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.

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.

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.

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.

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).

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.

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.

Development and External Validation of a PET Radiomic Model for Prognostication of Head and Neck Cancer.

AIM: To build and externally validate an [18F]FDG PET radiomic model to predict overall survival in patients with head and neck squamous cell carcinoma (HNSCC). METHODS: Two multicentre datasets of patients with operable HNSCC treated with preoperative afatinib who underwent a baseline and evaluation [18F]FDG PET/CT scan were included (EORTC: n = 20, Unicancer: n = 34). Tumours were delineated, and radiomic features were extracted. Each cohort served once as a training and once as an external validation set for the prediction of overall survival. Supervised feature selection was performed using variable hunting with variable importance, selecting the top two features. A Cox proportional hazards regression model using selected radiomic features and clinical characteristics was fitted on the training dataset and validated in the external validation set. Model performances are expressed by the concordance index (C-index). RESULTS: In both models, the radiomic model surpassed the clinical model with validation C-indices of 0.69 and 0.79 vs. 0.60 and 0.67, respectively. The model that combined the radiomic features and clinical variables performed best, with validation C-indices of 0.71 and 0.82. CONCLUSION: Although assessed in two small but independent cohorts, an [18F]FDG-PET radiomic signature based on the evaluation scan seems promising for the prediction of overall survival for HNSSC treated with preoperative afatinib. The robustness and clinical applicability of this radiomic signature should be assessed in a larger cohort.

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.

Added Value of Respiratory Gating in Positron Emission Tomography for the Clinical Management of Lung Cancer Patients.

Positron emission tomography (PET) is an important imaging modality for personalizing clinical management of patients with lung cancer. In this regard, PET imaging is essential for adequate clinical staging and monitoring of treatment response in patients with lung cancer. The key advantage of PET over other radiological imaging modalities is its high sensitivity for the detection of pulmonary lesions, normal-sized metastatic hilar and/or mediastinal lymph nodes, and distant metastases. Furthermore, with increasing clinical evidence, the role of PET imaging for treatment selection, adaptation, early response monitoring and follow up in patients with lung cancer is being increasingly recognized. At the heart of PET imaging lies the ability to visualize and quantify numerous biological parameters that are responsible for treatment resistance. In order to ensure accurate and reproducible image quantification, harmonization of patient preparation and imaging protocols is essential. Additionally, there are several technical factors during PET scanning that have to be taken care of to safeguard image quality and quantitative accuracy. One of these factors is the occurrence of respiratory motion artifacts, which is a well-known factor that can significantly influence image quality and quantitative accuracy of PET images. If left uncorrected, respiratory motion artifacts can introduce uncertainties in diagnosis and staging, inaccuracies in definition of target volumes for radiation treatment planning, and hinder adequate monitoring of therapy response. Although many different respiratory gating techniques have been developed to correct PET images for respiratory motion artifacts, respiratory gating has traditionally not been widely adopted in clinical practice. This is due to the fact that these methods tend to be disruptive for the clinical workflow due the lengthening of image acquisition times, higher amounts of activity being administered to the patient, and the requirement to synchronize additional hardware with the scanner. Developments in respiratory gating techniques over the last years have resulted in considerable technical improvements. These newer respiratory gating techniques can operate directly on the acquired PET data without the use of additional hardware to trace respiratory motion and can be seamlessly applied into clinical routine. Furthermore, instead of only using a fraction of the acquired PET data newer methods have the ability to use all of the acquired PET data for image reconstruction, thereby improving image quality. The clinically added value of respiratory gating lies in improving image quality by reducing the amount of respiration-induced image blurring. This considerably improves the detection and characterization of small lesions, potentially improving early diagnosis and staging of patients with lung cancer. Furthermore, the incorporation of (4D) respiratory gated PET for radiotherapy purposes has shown to improve target volume definition through more accurate tracking of tumor motion. In addition, the effect of respiratory motion artifacts on widely used volumetric and uptake parameters in PET have been described. Although respiratory gating improves quantitative accuracy of PET images, the exact impact of these corrections on clinical management of patients with lung cancer often still needs to be determined.

Editorial on Special Issue "Quantitative PET and SPECT".

Since the introduction of personalized (or precision) medicine, where individually tailored treatments are designed to deliver the right treatment to the right patient at the right time, the primary focus of imaging has moved from detection and diagnosis to tissue characterization, determination of prognosis, prediction of treatment efficacy, and measurement of treatment response [...].

The current status and future prospects for molecular imaging-guided precision surgery.

Molecular imaging technologies are increasingly used to diagnose, monitor, and guide treatment of i.e., cancer. In this review, the current status and future prospects of the use of molecular imaging as an instrument to help realize precision surgery is addressed with focus on the main components that form the conceptual basis of intraoperative molecular imaging. Paramount for successful interventions is the relevance and accessibility of surgical targets. In addition, selection of the correct combination of imaging agents and modalities is critical to visualize both microscopic and bulk disease sites with high affinity and specificity. In this context developments within engineering/imaging physics continue to drive the growth of image-guided surgery. Particularly important herein is enhancement of sensitivity through improved contrast and spatial resolution, features that are critical if sites of cancer involvement are not to be overlooked during surgery. By facilitating the connection between surgical planning and surgical execution, digital surgery technologies such as computer-aided visualization nicely complement these technologies. The complexity of image guidance, combined with the plurality of technologies that are becoming available, also drives the need for evaluation mechanisms that can objectively score the impact that technologies exert on the performance of healthcare professionals and outcome improvement for patients.

Early Prediction and Monitoring of Treatment Response in Gastrointestinal Stromal Tumors by Means of Imaging: A Systematic Review.

Gastrointestinal stromal tumors (GISTs) are rare mesenchymal neoplasms. Tyrosine kinase inhibitor (TKI) therapy is currently part of routine clinical practice for unresectable and metastatic disease. It is important to assess the efficacy of TKI treatment at an early stage to optimize therapy strategies and eliminate futile ineffective treatment, side effects and unnecessary costs. This systematic review provides an overview of the imaging features obtained from contrast-enhanced (CE)-CT and 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) PET/CT to predict and monitor TKI treatment response in GIST patients. PubMed, Web of Science, the Cochrane Library and Embase were systematically screened. Articles were considered eligible if quantitative outcome measures (area under the curve (AUC), correlations, sensitivity, specificity, accuracy) were used to evaluate the efficacy of imaging features for predicting and monitoring treatment response to various TKI treatments. The methodological quality of all articles was assessed using the Quality Assessment of Diagnostic Accuracy Studies, v2 (QUADAS-2) tool and modified versions of the Radiomics Quality Score (RQS). A total of 90 articles were included, of which 66 articles used baseline [18F]FDG-PET and CE-CT imaging features for response prediction. Generally, the presence of heterogeneous enhancement on baseline CE-CT imaging was considered predictive for high-risk GISTs, related to underlying neovascularization and necrosis of the tumor. The remaining articles discussed therapy monitoring. Clinically established imaging features, including changes in tumor size and density, were considered unfavorable monitoring criteria, leading to under- and overestimation of response. Furthermore, changes in glucose metabolism, as reflected by [18F]FDG-PET imaging features, preceded changes in tumor size and were more strongly correlated with tumor response. Although CE-CT and [18F]FDG-PET can aid in the prediction and monitoring in GIST patients, further research on cost-effectiveness is recommended.

Reinducing Radioiodine-Sensitivity in Radioiodine-Refractory Thyroid Cancer Using Lenvatinib (RESET): Study Protocol for a Single-Center, Open Label Phase II Trial.

Background: Management of patients with radioiodine (RAI)-refractory differentiated thyroid cancer (DTC) is a challenge as I-131 therapy is deemed ineffective while standard-of-care systemic therapy with tyrosine kinase inhibitor (TKI) lenvatinib is associated with frequent toxicities leading to dose reductions and withdrawal. A potential new treatment approach is to use TKIs as redifferentiation agent to restore RAI uptake to an extent that I-131 therapy is warranted. Prior studies show that short-term treatment with other TKIs restores RAI uptake in 50-60% of radioiodine-refractory DTC patients, but this concept has not been investigated for lenvatinib. Furthermore, the optimal duration of treatment with TKIs for maximal redifferentiation has not been explored. Methods and Design: A total of 12 patients with RAI-refractory DTC with an indication for lenvatinib will undergo I-124 PET/CT to quantify RAI uptake. This process is repeated after 6 and 12 weeks post-initiating lenvatinib after which the prospective dose estimate to target lesions and organs at risk will be determined. Patients will subsequently stop lenvatinib and undergo I-131 treatment if it is deemed effective and safe by predefined norms. The I-124 PET/CT measurements after 6 and 12 weeks of the first six patients are compared and the optimal timepoint will be determined for the remaining patients. In all I-131 treated patients post-therapy SPECT/CT dosimetry verification will be performed. During follow-up, clinical response will be evaluated using serum thyroglobulin levels and F-18 FDG PET/CT imaging for 6 months. It is hypothesized that at least 40% of patients will show meaningful renewed RAI uptake after short-term lenvatinib treatment. Discussion: Shorter treatment duration of lenvatinib treatment is preferred because of frequent toxicity-related dose reductions and drug withdrawals in long-term lenvatinib treatment. Short-term treatment with lenvatinib with subsequent I-131 therapy poses a potential new management approach for these patients. Since treatment duration is reduced and I-131 therapy is more tolerable for most patients, this potentially leads to less toxicity and higher quality of life. Identifying RAI-refractory DTC patients who redifferentiate after lenvatinib therapy is therefore crucial. Trial Registration: ClinicalTrials.gov, NTC04858867.