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

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

Does multiparametric imaging with 18F-FDG-PET/MRI capture spatial variation in immunohistochemical cancer biomarkers in head and neck squamous cell carcinoma?

BACKGROUND: The purpose of this study is to test if functional multiparametric imaging with 18F-FDG-PET/MRI correlates spatially with immunohistochemical biomarker status within a lesion of head and neck squamous cell carcinoma (HNSCC), and also whether a biopsy with the highest FDG uptake was more likely to have the highest PD-L1 expression or the highest percentage of vital tumour cells (VTC) compared with a random biopsy. METHODS: Thirty-one patients with HNSCC were scanned on an integrated PET/MRI scanner with FDG prior to surgery in this prospective study. Imaging was quantified with SUV, ADC and Ktrans. A 3D-morphometric MRI scan of the specimen was used to co-register the patient and the specimen scans. All specimens were sectioned in consecutive slices, and slices from six different locations were selected randomly from each tumour. Core biopsies were performed to construct TMA blocks for IHC staining with the ten predefined biomarkers. The spatial correlation was assessed with a partial correlation analysis. RESULTS: Twenty-eight patients with a total of 33 lesions were eligible for further analysis. There were significant correlations between the three imaging biomarkers and some of the IHC biomarkers. Moreover, a biopsy taken from the most FDG-avid part of the tumour did not have a statistically significantly higher probability of higher PD-L1 expression or VTC, compared with a random biopsy. CONCLUSION: We found statistically significant correlations between functional imaging parameters and key molecular cancer markers.

Intratumor heterogeneity of PD-L1 expression in head and neck squamous cell carcinoma.

Intratumor heterogeneity may contribute to the ambiguous clinical results on PD-L1 status as a predictor for immunotherapy response in patients with HNSCC. This decreases the utility of PD-L1 expression from single tumour biopsies as a predictive biomarker. In this prospective study, intratumor heterogeneity of PD-L1 expression in HNSCC was investigated with both Tumour Proportion Score (TPS) and Combined Positive Score (CPS). Thirty-three whole surgical specimens from 28 patients with HNSCC were included. PD-L1 expression in six random core biopsies from each surgical specimen was used to assess the concordance between multiple biopsies and the negative predictive value of a single negative core biopsy. With 1% cut off, 36% of the specimens were concordant with TPS and 52% with CPS. With a 50% cut-off value the concordance was 70% with TPS and 55% with CPS. Defining a tumour as positive if just a single-one of the biopsies was positive, the negative predictive value (NPV) of a single negative core biopsy was 38.9 and 0% (1% cut off), and 79.9% and 62.8% (50% cut off) for TPS and CPS, respectively. In conclusion, PD-L1 positivity varies markedly within the tumour, both with TPS and CPS, challenging the utility of this biomarker.

Immunohistochemical and molecular imaging biomarker signature for the prediction of failure site after chemoradiation for head and neck squamous cell carcinoma.

OBJECTIVE: To identify a failure site-specific prognostic model by combining immunohistochemistry (IHC) and molecular imaging information to predict long-term failure type in squamous cell carcinoma of the head and neck. PATIENT AND METHODS: Tissue microarray blocks of 196 head and neck squamous cell carcinoma cases were stained for a panel of biomarkers using IHC. Gross tumor volume (GTV) from the PET/CT radiation treatment planning CT scan, maximal Standard Uptake Value (SUVmax) of fludeoxyglucose (FDG) and clinical information were included in the model building using Cox proportional hazards models, stratified for p16 status in oropharyngeal carcinomas. Separate models were built for time to locoregional failure and time to distant metastasis. RESULTS: Higher than median p53 expression on IHC tended toward a risk factor for locoregional failure but was protective for distant metastasis, χ2 for difference p = .003. The final model for locoregional failure included p53 (HR: 1.9; p: .055), concomitant cisplatin (HR: 0.41; p: .008), ß-tubulin-1 (HR: 1.8; p: .08), ß-tubulin-2 (HR: 0.49; p: .057) and SUVmax (HR: 2.1; p: .046). The final model for distant metastasis included p53 (HR: 0.23; p: .025), Bcl-2 (HR: 2.6; p: .08), SUVmax (HR: 3.5; p: .095) and GTV (HR: 1.7; p: .063). CONCLUSIONS: The models successfully distinguished between risk of locoregional failure and risk of distant metastasis, which is important information for clinical decision-making. High p53 expression has opposite prognostic effects for the two endpoints; increasing risk of locoregional failure, but decreasing the risk of metastatic failure, but external validation of this finding is needed.

Spatio-temporal stability of pre-treatment 18F-Fludeoxyglucose uptake in head and neck squamous cell carcinomas sufficient for dose painting.

BACKGROUND: The pre-treatment 18F-Fludeoxyglucose (FDG) avid subvolume of the tumor has shown promise as a potential target for dose painting in patients with in head and neck squamous cell carcinomas (HNSCC). PURPOSE: The purposes of this study are: 1) to assess the pre-treatment spatio-temporal variability of FDG PET/CT target volumes and 2) to assess the impact of this variability on dose distribution in dose painting plans in patients with HNSCC. MATERIAL AND METHODS: Thirty patients were enrolled and scanned twice, three days apart, days prior to treatment. Delineation of the FDG avid subvolume of the tumor and lymph nodes on both scans was performed by a specialist in nuclear medicine yielding GTVPET1 and GTVPET2 and segmentation based on SUV iso-contours were constructed yielding two metabolic target volumes, MTV1 and MTV2. Images were co-registered rigidly and dose painting plans with dose escalation up to 82 Gy to GTVPET1 were planned and GTVPET2 was copied from the co-registered images to the dose planning scan. Variation in dose to the target and modeled tumor control probability were assessed as measures of the impact of imaging variations in a dose painting scenario. RESULTS: Twenty-four patients were available for full analysis. The median mismatch between GTVPET1 and GTVPET2 was 14.2% (1.7 cm(3)). The median difference in dose to the FDG planning target volume was 0.3 Gy (PTVPET) and 0.4 Gy (PTVMTV). Median difference in the modeled tumor control probability (TCP) was < 0.2% and 23 of 24 patients had a difference in expected TCP < 1%. CONCLUSIONS: Pre-treatment FDG PET/CT target volumes were stable and day-to-day variability had no relevant impact on dose distribution and expected tumor control in dose painting plans.

Positive correlation of trophic level and proportion of sexual taxa of oribatid mites (Acari: Oribatida) in alpine soil systems.

We investigated community structure, trophic ecology (using stable isotope ratios; (15)N/(14)N, (13)C/(12)C) and reproductive mode of oribatid mites (Acari, Oribatida) along an altitudinal gradient (2,050-2,900 m) in the Central Alps (Obergurgl, Austria). We hypothesized that (1) the community structure changes with altitude, (2) oribatid mites span over four trophic levels, (3) the proportion of sexual taxa increases with altitude, and (4) the proportion of sexual taxa increases with trophic level, i.e. is positively correlated with the δ(15)N signatures. Oribatid mite community structure changed with altitude indicating that oribatid mites occupy different niches at different altitudes. Oribatid mites spanned over 12 δ(15)N units, i.e. about four trophic levels, which is similar to lowland forest ecosystems. The proportion of sexually reproducing taxa increased from 2,050 to 2,900 m suggesting that limited resource availability at high altitudes favors sexual reproduction. Sexual taxa more frequently occurred higher in the food web indicating that the reproductive mode is related to nutrition of oribatid mites. Generally, oribatid mite community structure changed from being decomposer dominated at lower altitude to being dominated by fungal and lichen feeders, and predators at higher altitude. This supports the view that resources from dead organic material become less available with increasing altitude forcing species to feed on living resources such as fungi, lichens and nematodes. Our findings support the hypothesis that limited resource accessibility (at high altitudes) favors sexually reproducing species whereas ample resource supply (at lower altitudes) favors parthenogenetic species.

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

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

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

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

Biodiversity of oribatid mites (Acari: Oribatida) along an altitudinal gradient in the Central Alps.

Oribatid mite communities were studied in the Central Alps (Obergurgl, Tyrol, Austria). Samples were taken on four sites along an altitudinal gradient from 2050 m a.s.l to 2900 m a.s.l., in different vegetation units (pine forest, Nardetum, Caricetum, Androsacetum). A total of 86 species were found, most of them occurred only at one altitude, four species were found in all four study sites. Three taxa could not be ascribed to a certain species (Carabodes sp. Mycobates sp., Tectocepheus sp.). Species richness and density of oribatid mites decrease with increasing altitude. The results are compared with previous studies in the same region and show remarkable shifts in species composition.

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

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

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

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

A case-control evaluation of pulmonary and extrapulmonary findings of incidental asymptomatic COVID-19 infection on FDG PET-CT.

OBJECTIVES: To describe the findings of incidental asymptomatic COVID-19 infection on FDG PET-CT using a case-control design. METHODS: Incidental pulmonary findings suspicious of asymptomatic COVID-19 infection on FDG PET-CT were classified as a confirmed (positive RT-PCR test) or suspected case (no/negative RT-PCR test). Control cases were identified using a 4:1 control:case ratio. Pulmonary findings were re-categorised by two reporters using the BSTI classification. SUV metrics in ground glass opacification (GGO)/consolidation (where present), background lung, intrathoracic nodes, liver, spleen and bone marrow were measured. RESULTS: 7/9 confirmed and 11/15 suspected cases (COVID-19 group) were re-categorised as BSTI 1 (classic/probable COVID-19) or BSTI 2 (indeterminate COVID-19); 0/96 control cases were categorised as BSTI 1. Agreement between two reporters using the BSTI classification was almost perfect (weighted κ = 0.94). SUVmax GGO/consolidation (5.1 vs 2.2; p < 0.0001) and target-to-background ratio, normalised to liver SUVmean (2.4 vs 1.0; p < 0.0001) were higher in the BSTI 1 & 2 group vs BSTI 3 (non-COVID-19) cases. SUVmax GGO/consolidation discriminated between the BSTI 1 & 2 group vs BSTI 3 (non-COVID-19) cases with high accuracy (AUC = 0.93). SUV metrics were higher (p < 0.05) in the COVID-19 group vs control cases in the lungs, intrathoracic nodes and spleen. CONCLUSION: Asymptomatic COVID-19 infection on FDG PET-CT is characterised by bilateral areas of FDG avid (intensity > x2 liver SUVmean) GGO/consolidation and can be identified with high interobserver agreement using the BSTI classification. There is generalised background inflammation within the lungs, intrathoracic nodes and spleen. ADVANCES IN KNOWLEDGE: Incidental asymptomatic COVID-19 infection on FDG PET-CT, characterised by bilateral areas of ground glass opacification and consolidation, can be identified with high reproducibility using the BSTI classification. The intensity of associated FDG uptake (>x2 liver SUVmean) provides high discriminative ability in differentiating such cases from pulmonary findings in a non-COVID-19 pattern. Asymptomatic COVID-19 infection causes a generalised background inflammation within the mid-lower zones of the lungs, hilar and central mediastinal nodal stations, and spleen on FDG PET-CT.

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

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

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

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

Multimodality approach to mediastinal staging in non-small cell lung cancer. Faults and benefits of PET-CT: a randomised trial.

BACKGROUND: Correct mediastinal staging is a cornerstone in the treatment of patients with non-small cell lung cancer. A large range of methods is available for this purpose, making the process of adequate staging complex. The objective of this study was to describe faults and benefits of positron emission tomography (PET)-CT in multimodality mediastinal staging. METHODS: A randomised clinical trial was conducted including patients with a verified diagnosis of non-small cell lung cancer, who were considered operable. Patients were assigned to staging with PET-CT (PET-CT group) followed by invasive staging (mediastinoscopy and/or endoscopic ultrasound with fine needle aspiration (EUS-FNA)) or invasive staging without prior PET-CT (conventional work up (CWU) group). Mediastinal involvement (dichotomising N stage into N0-1 versus N2-3) was described according to CT, PET-CT, mediastinoscopy, EUS-FNA and consensus (based on all available information), and compared with the final N stage as verified by thoracotomy or a conclusive invasive diagnostic procedure. RESULTS: A total of 189 patients were recruited, 98 in the PET-CT group and 91 in the CWU group. In an intention-to-treat analysis the overall accuracy of the consensus N stage was not significantly higher in the PET-CT group than in the CWU group (90% (95% confidence interval 82% to 95%) vs 85% (95% CI 77% to 91%)). Excluding the patients in whom PET-CT was not performed (n=14) the difference was significant (95% (95% CI 88% to 98%) vs 85% (95% CI 77% to 91%), p=0.034). This was mainly based on a higher sensitivity of the staging approach including PET-CT. CONCLUSION: An approach to lung cancer staging with PET-CT improves discrimination between N0-1 and N2-3. In those without enlarged lymph nodes and a PET-negative mediastinum the patient may proceed directly to surgery. However, enlarged lymph nodes on CT needs confirmation independent of PET findings and a positive finding on PET-CT needs confirmation before a decision on surgery is made. CLINICAL TRIAL NUMBER: NCT00867412.

Effect of Follow-Up Surveillance After Curative-Intent Treatment of NSCLC on Detection of New and Recurrent Disease, Retreatment, and Survival: A Systematic Review and Meta-Analysis.

INTRODUCTION: Patients with NSCLC may be treated with curative intent, yet they remain at high risk of both disease recurrence and second primary lung cancer (SPLC) and increased risk of early death. Guidelines provide recommendations for follow-up, but there is little consensus, and review of available evidence is necessary. The use of a systematic follow-up strategy for the detection of disease recurrence or SPLC after curative-intent treatment of NSCLC may increase the proportion of patients available for retreatment and increase the survival of patients with surveillance detection. METHODS: We performed a systematic review and meta-analysis of prospective studies on follow-up of NSCLC after curative-intent treatment to answer the following three questions: What is the effect of follow-up on detection of recurrence or SPLC? What is the effect of surveillance detection on curative-intent retreatment? What is the survival impact? RESULTS: Recurrence or SPLC was observed in 17.8% to 71% of patients. Scheduled imaging-detected recurrence in 60% to 100% of cases, yet neither computed tomography-based (OR = 2.31, 95% confidence interval [CI]: 0.27-19.49, p = 0.44) nor positron emission tomography-computed tomography-based follow-up (OR = 1.431, 95% CI: 0.92-2.22, p = 0.12) was statistically superior to standard follow-up strategies. Detection of disease recurrence/SPLC significantly increased the odds of curative-intent retreatment (OR = 4.31; 95% CI: 2.10-8.84, p < 0.0001). Curative-intent retreatment prolonged survival in reported studies. CONCLUSIONS: The early detection of disease recurrence/SPLC may increase the likelihood of curative-intent retreatment and prolong survival. There is a clear need for prospective randomized controlled studies of follow-up to confirm effectiveness of available follow-up modalities.

Intratumor heterogeneity is biomarker specific and challenges the association with heterogeneity in multimodal functional imaging in head and neck squamous cell carcinoma.

RATIONALE: Tumor biopsy cannot detect heterogeneity and an association between heterogeneity in functional imaging and molecular biology will have an impact on both diagnostics and treatment possibilities. PURPOSE: Multiparametric imaging can provide 3D information on functional aspects of a tumor and may be suitable for predicting intratumor heterogeneity. Here, we investigate the correlation between intratumor heterogeneity assessed with multiparametric imaging and multiple-biopsy immunohistochemistry. METHODS: In this prospective study, patients with primary or recurrent head and neck squamous cell carcinoma (HNSCC) underwent PET/MRI scanning prior to surgery. Tumors were removed en bloc and six core biopsies were used for immunohistochemical (IHC) staining with a predefined list of biomarkers: p40, p53, EGFR, Ki-67, GLUT1, VEGF, Bcl-2, CAIX, PD-L1. Intratumor heterogeneity of each IHC biomarker was quantified by calculating the coefficient of variation (CV) in tumor proportion score among the six core biopsies within each tumor lesion. The heterogeneity in the imaging biomarkers was assessed by calculating CV in 18F-fluorodeoxyglucose (FDG)-uptake, diffusion and perfusion. Concordance of the two variance measures was quantified using Spearman's rank correlation RESULTS: Twenty-eight patients with a total of 33 lesions were included. There was considerable heterogeneity in most of the IHC biomarkers especially in GLUT1, PD-L1, Ki-67, CAIX and p53, however we only observed a correlation between the heterogeneity in GLUT1 and p53 and between Ki-67 and EGFR. Heterogeneity in FDG uptake and diffusion correlated with heterogeneity in cell density. CONCLUSION: Considerable heterogeneity of IHC biomarkers was found, however, only few and weak correlations between the studied IHC markers were observed. The studied functional imaging biomarkers showed weak associations with heterogeneity in some of the IHC biomarkers. Thus, biological heterogeneity is not a general tumor characteristic but depends on the specific biomarker or imaging modality.

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

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

Community structure, trophic position and reproductive mode of soil and bark-living oribatid mites in an alpine grassland ecosystem.

The community structure, stable isotope ratios ((15)N/(14)N, (13)C/(12)C) and reproductive mode of oribatid mites (Acari, Oribatida) were investigated in four habitats (upper tree bark, lower tree bark, dry grassland soil, forest soil) at two sites in the Central Alps (Tyrol, Austria). We hypothesized that community structure and trophic position of oribatid mites of dry grassland soils and bark of trees are similar since these habitats have similar abiotic characteristics (open, dry) compared with forest soil. Further, we hypothesized that derived taxa of oribatid mites reproducing sexually dominate on the bark of trees since species in this habitat consume living resources such as lichens. In contrast to our hypothesis, the community structure of oribatid mites differed among grassland, forest and bark indicating the existence of niche differentiation in the respective oribatid mite species. In agreement with our hypothesis, sexually reproducing taxa of oribatid mites dominated on the bark of trees whereas parthenogenetic species were more frequent in soil. Several species of bark-living oribatid mites had stable isotope signatures that were similar to lichens indicating that they feed on lichens. However, nine species that frequently occurred on tree bark did not feed on lichens according to their stable isotope signatures. No oribatid mite species could be ascribed to moss feeding. We conclude that sexual reproduction served as preadaptation for oribatid mites allowing them to exploit new habitats and new resources on the bark of trees. Abiotic factors likely are of limited importance for bark-living oribatid mites since harsh abiotic conditions are assumed to favor parthenogenesis.

Feasibility of Multiparametric Positron Emission Tomography/Magnetic Resonance Imaging as a One-Stop Shop for Radiation Therapy Planning for Patients with Head and Neck Cancer.

PURPOSE: Multiparametric positron emission tomography (PET)/magnetic resonance imaging (MRI) as a one-stop shop for radiation therapy (RT) planning has great potential but is technically challenging. We studied the feasibility of performing multiparametric PET/MRI of patients with head and neck cancer (HNC) in RT treatment position. As a step toward planning RT based solely on PET/MRI, a deep learning approach was employed to generate synthetic computed tomography (sCT) from MRI. This was subsequently evaluated for dose calculation and PET attenuation correction (AC). METHODS AND MATERIALS: Eleven patients, including 3 pilot patients referred for RT of HNC, underwent PET/MRI in treatment position after a routine fluorodeoxyglucose-PET/CT planning scan. The PET/MRI scan protocol included multiparametric imaging. A convolutional neural network was trained in a leave-one-out process to predict sCT from the Dixon MRI. The clinical CT-based dose plans were recalculated on sCT, and the plans were compared in terms of relative differences in mean, maximum, near-maximum, and near-minimum absorbed doses for different volumes of interest. Comparisons between PET with sCT-based AC and PET with CT-based AC were assessed based on the relative differences in mean and maximum standardized uptake values (SUVmean and SUVmax) from the PET-positive volumes. RESULTS: All 11 patients underwent PET/MRI in RT treatment position. Apart from the 3 pilots, full multiparametric imaging was completed in 45 minutes for 7 out of 8 patients. One patient terminated the examination after 30 minutes. With the exception of 1 patient with an inserted tracheostomy tube, all dosimetric parameters of the sCT-based dose plans were within ±1% of the CT-based dose plans. For PET, the mean difference was 0.4 ± 1.2% for SUVmean and -0.5 ± 1.0% for SUVmax. CONCLUSIONS: Performing multiparametric PET/MRI of patients with HNC in RT treatment position was clinically feasible. The sCT generation resulted in AC of PET and dose calculations sufficiently accurate for clinical use. These results are an important step toward using multiparametric PET/MRI as a one-stop shop for personalized RT planning.