the primary endpoint was met with a median absorbed target volume dose of 138 Gy (IQR, [127-145]). No local recurrences were found within 1-year follow-up. CONCLUSION: Adjuvant (super-)selective infusion of 166Ho-MS after RFA for the treatment of HCC can be administered safely at a dose of 90 Gy to the treatment volume while reaching a dose of ≥ 120 Gy to the target volume and may be a favorable adjuvant therapy for HCC lesions 2-5 cm. TRIAL REGISTRATION: Clinicaltrials.gov NCT03437382 . (registered: 19-02-2018).

Quantitative classification and radiomics of [18F]FDG-PET/CT in indeterminate thyroid nodules.

PURPOSE: To evaluate whether quantitative [18F]FDG-PET/CT assessment, including radiomic analysis of [18F]FDG-positive thyroid nodules, improved the preoperative differentiation of indeterminate thyroid nodules of non-Hürthle cell and Hürthle cell cytology. METHODS: Prospectively included patients with a Bethesda III or IV thyroid nodule underwent [18F]FDG-PET/CT imaging. Receiver operating characteristic (ROC) curve analysis was performed for standardised uptake values (SUV) and SUV-ratios, including assessment of SUV cut-offs at which a malignant/borderline neoplasm was reliably ruled out (≥ 95% sensitivity). [18F]FDG-positive scans were included in radiomic analysis. After segmentation at 50% of SUVpeak, 107 radiomic features were extracted from [18F]FDG-PET and low-dose CT images. Elastic net regression classifiers were trained in a 20-times repeated random split. Dimensionality reduction was incorporated into the splits. Predictive performance of radiomics was presented as mean area under the ROC curve (AUC) across the test sets. RESULTS: Of 123 included patients, 84 (68%) index nodules were visually [18F]FDG-positive. The malignant/borderline rate was 27% (33/123). SUV-metrices showed AUCs ranging from 0.705 (95% CI, 0.601-0.810) to 0.729 (0.633-0.824), 0.708 (0.580-0.835) to 0.757 (0.650-0.864), and 0.533 (0.320-0.747) to 0.700 (0.502-0.898) in all (n = 123), non-Hürthle (n = 94), and Hürthle cell (n = 29) nodules, respectively. At SUVmax, SUVpeak, SUVmax-ratio, and SUVpeak-ratio cut-offs of 2.1 g/mL, 1.6 g/mL, 1.2, and 0.9, respectively, sensitivity of [18F]FDG-PET/CT was 95.8% (95% CI, 78.9-99.9%) in non-Hürthle cell nodules. In Hürthle cell nodules, cut-offs of 5.2 g/mL, 4.7 g/mL, 3.4, and 2.8, respectively, resulted in 100% sensitivity (95% CI, 66.4-100%). Radiomic analysis of 84 (68%) [18F]FDG-positive nodules showed a mean test set AUC of 0.445 (95% CI, 0.290-0.600) for the PET model. CONCLUSION: Quantitative [18F]FDG-PET/CT assessment ruled out malignancy in indeterminate thyroid nodules. Distinctive, higher SUV cut-offs should be applied in Hürthle cell nodules to optimize rule-out ability. Radiomic analysis did not contribute to the additional differentiation of [18F]FDG-positive nodules. TRIAL REGISTRATION NUMBER: This trial is registered with ClinicalTrials.gov: NCT02208544 (5 August 2014), https://clinicaltrials.gov/ct2/show/NCT02208544 .

[18F]FDG-PET/CT radiomics for the identification of genetic clusters in pheochromocytomas and paragangliomas.

OBJECTIVES: Based on germline and somatic mutation profiles, pheochromocytomas and paragangliomas (PPGLs) can be classified into different clusters. We investigated the use of [18F]FDG-PET/CT radiomics, SUVmax and biochemical profile for the identification of the genetic clusters of PPGLs. METHODS: In this single-centre cohort, 40 PPGLs (13 cluster 1, 18 cluster 2, 9 sporadic) were delineated using a 41% adaptive threshold of SUVpeak ([18F]FDG-PET) and manually (low-dose CT; ldCT). Using PyRadiomics, 211 radiomic features were extracted. Stratified 5-fold cross-validation for the identification of the genetic cluster was performed using multinomial logistic regression with dimensionality reduction incorporated per fold. Classification performances of biochemistry, SUVmax and PET(/CT) radiomic models were compared and presented as mean (multiclass) test AUCs over the five folds. Results were validated using a sham experiment, randomly shuffling the outcome labels. RESULTS: The model with biochemistry only could identify the genetic cluster (multiclass AUC 0.60). The three-factor PET model had the best classification performance (multiclass AUC 0.88). A simplified model with only SUVmax performed almost similarly. Addition of ldCT features and biochemistry decreased the classification performances. All sham AUCs were approximately 0.50. CONCLUSION: PET radiomics achieves a better identification of PPGLs compared to biochemistry, SUVmax, ldCT radiomics and combined approaches, especially for the differentiation of sporadic PPGLs. Nevertheless, a model with SUVmax alone might be preferred clinically, weighing model performances against laborious radiomic analysis. The limited added value of radiomics to the overall classification performance for PPGL should be validated in a larger external cohort. KEY POINTS: • Radiomics derived from [18F]FDG-PET/CT has the potential to improve the identification of the genetic clusters of pheochromocytomas and paragangliomas. • A simplified model with SUVmax only might be preferred clinically, weighing model performances against the laborious radiomic analysis. • Cluster 1 and 2 PPGLs generally present distinctive characteristics that can be captured using [18F]FDG-PET imaging. Sporadic PPGLs appear more heterogeneous, frequently resembling cluster 2 PPGLs and occasionally resembling cluster 1 PPGLs.

Outcome prediction of head and neck squamous cell carcinoma by MRI radiomic signatures.

OBJECTIVES: Head and neck squamous cell carcinoma (HNSCC) shows a remarkable heterogeneity between tumors, which may be captured by a variety of quantitative features extracted from diagnostic images, termed radiomics. The aim of this study was to develop and validate MRI-based radiomic prognostic models in oral and oropharyngeal cancer. MATERIALS AND METHODS: Native T1-weighted images of four independent, retrospective (2005-2013), patient cohorts (n = 102, n = 76, n = 89, and n = 56) were used to delineate primary tumors, and to extract 545 quantitative features from. Subsequently, redundancy filtering and factor analysis were performed to handle collinearity in the data. Next, radiomic prognostic models were trained and validated to predict overall survival (OS) and relapse-free survival (RFS). Radiomic features were compared to and combined with prognostic models based on standard clinical parameters. Performance was assessed by integrated area under the curve (iAUC). RESULTS: In oral cancer, the radiomic model showed an iAUC of 0.69 (OS) and 0.70 (RFS) in the validation cohort, whereas the iAUC in the oropharyngeal cancer validation cohort was 0.71 (OS) and 0.74 (RFS). By integration of radiomic and clinical variables, the most accurate models were defined (iAUC oral cavity, 0.72 (OS) and 0.74 (RFS); iAUC oropharynx, 0.81 (OS) and 0.78 (RFS)), and these combined models outperformed prognostic models based on standard clinical variables only (p < 0.001). CONCLUSIONS: MRI radiomics is feasible in HNSCC despite the known variability in MRI vendors and acquisition protocols, and radiomic features added information to prognostic models based on clinical parameters. KEY POINTS: • MRI radiomics can predict overall survival and relapse-free survival in oral and HPV-negative oropharyngeal cancer. • MRI radiomics provides additional prognostic information to known clinical variables, with the best performance of the combined models. • Variation in MRI vendors and acquisition protocols did not influence performance of radiomic prognostic models.

Managing radioiodine refractory thyroid cancer: the role of dosimetry and redifferentiation on subsequent I-131 therapy.

Poor responses to iodine-131 (I-131) therapy can relate to either low iodine uptake and retention in thyroid cancer cells or to increased radioresistance. Both mechanisms are currently termed radioactive iodine (RAI)-refractory (RAI-R) thyroid cancer but the first reflects unsuitability for I-131 therapy that can be evaluated in advance of treatment, whereas the other can only be identified post hoc. Management of both represents a considerable challenge in clinical practice as failure of I-131 therapy, the most effective treatment of metastatic thyroid cancer, is associated with a poor overall prognosis. The development of targeted therapies has shown substantial promise in the treatment of RAI-R thyroid cancer in progressive patients. Recent studies show that selective tyrosine kinase inhibitors (TKIs) targeting B-type rapidly accelerated fibrosarcoma kinase (BRAF) and mitogen-activated protein kinase (MEK) can be used as redifferentiation agents to re-induce RAI uptake, thereby (re)enabling I-131 therapy. The use of dosimetry prior- and post-TKI treatment can assist in quantifying RAI uptake and improve identification of patients that will benefit from I-131 therapy. It also potentially offers the prospect of calculating individualized therapeutic administered activities to enhance efficacy and limit toxicity. In this review, we present an overview of the regulation of RAI uptake and clinically investigated redifferentiation agents, both reimbursed and in experimental setting, that induce renewed RAI uptake. We describe the role of dosimetry in redifferentiation and subsequent I-131 therapy in RAI-R thyroid cancer, explain different dosimetry approaches and discuss limitations and considerations in the field.

Nuclear medicine radiomics in precision medicine: why we can't do without artificial intelligence.

In recent years, radiomics, defined as the extraction of large amounts of quantitative features from medical images, has gained emerging interest. Radiomics consists of the extraction of handcrafted features combined with sophisticated statistical methods or machine learning algorithms for modelling, or deep learning algorithms that both learn features from raw data and perform modelling. These features have the potential to serve as non-invasive biomarkers for tumor characterization, prognostic stratification and response prediction, thereby contributing to precision medicine. However, especially in nuclear medicine, variable results are obtained when using radiomics for these purposes. Individual studies show promising results, but due to small numbers of patients per study and little standardization, it is difficult to compare and validate results on other datasets. This review describes the radiomic pipeline, its applications and the increasing role of artificial intelligence within the field. Furthermore, the challenges that need to be overcome to achieve clinical translation are discussed, so that, eventually, radiomics, combined with clinical data and other biomarkers, can contribute to precision medicine, by providing the right treatment to the right patient, with the right dose, at the right time.

Effect of sitagliptin on energy metabolism and brown adipose tissue in overweight individuals with prediabetes: a randomised placebo-controlled trial.

AIMS/HYPOTHESIS: The aim of this study was to evaluate the effect of sitagliptin on glucose tolerance, plasma lipids, energy expenditure and metabolism of brown adipose tissue (BAT), white adipose tissue (WAT) and skeletal muscle in overweight individuals with prediabetes (impaired glucose tolerance and/or impaired fasting glucose). METHODS: We performed a randomised, double-blinded, placebo-controlled trial in 30 overweight, Europid men (age 45.9 ± 6.2 years; BMI 28.8 ± 2.3 kg/m2) with prediabetes in the Leiden University Medical Center and the Alrijne Hospital between March 2015 and September 2016. Participants were initially randomly allocated to receive sitagliptin (100 mg/day) (n = 15) or placebo (n = 15) for 12 weeks, using a randomisation list that was set up by an unblinded pharmacist. All people involved in the study as well as participants were blinded to group assignment. Two participants withdrew from the study prior to completion (both in the sitagliptin group) and were subsequently replaced with two new participants that were allocated to the same treatment. Before and after treatment, fasting venous blood samples and skeletal muscle biopsies were obtained, OGTT was performed and body composition, resting energy expenditure and [18F] fluorodeoxyglucose ([18F]FDG) uptake by metabolic tissues were assessed. The primary study endpoint was the effect of sitagliptin on BAT volume and activity. RESULTS: One participant from the sitagliptin group was excluded from analysis, due to a distribution error, leaving 29 participants for further analysis. Sitagliptin, but not placebo, lowered glucose excursion (-40%; p < 0.003) during OGTT, accompanied by an improved insulinogenic index (+38%; p < 0.003) and oral disposition index (+44%; p < 0.003). In addition, sitagliptin lowered serum concentrations of triacylglycerol (-29%) and very large (-46%), large (-35%) and medium-sized (-24%) VLDL particles (all p < 0.05). Body weight, body composition and energy expenditure did not change. In skeletal muscle, sitagliptin increased mRNA expression of PGC1ß (also known as PPARGC1B) (+117%; p < 0.05), a main controller of mitochondrial oxidative energy metabolism. Although the primary endpoint of change in BAT volume and activity was not met, sitagliptin increased [18F] FDG uptake in subcutaneous WAT (sWAT; +53%; p < 0.05). Reported side effects were mild and transient and not necessarily related to the treatment. CONCLUSIONS/INTERPRETATION: Twelve weeks of sitagliptin in overweight, Europid men with prediabetes improves glucose tolerance and lipid metabolism, as related to increased [18F] FDG uptake by sWAT, rather than BAT, and upregulation of the mitochondrial gene PGC1ß in skeletal muscle. Studies on the effect of sitagliptin on preventing or delaying the progression of prediabetes into type 2 diabetes are warranted. TRIAL REGISTRATION: ClinicalTrials.gov NCT02294084. FUNDING: This study was funded by Merck Sharp & Dohme Corp, Dutch Heart Foundation, Dutch Diabetes Research Foundation, Ministry of Economic Affairs and the University of Granada.

Repeatability of metabolically active tumor volume measurements with FDG PET/CT in advanced gastrointestinal malignancies: a multicenter study.

PURPOSE: To evaluate the feasibility and repeatability of various metabolically active tumor volume ( MATV metabolically active tumor volume ) quantification methods in fluorine 18 fluorodeoxyglucose ( FDG fluorine 18 fluorodeoxyglucose ) positron emission tomography (PET)/computed tomography (CT) in a multicenter setting and propose the optimal MATV metabolically active tumor volume method together with the minimal threshold for future response evaluation studies. MATERIALS AND METHODS: The study was approved by the institutional review board of all four participating centers, and patients provided written informed consent. Thirty-four patients with advanced gastrointestinal malignancies underwent two FDG fluorine 18 fluorodeoxyglucose PET/CT examinations within 1 week. MATV metabolically active tumor volume s were defined semiautomatically with 27 variations of tumor delineation methods with different reference values. Feasibility was determined as the percentage of successful tumor segmentations per MATV metabolically active tumor volume method. Repeatability was determined with intraclass correlation coefficients, Bland-Altman plots, and limits of agreement ( LOA limit of agreement s) of the percentage difference between the test and repeat test measurements. In addition, LOA limit of agreement variability per center was investigated. RESULTS: In total, 136 lesions were identified. Feasibility of tumor segmentation ranged from 54% to 100% (74-136 of 136 lesions); repeatability was evaluated for 19 MATV metabolically active tumor volume methods with feasibility of greater than 95%. The median MATV metabolically active tumor volume derived with 50% threshold of mean standardized uptake value ( SUV standardized uptake value ) of a sphere of 12-mm diameter with highest local intensity ( SUVhp mean SUV of a sphere of 12-mm diameter with highest local intensity ), which may not include the voxel with highest SUV standardized uptake value corrected for local background, was 5.7 and 6.1 mL for test and retest scans, respectively, with a relative LOA limit of agreement of 36.1%. Comparable repeatability was found between centers. A difference in uptake time between scan 1 and 2 of 15 minutes or longer had a minor negative influence on repeatability. CONCLUSION: MATV metabolically active tumor volume measured with 50% of SUVhp mean SUV of a sphere of 12-mm diameter with highest local intensity corrected for local background is recommended in multicenter FDG fluorine 18 fluorodeoxyglucose PET/CT studies on the basis of a high feasibility (96%) and repeatability ( LOA limit of agreement of 36.1%).

Dynamic rubidium-82 PET/CT as a novel tool for quantifying hemodynamic differences in renal blood flow using a one-tissue compartment model.

PURPOSE: Assessing renal perfusion in-vivo is challenging and quantitative information regarding renal hemodynamics is hardly incorporated in medical decision-making while abnormal renal hemodynamics might play a crucial role in the onset and progression of renal disease. Combining physiological stimuli with rubidium-82 positron emission tomography/computed tomography (82Rb PET/CT) offers opportunities to test the kidney perfusion under various conditions. The aim of this study is: (1) to investigate the application of a one-tissue compartment model for measuring renal hemodynamics with dynamic 82Rb PET/CT imaging, and (2) to evaluate whether dynamic PET/CT is sensitive to detect differences in renal hemodynamics in stress conditions compared to resting state. METHODS: A one-tissue compartment model for the kidney was applied to cardiac 82Rb PET/CT scans that were obtained for ischemia detection as part of clinical care. Retrospective data, collected from 17 patients undergoing dynamic myocardial 82Rb PET/CT imaging in rest, were used to evaluate various CT-based volumes of interest (VOIs) of the kidney. Subsequently, retrospective data, collected from 10 patients (five impaired kidney functions and five controls) undergoing dynamic myocardial 82Rb PET/CT imaging, were used to evaluate image-derived input functions (IDIFs), PET-based VOIs of the kidney, extraction fractions, and whether dynamic 82Rb PET/CT can measure renal hemodynamics differences using the renal blood flow (RBF) values in rest and after exposure to adenosine pharmacological stress. RESULTS: The delivery rate (K1) values showed no significant (p = 0.14) difference between the mean standard deviation (SD) K1 values using one CT-based VOI and the use of two, three, and four CT-based VOIs, respectively 2.01(0.32), 1.90(0.40), 1.93(0.39), and 1.94(0.40) mL/min/mL. The ratio between RBF in rest and RBF in pharmacological stress for the controls were overall significantly lower compared to the impaired kidney function group for both PET-based delineation methods (region growing and iso-contouring), with the smallest median interquartile range (IQR) of 0.40(0.28-0.66) and 0.96(0.62-1.15), respectively (p < 0.05). The K1 of the impaired kidney function group were close to 1.0 mL/min/mL. CONCLUSIONS: This study demonstrated that obtaining renal K1 and RBF values using 82Rb PET/CT was feasible using a one-tissue compartment model. Applying iso-contouring as the PET-based VOI of the kidney and using AA as an IDIF is suggested for consideration in further studies. Dynamic 82Rb PET/CT imaging showed significant differences in renal hemodynamics in rest compared to when exposed to adenosine. This indicates that dynamic 82Rb PET/CT has potential to detect differences in renal hemodynamics in stress conditions compared to the resting state, and might be useful as a novel diagnostic tool for assessing renal perfusion.

Augmenting CT-Guided Bone Biopsies Using 18F-FDG PET/CT Guidance.

Computer tomography (CT)-guided percutaneous core biopsies are currently the gold standard in diagnostic procedures for patients with bone lesions of unknown kind. CT-guided biopsies can lead to misdiagnosis or repetition of biopsies in case of small or heterogeneous lesions. We hypothesize that molecular image guidance could be used to optimize the biopsy strategy, by supporting the detection of heterogeneous lesions or lesions without radiographic substrate. To evaluate this hypothesis, we investigated if and how the addition of 2-deoxy-2-18F-fluoro-D-glucose-positron emission tomography (18F-FDG-PET)/CT could augment routine CT-guided bone biopsies. To this end, 106 patients who underwent a CT-guided bone biopsy between April 2019 and April 2020, obtained from either a vertebral or peripheral bone, were included. Patients were divided into 2 groups: 36 patients received an 18F-FDG-PET/CT scan prior to their CT-guided bone biopsy (PET group), while 70 patients only had a morphological CT scan (CT group). Histopathology was used to categorize biopsies into five subgroups (inconclusive, benign, malignant or infectious disease, or normal tissue). In the PET group, the number of conclusive biopsies was significantly higher compared to the CT group (N = 33/36 (92%) versus N = 53/70 (76%); p < 0.05). Furthermore, the number of first-try biopsies was lower in the PET group compared to the CT group (1.9 vs. 2.54, p = 0.051). In conclusion, 18F-FDG-PET/CT imaging significantly increased the success rate of first-try CT-guided bone biopsies by showing less inconclusive biopsies and misdiagnosis.

Arterial inflammation on [18F]FDG PET/CT in melanoma patients treated with and without immune checkpoint inhibitors: CHECK-FLAME I.

BACKGROUND AND AIMS: Immune checkpoint inhibitors (ICIs) revolutionized cancer treatment. However, ICIs may increase the immune response to non-tumor cells, possibly resulting in increased arterial inflammation, raising the risk of atherosclerotic events. Nevertheless, malignancies may induce a pro-inflammatory state and the association between ICIs and arterial inflammation remains to be clarified. This study aims to assess differences in increase in arterial inflammation between patients with advanced melanoma treated with ICIs compared to a control group without ICIs. METHODS: Patients with advanced melanoma who underwent [18F]FDG PET/CT scans at baseline, 6 months (T1) and 18 months (T2) were included in this retrospective observational study. Arterial inflammation was evaluated in eight segments by calculating the target-to-background ratio (TBR). The primary study outcome was the difference in increase in mean TBRmax between patients treated with and without ICIs. RESULTS: We included 132 patients of whom 72.7 % were treated with ICIs. After exclusion for the use of anti-inflammatory medication, patients treated with ICIs showed a significant increase in mean TBRmax between baseline and T1 from 1.29 ± 0.12 to 1.33 ± 0.13 (p = 0.017), while in the control group, no change in mean TBRmax (1.30 ± 0.12 to 1.28 ± 0.10, p = 0.22) was observed (p = 0.027). During longer follow-up, mean TBRmax remained stable in both groups. Arterial inflammation increased significantly after ICI therapy in patients without active inflammation (p < 0.001) and in patients without calcifications (p = 0.013). CONCLUSIONS: A significant increase in arterial inflammation as measured on [18F]FDG PET/CT was observed in patients with advanced melanoma treated with ICIs only in the first six months after initiation of therapy, whereas no changes were observed in the control group. Moreover, arterial inflammation was mainly increased in patients without pre-existing inflammatory activity and with non-calcified lesions.

Is PET Radiomics Useful to Predict Pathologic Tumor Response and Prognosis in Locally Advanced Cervical Cancer?

This study investigated whether radiomic features extracted from pretreatment [18F]FDG PET could improve the prediction of both histopathologic tumor response and survival in patients with locally advanced cervical cancer (LACC) treated with neoadjuvant chemoradiotherapy followed by surgery compared with conventional PET parameters and histopathologic features. Methods: The medical records of all consecutive patients with LACC referred between July 2010 and July 2016 were reviewed. [18F]FDG PET/CT was performed before neoadjuvant chemoradiotherapy. Radiomic features were extracted from the primary tumor volumes delineated semiautomatically on the PET images and reduced by factor analysis. A receiver-operating-characteristic analysis was performed, and conventional and radiomic features were dichotomized with Liu's method according to pathologic response (pR) and cancer-specific death. According to the study protocol, only areas under the curve of more than 0.70 were selected for further analysis, including logistic regression analysis for response prediction and Cox regression analysis for survival prediction. Results: A total of 195 patients fulfilled the inclusion criteria. At pathologic evaluation after surgery, 131 patients (67.2%) had no or microscopic (≤3 mm) residual tumor (pR0 or pR1, respectively); 64 patients (32.8%) had macroscopic residual tumor (>3 mm, pR2). With a median follow-up of 76.0 mo (95% CI, 70.7-78.7 mo), 31.3% of patients had recurrence or progression and 20.0% died of the disease. Among conventional PET parameters, SUVmean significantly differed between pathologic responders and nonresponders. Among radiomic features, 1 shape and 3 textural features significantly differed between pathologic responders and nonresponders. Three radiomic features significantly differed between presence and absence of recurrence or progression and between presence and absence of cancer-specific death. Areas under the curve were less than 0.70 for all parameters; thus, univariate and multivariate regression analyses were not performed. Conclusion: In a large series of patients with LACC treated with neoadjuvant chemoradiotherapy followed by surgery, PET radiomic features could not predict histopathologic tumor response and survival. It is crucial to further explore the biologic mechanism underlying imaging-derived parameters and plan a large, prospective, multicenter study with standardized protocols for all phases of the process of radiomic analysis to validate radiomics before its use in clinical routine.

Challenges in Pharmacokinetic Modelling of [18F]fluoro-PEG-folate PET/CT Imaging in Epithelial Ovarian Cancer Patients.

PURPOSE: To describe the pharmacokinetic properties of the [18F]fluoro-polyethylene glycol(PEG)-folate radiotracer in PET/CT imaging of patients with advanced stage epithelial ovarian cancer (EOC). PROCEDURES: In five patients with advanced EOC (FIGO stage IIIB/IIIC, Fédération Internationale de Gynécologie et d'Obstétrique), a 90-min dynamic PET acquisition of the pelvis was performed directly after i.v. administration of 185 MBq [18F]fluoro-PEG6-folate. Arterial blood samples collected at nineteen timepoints were used to determine the plasma input function. A static volume of interest (VOI) for included tumor lesions was drawn manually on the PET images. Modelling was performed using PMOD software. Three different models (a 1-tissue compartment model (1T2k) and two 2-tissue compartment models, irreversible (2T3k) and reversible (2T4k)) were compared in goodness of fit with the time activity curves by means of the Akaike information criterion. RESULTS: The pharmacokinetic analysis in the pelvic area has proven to be much more challenging than expected. Only four out of 22 tumor lesions in five patients were considered suitable to perform modelling on. The remaining tumor lesions were inapt due to either low tracer uptake, small size, proximity to other [18F]fluoro-PEG6-folate -avid structures and/or displacement by abdominal organ motion in the dynamic scan. Data from the four analyzed tumor lesions suggest that the irreversible 2T3k may best describe the pharmacokinetics. All 22 lesions were immunohistochemically stained positive for the folate receptor alpha (FRα) after resection. CONCLUSION: Performing pharmacokinetic analysis in the abdominal pelvic region is very challenging. This brief article describes the challenges and pitfalls in pharmacokinetic analysis of a tracer with high physiological accumulation in the intestines, in case of lesions of limited size in the abdominal pelvic area.

Preoperative [18F]fluoro-PEG-folate PET/CT in advanced stage epithelial ovarian cancer: A safety and feasibility study.

PURPOSE: The selection for either primary or interval cytoreductive surgery (CRS) in patients with epithelial ovarian cancer (EOC) is currently based on imaging techniques like computed tomography (CT), [18F]fluorodeoxyglucose-positron emission tomography ([18F]FDG-PET), diffusion-weighted magnetic resonance imaging (DW-MRI) and/or diagnostic laparoscopy, but these have limitations. Folate receptor (FR)-targeted PET/CT imaging, using [18F]fluoro-PEG-folate, could improve preoperative assessment, potentially reducing unnecessary laparotomies. This paper presents the first experience with [18F]fluoro-PEG-folate PET/CT imaging in advanced stage EOC, focusing on safety, tolerability, and feasibility for reflecting the extent of disease. METHODS: Tolerability and safety were monitored after administration of the [18F]fluoro-PEG-folate tracer by measurements of vital function parameters (blood pressure, heart rate, peripheral oxygen saturation, respiratory rate, and temperature). In addition, (serious) adverse events were recorded. Disease burden was quantified using the Peritoneal Cancer Index (PCI) score on preoperative [18F]fluoro-PEG-folate PET/CT and during surgery. PCI scores were compared with intraoperative findings, considering histopathologic results as the gold standard. Tissue specimens were stained for FRα and FRß. Relative uptake of the radiotracer by EOC lesions and other tissues was quantified using body weighted standardized uptake values (SUV). RESULTS: The study was terminated prematurely during the interim analysis after inclusion of eight patients of whom five had completed the study protocol. Although [18F]fluoro-PEG-folate demonstrated safety, efficacy for tumor-specific imaging was limited. Despite clear FRα overexpression, low tracer uptake was observed in EOC lesions, contrasting with high uptake in healthy tissues, posing challenges in specificity and accurately assessing tumor burden. CONCLUSIONS: Overall, while [18F]fluoro-PEG-folate was well-tolerated, its clinical utility in the preoperative assessment of the extent of disease in EOC was limited. This highlights the need for further research in developing targeted imaging agents for optimal detection of EOC metastases. TRIAL REGISTRATION: Clinicaltrials.gov, NCT05215496. Registered 31 January 2022.

Pharmacokinetic analysis of [18F]FAZA in non-small cell lung cancer patients.

PURPOSE: [(18)F]Fluoroazomycin arabinoside (FAZA) is a positron emission tomography (PET) tracer developed to enable identification of hypoxic regions within a tumour. The aims of this study were to determine the optimal kinetic model along with validation of using alternatives to arterial blood sampling for analysing [(18)F]FAZA studies and to assess the validity of simplified analytical methods. METHODS: Dynamic 70-min [(18)F]FAZA PET/CT scans were obtained from nine non-small cell lung cancer patients. Continuous arterial blood sampling, together with manual arterial and venous sampling, was performed to derive metabolite-corrected plasma input functions. Volumes of interest (VOIs) were defined for tumour, healthy lung muscle and adipose tissue generating [(18)F]FAZA time-activity curves (TACs). TACs were analysed using one- and two-tissue compartment models using both metabolite-corrected blood sampler plasma input functions (BSIF) and image-derived plasma input functions (IDIF). RESULTS: The reversible two-tissue compartment model with blood volume parameter (2T4k+VB) best described kinetics of [(18)F]FAZA in tumours. Volumes of distribution (VT) obtained using IDIF correlated well with those derived using BSIF (R(2) = 0.82). Venous samples yielded the same radioactivity concentrations as arterial samples for times >50 min post-injection (p.i.). In addition, both plasma to whole blood ratios and parent fractions were essentially the same for venous and arterial samples. Both standardised uptake value (SUV), normalised to lean body mass, and tumour to blood ratio correlated well with VT (R(2) = 0.77 and R(2) = 0.87, respectively, at 50-60 min p.i.), although a bias was observed at low VT. CONCLUSION: The 2T4k+VB model provided the best fit to the dynamic [(18)F]FAZA data. IDIF with venous blood samples can be used as input function. Further data are needed to validate the use of simplified methods.

Explainable artificial intelligence (XAI) in radiology and nuclear medicine: a literature review.

Rational: Deep learning (DL) has demonstrated a remarkable performance in diagnostic imaging for various diseases and modalities and therefore has a high potential to be used as a clinical tool. However, current practice shows low deployment of these algorithms in clinical practice, because DL algorithms lack transparency and trust due to their underlying black-box mechanism. For successful employment, explainable artificial intelligence (XAI) could be introduced to close the gap between the medical professionals and the DL algorithms. In this literature review, XAI methods available for magnetic resonance (MR), computed tomography (CT), and positron emission tomography (PET) imaging are discussed and future suggestions are made. Methods: PubMed, Embase.com and Clarivate Analytics/Web of Science Core Collection were screened. Articles were considered eligible for inclusion if XAI was used (and well described) to describe the behavior of a DL model used in MR, CT and PET imaging. Results: A total of 75 articles were included of which 54 and 17 articles described post and ad hoc XAI methods, respectively, and 4 articles described both XAI methods. Major variations in performance is seen between the methods. Overall, post hoc XAI lacks the ability to provide class-discriminative and target-specific explanation. Ad hoc XAI seems to tackle this because of its intrinsic ability to explain. However, quality control of the XAI methods is rarely applied and therefore systematic comparison between the methods is difficult. Conclusion: There is currently no clear consensus on how XAI should be deployed in order to close the gap between medical professionals and DL algorithms for clinical implementation. We advocate for systematic technical and clinical quality assessment of XAI methods. Also, to ensure end-to-end unbiased and safe integration of XAI in clinical workflow, (anatomical) data minimization and quality control methods should be included.

Investigating the potential added value of [ 18 F]FDG-PET/CT in long COVID patients with persistent symptoms: a proof of concept study.

OBJECTIVE: Since the end of 2019, the coronavirus disease 2019 (COVID-19) virus has infected millions of people, of whom a significant group suffers from sequelae from COVID-19, termed long COVID. As more and more patients emerge with long COVID who have symptoms of fatigue, myalgia and joint pain, we must examine potential biomarkers to find quantifiable parameters to define the underlying mechanisms and enable response monitoring. The aim of this study is to investigate the potential added value of [ 18 F]FDG-PET/computed tomography (CT) for this group of long COVID patients. METHODS: For this proof of concept study, we evaluated [ 18 F]FDG-PET/CT scans of long COVID patients and controls. Two analyses were performed: semi-quantitative analysis using target-to-background ratios (TBRs) in 24 targets and total vascular score (TVS) assessed by two independent nuclear medicine physicians. Mann-Whitney U -test was performed to find significant differences between the two groups. RESULTS: Thirteen patients were included in the long COVID group and 25 patients were included in the control group. No significant differences ( P  < 0.05) were found between the long COVID group and the control group in the TBR or TVS assessment. CONCLUSION: As we found no quantitative difference in the TBR or TVS between long COVID patients and controls, we are unable to prove that [ 18 F]FDG is of added value for long COVID patients with symptoms of myalgia or joint pain. Prospective cohort studies are necessary to understand the underlying mechanisms of long COVID.

Stimulation of the beta-2-adrenergic receptor with salbutamol activates human brown adipose tissue.

While brown adipose tissue (BAT) is activated by the beta-3-adrenergic receptor (ADRB3) in rodents, in human brown adipocytes, the ADRB2 is dominantly present and responsible for noradrenergic activation. Therefore, we performed a randomized double-blinded crossover trial in young lean men to compare the effects of single intravenous bolus of the ADRB2 agonist salbutamol without and with the ADRB1/2 antagonist propranolol on glucose uptake by BAT, assessed by dynamic 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography-computed tomography scan (i.e., primary outcome). Salbutamol, compared with salbutamol with propranolol, increases glucose uptake by BAT, without affecting the glucose uptake by skeletal muscle and white adipose tissue. The salbutamol-induced glucose uptake by BAT positively associates with the increase in energy expenditure. Notably, participants with high salbutamol-induced glucose uptake by BAT have lower body fat mass, waist-hip ratio, and serum LDL-cholesterol concentration. In conclusion, specific ADRB2 agonism activates human BAT, which warrants investigation of ADRB2 activation in long-term studies (EudraCT: 2020-004059-34).

Baseline and early digital [ 18 F]FDG PET/CT and multiparametric MRI contain promising features to predict response to neoadjuvant therapy in locally advanced rectal cancer patients: a pilot study.

OBJECTIVE: In this pilot study, we investigated the feasibility of response prediction using digital [ 18 F]FDG PET/computed tomography (CT) and multiparametric MRI before, during, and after neoadjuvant chemoradiation therapy in locally advanced rectal cancer (LARC) patients and aimed to select the most promising imaging modalities and timepoints for further investigation in a larger trial. METHODS: Rectal cancer patients scheduled to undergo neoadjuvant chemoradiation therapy were prospectively included in this trial, and underwent multiparametric MRI and [ 18 F]FDG PET/CT before, 2 weeks into, and 6-8 weeks after chemoradiation therapy. Two groups were created based on pathological tumor regression grade, that is, good responders (TRG1-2) and poor responders (TRG3-5). Using binary logistic regression analysis with a cutoff value of P  ≤ 0.2, promising predictive features for response were selected. RESULTS: Nineteen patients were included. Of these, 5 were good responders, and 14 were poor responders. Patient characteristics of these groups were similar at baseline. Fifty-seven features were extracted, of which 13 were found to be promising predictors of response. Baseline [T2: volume, diffusion-weighted imaging (DWI): apparent diffusion coefficient (ADC) mean, DWI: difference entropy], early response (T2: volume change, DWI: ADC mean change) and end-of-treatment presurgical evaluation MRI (T2: gray level nonuniformity, DWI: inverse difference normalized, DWI: gray level nonuniformity normalized), as well as baseline (metabolic tumor volume, total lesion glycolysis) and early response PET/CT (Δ maximum standardized uptake value, Δ peak standardized uptake value corrected for lean body mass), were promising features. CONCLUSION: Both multiparametric MRI and [ 18 F]FDG PET/CT contain promising imaging features to predict response to neoadjuvant chemoradiotherapy in LARC patients. A future larger trial should investigate baseline, early response, and end-of-treatment presurgical evaluation MRI and baseline and early response PET/CT.

Prognostic Value of [18F]FDG PET Radiomics to Detect Peritoneal and Distant Metastases in Locally Advanced Gastric Cancer-A Side Study of the Prospective Multicentre PLASTIC Study.

AIM: To improve identification of peritoneal and distant metastases in locally advanced gastric cancer using [18F]FDG-PET radiomics. METHODS: [18F]FDG-PET scans of 206 patients acquired in 16 different Dutch hospitals in the prospective multicentre PLASTIC-study were analysed. Tumours were delineated and 105 radiomic features were extracted. Three classification models were developed to identify peritoneal and distant metastases (incidence: 21%): a model with clinical variables, a model with radiomic features, and a clinicoradiomic model, combining clinical variables and radiomic features. A least absolute shrinkage and selection operator (LASSO) regression classifier was trained and evaluated in a 100-times repeated random split, stratified for the presence of peritoneal and distant metastases. To exclude features with high mutual correlations, redundancy filtering of the Pearson correlation matrix was performed (r = 0.9). Model performances were expressed by the area under the receiver operating characteristic curve (AUC). In addition, subgroup analyses based on Lauren classification were performed. RESULTS: None of the models could identify metastases with low AUCs of 0.59, 0.51, and 0.56, for the clinical, radiomic, and clinicoradiomic model, respectively. Subgroup analysis of intestinal and mixed-type tumours resulted in low AUCs of 0.67 and 0.60 for the clinical and radiomic models, and a moderate AUC of 0.71 in the clinicoradiomic model. Subgroup analysis of diffuse-type tumours did not improve the classification performance. CONCLUSION: Overall, [18F]FDG-PET-based radiomics did not contribute to the preoperative identification of peritoneal and distant metastases in patients with locally advanced gastric carcinoma. In intestinal and mixed-type tumours, the classification performance of the clinical model slightly improved with the addition of radiomic features, but this slight improvement does not outweigh the laborious radiomic analysis.