Evaluation of elastix-based propagated align algorithm for VOI- and voxel-based analysis of longitudinal F-18-FDG PET/CT data from patients with non-small cell lung cancer (NSCLC)

Background: Deformable image registration allows volume of interest (VOI)- and voxel-based analysis of longitudinal changes in fluorodeoxyglucose (FDG) tumor uptake in patients with non-small cell lung cancer (NSCLC). This study evaluates the performance of the elastix toolbox deformable image registration algorithm for VOI and voxel-wise assessment of longitudinal variations in FDG tumor uptake in NSCLC patients. Methods: Evaluation of the elastix toolbox was performed using F-18-FDG PET/CT at baseline and after 2 cycles of therapy (follow-up) data in advanced NSCLC patients. The elastix toolbox, an integrated part of the IMALYTICS workstation, was used to apply a CT-based non-linear image registration of follow-up PET/CT data using the baseline PET/CT data as reference. Lesion statistics were compared to assess the impact on therapy response assessment. Next, CT-based deformable image registration was performed anew on the deformed follow-up PET/CT data using the original follow-up PET/CT data as reference, yielding a realigned follow-up PET dataset. Performance was evaluated by determining the correlation coefficient between original and realigned follow-up PET datasets. The intra-and extra-thoracic tumors were automatically delineated on the original PET using a 41% of maximum standardized uptake value (SUVmax) adaptive threshold. Equivalence between reference and realigned images was tested (determining 95% range of the difference) and estimating the percentage of voxel values that fell within that range. Results: Thirty-nine patients with 191 tumor lesions were included. In 37/39 and 12/39 patients, respectively, thoracic and non-thoracic lesions were evaluable for response assessment. Using the EORTC/SUVmax-based criteria, 5/37 patients had a discordant response of thoracic, and 2/12 a discordant response of non-thoracic lesions between the reference and the realigned image. FDG uptake values of corresponding tumor voxels in the original and realigned reference PET correlated well (R-2=0.98). Using equivalence testing, 94% of all the voxel values fell within the 95% range of the difference between original and realigned reference PET. Conclusions: The elastix toolbox impacts lesion statistics and therefore therapy response assessment in a clinically significant way. The elastix toolbox is therefore not applicable in its current form and/or standard settings for PET response evaluation. Further optimization and validation of this technique is necessary prior to clinical implementation

Total Body Metabolic Tumor Response in ALK Positive Non-Small Cell Lung Cancer Patients Treated with ALK Inhibition

In ALK-positive advanced NSCLC, crizotinib has a high response rate and effectively increases quality of life and survival. CT measurement of the tumor may insufficiently reflect the actual tumor load changes during targeted therapy with crizotinib. We explored whether 18F-FDG PET measured metabolic changes are different from CT based changes and studied the impact of these changes on disease progression.18F-FDG PET/CT was performed prior to and after 6 weeks of crizotinib treatment. Tumor response on CT was classified with RECIST 1.1, while 18F-FDG PET response was assessed according to the 1999 EORTC recommendations and PERCIST criteria. Agreement was assessed using McNemars test. During follow-up, patients received additional PET/CT during crizotinib treatment and second generation ALK inhibition. We assessed whether PET was able to detect progression earlier then CT.In this exploratory study 15 patients were analyzed who were treated with crizotinib. There was a good agreement in the applicability of CT and 18F-FDG PET/CT using the EORTC recommendations. During first line crizotinib and subsequent second line ALK inhibitors, PET was able to detect progression earlier then CT in 10/22 (45%) events of progression and in the others disease progression was detected simultaneously.In advanced ALK positive NSCLC PET was able to detect progressive disease earlier than with CT in nearly half of the assessments while both imaging tests performed similar in the others

Pharmacokinetic modeling of [C-11]flumazenil kinetics in the rat brain

BACKGROUND: Preferred models for the pharmacokinetic analysis of [11C]flumazenil human studies have been previously established. However, direct translation of these models and settings to animal studies might be sub-optimal. Therefore, this study evaluates pharmacokinetic models for the quantification of [11C]flumazenil binding in the rat brain. Dynamic (60 min) [11C]flumazenil brain PET scans were performed in two groups of male Wistar rats (tracer dose (TD), n = 10 and pre-saturated (PS), n = 2). Time-activity curves from five regions were analyzed, including the pons (pseudo-reference region). Distribution volume (VT) was calculated using one- and two-tissue compartment models (1TCM and 2TCM) and spectral analysis (SA). Binding potential (BPND) was determined from full and simplified reference tissue models with one or two compartments for the reference tissue (FRTM, SRTM, and SRTM-2C). Model preference was determined by Akaike information criterion (AIC), while parameter agreement was assessed by linear regression, repeated measurements ANOVA and Bland-Altman plots. RESULTS: 1TCM and 2TCM fits of regions with high specific binding showed similar AIC, a preference for the 1TCM, and good VT agreement (0.1% difference). In contrast, the 2TCM was markedly preferred and necessary for fitting low specific-binding regions, where a worse VT agreement (17.6% difference) and significant VT differences between the models (p < 0.005) were seen. The PS group displayed results similar to those of low specific-binding regions. All reference models (FRTM, SRTM, and SRTM-2C) resulted in at least 13% underestimation of BPND. CONCLUSIONS: Although the 1TCM was sufficient for the quantification of high specific-binding regions, the 2TCM was found to be the most adequate for the quantification of [11C]flumazenil in the rat brain based on (1) higher fit quality, (2) lower AIC values, and (3) ability to provide reliable fits for all regions. Reference models resulted in negatively biased BPND and were affected by specific binding in the pons of the rat

Neonates’ responses to repeated exposure to a still face

The main aims of the study were to examine whether human neonates' responses to communication disturbance modelled by the still-face paradigm were stable and whether their responses were affected by their previous experience with the still-face paradigm.The still face procedure, as a laboratory model of interpersonal stress, was administered repeatedly, twice, to 84 neonates (0 to 4 day olds), with a delay of an average of 1.25 day.Frame-by-frame analysis of the frequency and duration of gaze, distressed face, crying, sleeping and sucking behaviours showed that the procedure was stressful to them both times, that is, the still face effect was stable after repeated administration and newborns consistently responded to such nonverbal violation of communication. They averted their gaze, showed distress and cried more during the still-face phase in both the first and the second administration. They also showed a carry-over effect in that they continued to avert their gaze and displayed increased distress and crying in the first reunion period, but their gaze behaviour changed with experience, in the second administration. While in the first administration the babies continued averting their gaze even after the stressful still-face phase was over, this carry-over effect disappeared in the second administration, and the babies significantly increased their gaze following the still-face phase.After excluding explanations of fatigue, habituation and random effects, a self-other regulatory model is discussed as a possible explanation for this pattern

Proceedings of the International Cancer Imaging Society (ICIS) 16th Annual Teaching Course

Table of contents O1 Tumour heterogeneity: what does it mean? Dow-Mu Koh O2 Skeletal sequelae in adult survivors of childhood cancer Sue Creviston Kaste O3 Locoregional effects of breast cancer treatment Sarah J Vinnicombe O4 Imaging of cancer therapy-induced CNS toxicity Giovanni Morana, Andrea Rossi O5 Screening for lung cancer Christian J. Herold O6Risk stratification of lung nodules Theresa C. McLoud O7 PET imaging of pulmonary nodules Kirk A Frey O8 Transarterial tumour therapy Bernhard Gebauer O9 Interventional radiology in paediatric oncology Derek Roebuck O10 Image guided prostate interventions Jurgen J. Fütterer O11 Imaging cancer predisposition syndromes Alexander J. Towbin O12Chest and chest wall masses Thierry AG Huisman O13 Abdominal masses: good or bad? Anne MJB Smets O14 Hepatobiliary MR contrast: enhanced liver MRI for HCC diagnosis and management Giovanni Morana O15 Role of US elastography and multimodality fusion for managing patients with chronic liver disease and HCC Jeong Min Lee O16 Opportunities and challenges in imaging metastatic disease Hersh Chandarana O17 Diagnosis, treatment monitoring, and follow-up of lymphoma Marius E. Mayerhoefer, Markus Raderer, Alexander Haug O18 Managing high-risk and advanced prostate cancer Matthias Eiber O19 Immunotherapy: imaging challenges Bernhard Gebauer O20 RECIST and RECIST 1.1 Andrea Rockall O21 Challenges of RECIST in oncology imaging basics for the trainee and novice Aslam Sohaib O22 Lymphoma: PET for interim and end of treatment response assessment: a users’ guide to the Deauville Score Victoria S Warbey O23 Available resources Hebert Alberto Vargas O24 ICIS e-portal and the online learning community Dow-Mu Koh O25 Benign lesions that mimic pancreatic cancer Jay P Heiken O26 Staging and reporting pancreatic malignancies Isaac R Francis, Mahmoud, M Al-Hawary, Ravi K Kaza O27 Intraductal papillary mucinous neoplasm Giovanni Morana O28 Cystic pancreatic tumours Mirko D’Onofrio O29 Diffusion-weighted imaging of head and neck tumours Harriet C. Thoeny O30 Radiation injury in the head and neck Ann D King O31 PET/MR of paediatric brain tumours Giovanni Morana, Arnoldo Piccardo, Maria Luisa Garrè, Andrea Rossi O32 Structured reporting and beyond Hebert Alberto Vargas O33 Massachusetts General Hospital experience with structured reporting Theresa C. McLoud O34 The oncologist’s perspective: what the oncologist needs to know Nick Reed O35 Towards the cure of all children with cancer: global initiatives in pediatric oncology Carlos Rodriguez-Galindo O36 Multiparametric imaging of renal cancers Hersh Chandarana O37 Linking imaging features of renal disease and their impact on management strategies Hebert Alberto Vargas O38 Adrenals, retroperitoneum and peritoneum Isaac R Francis, Ashish P Wasnik O39 Lung and pleura Stefan Diederich O40 Advances in MRI Jurgen J. Fütterer O41 Advances in molecular imaging Wim J.G. Oyen O42 Incorporating advanced imaging, impact on treatment selection and patient outcome Cheng Lee Chaw, Nicholas van As S1 Combining ADC-histogram features improves performance of MR diffusion-weighted imaging for Lymph node characterisation in cervical cancer Igor Vieira, Frederik De Keyzer, Elleke Dresen, Sileny Han, Ignace Vergote, Philippe Moerman, Frederic Amant, Michel Koole, Vincent Vandecaveye S2 Whole-body diffusion-weighted MRI for surgical planning in patients with colorectal cancer and peritoneal metastases R Dresen, S De Vuysere, F De Keyzer, E Van Cutsem, A D’Hoore, A Wolthuis, V Vandecaveye S3 Role of apparent diffusion coefficient (ADC) diffusion-weighted MRI for predicting extra capsular extension of prostate cancer. P. Pricolo ([email protected]), S. Alessi, P. Summers, E. Tagliabue, G. Petralia S4 Generating evidence for clinical benefit of PET/CT – are management studies sufficient as surrogate for patient outcome? C. Pfannenberg, B. Gückel, SC Schüle, AC Müller, S. Kaufmann, N. Schwenzer, M. Reimold,C. la Fougere, K. Nikolaou, P. Martus S5 Heterogeneity of treatment response in skeletal metastases from breast cancer with 18F-fluoride and 18F-FDG PET GJ Cook, GK Azad, BP Taylor, M Siddique, J John, J Mansi, M Harries, V Goh S6 Accuracy of suspicious breast imaging—can we tell the patient? S Seth, R Burgul, A Seth S7 Measurement method of tumour volume changes during neoadjuvant chemotherapy affects ability to predict pathological response S Waugh, N Muhammad Gowdh, C Purdie, A Evans, E Crowe, A Thompson, S Vinnicombe S8 Diagnostic yield of CT IVU in haematuria screening F. Arfeen, T. Campion, E. Goldstraw S9 Percutaneous radiofrequency ablation of unresectable locally advanced pancreatic cancer: preliminary results D’Onofrio M, Ciaravino V, Crosara S, De Robertis R, Pozzi Mucelli R S10 Iodine maps from dual energy CT improve detection of metastases in staging examinations of melanoma patients M. Uhrig, D. Simons, H. Schlemmer S11Can contrast enhanced CT predict pelvic nodal status in malignant melanoma of the lower limb? Kate Downey S12 Current practice in the investigation for suspected Paraneoplastic Neurological Syndromes (PNS) and positive malignancy yield. S Murdoch, AS Al-adhami, S Viswanathan P1 Technical success and efficacy of Pulmonary Radiofrequency ablation: an analysis of 207 ablations S Smith, P Jennings, D Bowers, R Soomal P2 Lesion control and patient outcome: prospective analysis of radiofrequency abaltion in pulmonary colorectal cancer metastatic disease S Smith, P Jennings, D Bowers, R Soomal P3 Hepatocellular carcinoma in a post-TB patient: case of tropical infections and oncologic imaging challenges TM Mutala, AO Odhiambo, N Harish P4 Role of apparent diffusion coefficient (ADC) diffusion-weighted MRI for predicting extracapsular extension of prostate cancer P. Pricolo, S. Alessi, P. Summers, E. Tagliabue, G. Petralia P5 What a difference a decade makes; comparison of lung biopsies in Glasgow 2005 and 2015 M. Hall, M. Sproule, S. Sheridan P6 Solid pseudopapillary tumour of pancreas: imaging features of a rare neoplasm KY Thein, CH Tan, YL Thian, CM Ho P7 MDCT - pathological correlation in colon adenocarcinoma staging: preliminary experience S De Luca, C Carrera, V Blanchet, L Alarcón, E Eyheremnedy P8 Image guided biopsy of thoracic masses and reduction of pneumothorax risk: 25 years experience B K Choudhury, K Bujarbarua, G Barman P9 Tumour heterogeneity analysis of 18F-FDG-PET for characterisation of malignant peripheral nerve sheath tumours in neurofibromatosis-1 GJ Cook, E Lovat, M Siddique, V Goh, R Ferner, VS Warbey P10 Impact of introduction of vacuum assisted excision (VAE) on screen detected high risk breast lesions L Potti, B Kaye, A Beattie, K Dutton P11 Can we reduce prevalent recall rate in breast screening? AA Seth, F Constantinidis, H Dobson P12 How to reduce prevalent recall rate? Identifying mammographic lesions with low Positive Predictive Value (PPV) AA Seth ([email protected]), F Constantinidis, H Dobson P13 Behaviour of untreated pulmonary thrombus in oncology patients diagnosed with incidental pulmonary embolism on CT R. Bradley, G. Bozas, G. Avery, A. Stephens, A. Maraveyas P14 A one-stop lymphoma biopsy service – is it possible? S Bhuva, CA Johnson, M Subesinghe, N Taylor P15 Changes in the new TNM classification for lung cancer (8th edition, effective January 2017) LE Quint, RM Reddy, GP Kalemkerian P16 Cancer immunotherapy: a review of adequate imaging assessment G González Zapico, E Gainza Jauregui, R Álvarez Francisco, S Ibáñez Alonso, I Tavera Bahillo, L Múgica Álvarez P17 Succinate dehydrogenase mutations and their associated tumours O Francies, R Wheeler, L Childs, A Adams, A Sahdev P18 Initial experience in the usefulness of dual energy technique in the abdomen SE De Luca, ME Casalini Vañek, MD Pascuzzi, T Gillanders, PM Ramos, EP Eyheremendy P19 Recognising the serious complication of Richter’s transformation in CLL patients C Stove, M Digby P20 Body diffusion-weighted MRI in oncologic practice: truths, tricks and tips M. Nazar, M. Wirtz, MD. Pascuzzi, F. Troncoso, F. Saguier, EP. Eyheremendy P21 Methotrexate-induced leukoencephalopathy in paediatric ALL Patients D.J. Quint, L. Dang, M. Carlson, S. Leber, F. Silverstein P22 Pitfalls in oncology CT reporting. A pictorial review R Rueben, S Viswanathan P23 Imaging of perineural extension in head and neck tumours B Nazir, TH Teo, JB Khoo P24 MRI findings of molecular subtypes of breast cancer: a pictorial primer K Sharma, N Gupta, B Mathew, T Jeyakumar, K Harkins P25 When cancer can’t wait! A pictorial review of oncological emergencies K Sharma, B Mathew, N Gupta, T Jeyakumar, S Joshua P26 MRI of pancreatic neuroendocrine tumours: an approach to interpretation D Christodoulou, S Gourtsoyianni, A Jacques, N Griffin, V Goh P27 Gynaecological cancers in pregnancy: a review of imaging CA Johnson, J Lee P28 Suspected paraneoplastic neurological syndromes - review of published recommendations to date, with proposed guideline/flowchart JA Goodfellow, AS Al-adhami, S Viswanathan P29 Multi-parametric MRI of the pelvis for suspected local recurrence of prostate cancer after radical prostatectomy R Bradley P30 Utilisation of PI-RADS version 2 in multi-parametric MRI of the prostate; 12-months experience R Bradley P31 Radiological assessment of the post-chemotherapy liver A Yong, S Jenkins, G Joseph P32 Skeletal staging with MRI in breast cancer – what the radiologist needs to know S Bhuva, K Partington P33 Perineural spread of lympoma: an educational review of an unusual distribution of disease CA Johnson, S Bhuva, M Subesinghe, N Taylor P34 Visually isoattenuating pancreatic adenocarcinoma. Diagnostic imaging tools. C Carrera, A Zanfardini, S De Luca, L Alarcón, V Blanchet, EP Eyheremendy P35 Imaging of larynx cancer: when is CT, MRI or FDG PET/CT the best test? K Cavanagh, E Lauhttp://deepblue.lib.umich.edu/bitstream/2027.42/134651/1/40644_2016_Article_79.pd

Preclinical Evaluation and Quantification of F-18-Fluoroethyl and F-18-Fluoropropyl Analogs of SCH442416 as Radioligands for PET Imaging of the Adenosine A(2A) Receptor in Rat Brain

The cerebral adenosine A(2A) receptor is an attractive therapeutic target for neuropsychiatric disorders. F-18-fluoroethyl and F-18-fluoropropyl analogs of F-18-labeled pyrazolo[4,3-e]-1,2,4-triazolo [1,5-c] pyrimidine (SCH442416) (F-18-FESCH and F-18-FPSCH, respectively) were developed as A(2A) receptor-specific PET ligands. Our aim was to determine an appropriate compartmental model for tracer kinetics, evaluate a reference tissue approach, and select the most suitable PET ligand. Methods: A 90-min dynamic PET scan with arterial blood sampling and metabolite analysis was acquired for 22 healthy male Wistar rats starting at the time of F-18-FESCH (n = 12) and F-18-FPSCH (n = 10) injection. For each tracer, half the animals were vehicle-treated whereas the other half were pretreated with the A(2A) receptor-selective antagonist KW-6002, inducing full blocking. Regional tissue total volume of distribution (V-T) was estimated by 1- and 2-tissue-compartment modeling (1TCM and 2TCM, respectively) and Logan graphical analysis. Midbrain, cerebellum, and hippocampus were evaluated as the reference region by comparing baseline V-T with V-T under full blocking conditions and comparing striatal nondisplaceable binding potential (BPND) using a simplified reference tissue model (SRTM) with distribution volume ratio minus 1 (DVR - 1) for 60- and 90-min scans. Results: On the basis of the Akaike information criterion, 1TCM and 2TCM were the most appropriate models for F-18-FPSCH (baseline striatal VT, 3.7 6 1.1) and F-18-FESCH (baseline striatal V-T, 5.0 6 2.0), respectively. Baseline striatal V-T did not significantly differ between tracers. After pretreatment, striatal V-T was reduced significantly, with no significant decrease in hippocampus, midbrain, or cerebellum V-T. Baseline striatal SRTM BPND did not differ significantly from DVR - 1 except for F-18-FPSCH when using a 60-min scan and midbrain as the reference region, whereas Bland-Altman analysis found a smaller bias for F-18-FESCH and a 60-min scan. After pretreatment, striatal SRTM BPND did not significantly differ from zero except for F-18-FPSCH when using hippocampus as the reference region. Striatal SRTM BPND using midbrain or cerebellum as the reference region was significantly lower for F-18-FPSCH (range, 1.41-2.62) than for F-18-FESCH (range, 1.64-3.36). Conclusion: Dynamic PET imaging under baseline and blocking conditions determined F-18-FESCH to be the most suitable PET ligand for quantifying A(2A) receptor expression in the rat brain. Accurate quantification is achieved by a 60-min dynamic PET scan and the use of either cerebellum or midbrain as the reference region

Dual time-point imaging for post-dose binding potential estimation applied to a [C-11]raclopride PET dose occupancy study

Receptor occupancy studies performed with PET often require time-consuming dynamic imaging for baseline and post-dose scans. Shorter protocol approximations based on standard uptake value ratios have been proposed. However, such methods depend on the time-point chosen for the quantification and often lead to overestimation and bias. The aim of this study was to develop a shorter protocol for the quantification of post-dose scans using a dual time-point approximation, which employs kinetic parameters from the baseline scan. Dual time-point was evaluated for a [C-11]raclopride PET dose occupancy study with the D2 antagonist JNJ-37822681, obtaining estimates for binding potential and receptor occupancy. Results were compared to standard simplified reference tissue model and standard uptake value ratios-based estimates. Linear regression and Bland-Altman analysis demonstrated excellent correlation and agreement between dual time-point and the standard simplified reference tissue model approach. Moreover, the stability of dual time-point-based estimates is shown to be independent of the time-point chosen for quantification. Therefore, a dual time-point imaging protocol can be applied to post-dose [C-11]raclopride PET scans, resulting in a significant reduction in total acquisition time while maintaining accuracy in the quantification of both the binding potential and the receptor occupancy

Baseline patient characteristics.

<p>Baseline patient characteristics.</p

Baseline ¹⁸F-FDG PET and CT tumor response measurements with PERCIST and EORTC criteria and progression-free survival per patient with ALK positive NSCLC.

<p>Baseline ¹⁸F-FDG PET and CT tumor response measurements with PERCIST and EORTC criteria and progression-free survival per patient with ALK positive NSCLC.</p

¹⁸F-FDG maximum intensity projection of patient 2 and 8 prior to (A, B) and after 6 weeks of treatment with crizotinib (C, D).

<p>Scale is from 0–15 SUV. These images illustrate the clinically dramatic decrease in ¹⁸F-FDG uptake, with both patients having a PMR according to both PERCIST criteria and the EORTC recommendations.</p