An automatic method for accurate volume delineation of heterogeneous tumors in PET

Total lesion glycolysis of primary tumor and lymphnodes is a strong predictor for development of distant metastases in oropharyngeal carcinoma patients with independent validation in automatically delineated lesions

BACKGROUND

Oropharyngeal carcinomas are characterized by an increasing incidence and a relatively good prognosis. Nonetheless, a considerable number of patients develops metachronous distant metastases; identification of these patients is an urgent medical need.

METHODS

This is a retrospective multicenter evaluation of 431 patients. All patients underwent [18F]-FDG positron emission tomography (PET). The cohort was split into an explorative group (n = 366) and a validation group (n = 65). Lesions were manually delineated in the explorative group and automatically delineated by a convolutional neuronal network (CNN) in the validation group. Quantitative PET parameters standardized uptake value (SUV), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were calculated for primary tumors (prim) and tumor plus lymphnodes (all). Association of parameters with freedom from distant metastases (FFDM) and overall survival (OS) was tested by cox regression analyses.

RESULTS

In the explorative group, univariate analyses revealed an association of metric MTVprim (p = 0.022), MTVall (p < 0.001) and TLGall (p < 0.001) with FFDM, binarized parameters were also associated with FFDM (p < 0.001 and p = 0.002). Bootstrap analyses revealed a significantly better association of TLGall compared to TLGprim with FFDM (p = 0.02). MTVall and TLGall remained significantly associated with FFDM upon multivariate testing (p = 0.002, p = 0.031, respectively). In the validation group, the cutoff value for TLGall but not for TLGprim was significantly associated with FFDM (HR = 3.1, p = 0.045). Additional analyses with manually delineated contours of the validation cohort revealed a similar effect (HR = 3.47, p = 0.026). No considerable differences between HPV positive and negative disease were observed.

CONCLUSIONS

TLGall is a promising biomarker to select OPC patients with high risk for metachronous distant metastases.

Discrimination of benign, atypical, and malignant peripheral nerve sheath tumours in neurofibromatosis type 1 - intraindividual comparison of positron emission computed tomography and diffusion-weighted magnetic resonance imaging

BACKGROUND

To intraindividually compare the diagnostic performance of positron emission computed tomography (F-18-FDG-PET/CT) and diffusion-weighted magnetic resonance imaging (DW-MRI) in a non-inferiority design for the discrimination of peripheral nerve sheath tumours as benign (BPNST), atypical (ANF), or malignant (MPNST) in patients with neurofibromatosis type 1 (NF1).

RESULTS

In this prospective single-centre study, thirty-four NF1 patients (18 male; 30 ± 11 years) underwent F-18-FDG-PET/CT and multi-b-value DW-MRI (11 b-values 0 - 800 s/mm²) at 3T. Sixty-six lesions corresponding to 39 BPNST, 11 ANF, and 16 MPNST were evaluated. Two radiologists independently assessed the maximum standardized uptake value (SUVmax) and mean and minimum apparent diffusion coefficient (ADCmean/min) as well as the ADC in areas of lowest signal intensity in each lesion (ADCdark). The AUCs of DW-MRI and F-18-FDG-PET/CT were compared to determine whether the ADC is non-inferior to SUVmax (non-inferiority margin equal to -10%). Follow-up of ≥ 24 months (BPNST) or histopathological evaluation (MPNST + ANF) served as diagnostic reference standard. Both SUVmax and ADC parameters demonstrated good diagnostic accuracy (AUCSUVmax 94.0%; AUCADCmean/min/dark 91.6% / 90.1% / 92.5%). However, non-inferiority could not be demonstrated for any of the three ADC parameters (lower limits of the confidence intervals of the difference between the AUC of ADCmean/min/dark and SUVmax -12.9% / -14.5% / -11.6%). Inter-rater reliability was excellent for both imaging techniques (Krippendorff's alpha all > 0.94).

CONCLUSIONS

Both PET/CT-derived SUVmax and MRI-derived ADC allow sensitive and non-invasive differentiation of benign and (pre)-malignant peripheral nerve sheath tumours. Nevertheless, DW-MRI cannot be considered as non-inferior to F-18-FDG-PET/CT in this prospective single-centre study.

Organ and tumor dosimetry including method simplification for [177Lu]Lu-PSMA-I&T for treatment of metastatic castration resistant prostate cancer

BACKGROUND

Internal dosimetry in individual patients is essential for safe and effective radioligand therapy. Multiple time point imaging for accurate dosimetry is time consuming and hence can be demanding for nuclear medicine departments as well as patients. The objectives of this study were (1) to assess absorbed doses to organs at risk and tumor lesions for [177Lu]Lu-PSMA-I&T using whole body SPECT imaging and (2) to investigate possible simplified dosimetry protocols.

METHODS

This study included 16 patients each treated with 4 cycles of [177Lu]Lu-PSMA-I&T. They underwent quantitative whole body SPECT/CT imaging (3 bed positions) at four time points (TP) comprising 2 h, 24 h, 48 h and 72-168 h post-injection (p.i.). Full 3D dosimetry (reference method) was performed for all patients and dose cycles for organs at risk (kidneys, parotid glands and submandibular glands) and up to ten tumor lesions per patient (resulting in 90 lesions overall). The simplified dosimetry methods (SM) included (1) generating time activity curves for subsequent cycles using a single TP of imaging applying the kinetics of dose cycle 1, and for organs at risk also (2) simple extrapolation from dose cycle 1 and (3) from both, dose cycle 1 and 2.

RESULTS

Normalized absorbed doses were 0.71 ± 0.32 mGy/MBq, 0.28 ± 0.12 mGy/MBq and 0.22 ± 0.08 mGy/MBq for kidneys, parotid glands and submandibular glands, respectively. Tumor doses decreased from 3.86 ± 3.38 mGy/MBq in dose cycle 1 to 2.01 ± 2.65 mGy/MBq in dose cycle 4. Compared to the full dosimetry approach the SM 1 using single TP imaging at 48 h p.i. resulted in the most accurate and precise results for the organs at risk in terms of absorbed doses per cycle and total cumulated dose. For tumor lesions better results were achieved using the fourth TP (≥ 72 h p.i.).

CONCLUSION

Simplification of safety dosimetry protocols is possible for [177Lu]Lu-PSMA-I&T therapy. If tumor dosimetry is of interest a later imaging TP (≥ 72 h p.i.) should be used/added to account for the slower kinetics of tumors compared to organs at risk.

Value of [18F]FDG PET/CT parameters of the primary tumor in assessing overall survival in NSCLC patients with cN1-cN3 lymph nodes involvement

Background

The aim of this retrospective study was to assess the value of 18F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography ([18F]FDG PET/CT parameters in cN1-cN3 non-small cell lung cancer (NSCLC) patients.

Materials and methods

59 consecutive patients (35 M, 24 F) with NSCLC who underwent pretreatment [18F]FDG PET/CT were enrolled to this study. Several primary tumor PET parameters, including the maximum and mean standardized uptake value (SUVmax and SUVmean), the metabolic active tumor volume (MTV) and the total lesion glycolysis (TLG = MTVxSUVmean), were extracted and analysed. Overall survival was defined as time from primary diagnosis to death or the last info.

Results

In the whole analysed group 44 patients underwent curative treatment, while 15, because of the severity of the disease, were classified for palliative treatment. Univariate Cox analysis of clinical and metric PET parameters revealed that MTV was a significant prognostic factor for OS (p = 0.024), while TLG and curative treatment showed a trend for significance (p < 0.1). In multivariate Cox regression (MTV and curative treatment) MTV remained a significant factor (p = 0.047).

Conclusions

Metabolic tumor volume of the primary tumor was the only independent prognostic factor for cN1-cN3 NSCLC patients.

Combination of tumor asphericity and an extracellular matrix-related prognostic gene signature in non-small cell lung cancer patients

One important aim of precision oncology is a personalized treatment of patients. This can be achieved by various biomarkers, especially imaging parameters and gene expression signatures are commonly used. So far, combination approaches are sparse. The aim of the study was to independently validate the prognostic value of the novel positron emission tomography (PET) parameter tumor asphericity (ASP) in non small cell lung cancer (NSCLC) patients and to investigate associations between published gene expression profiles and ASP. This was a retrospective evaluation of PET imaging and gene expression data from three public databases and two institutional datasets. The whole cohort comprised 253 NSCLC patients, all treated with curative intent surgery. Clinical parameters, standard PET parameters and ASP were evaluated in all patients. Additional gene expression data were available for 120 patients. Univariate Cox regression and Kaplan-Meier analysis was performed for the primary endpoint progression-free survival (PFS) and additional endpoints. Furthermore, multivariate cox regression testing was performed including clinically significant parameters, ASP, and the extracellular matrix-related prognostic gene signature (EPPI). In the whole cohort, a significant association with PFS was observed for ASP (p < 0.001) and EPPI (p = 0.012). Upon multivariate testing, EPPI remained significantly associated with PFS (p = 0.018) in the subgroup of patients with additional gene expression data, while ASP was significantly associated with PFS in the whole cohort (p = 0.012). In stage II patients, ASP was significantly associated with PFS (p = 0.009), and a previously published cutoff value for ASP (19.5%) was successfully validated (p = 0.008). In patients with additional gene expression data, EPPI showed a significant association with PFS, too (p = 0.033). The exploratory combination of ASP and EPPI showed that the combinatory approach has potential to further improve patient stratification compared to the use of only one parameter. We report the first successful validation of EPPI and ASP in stage II NSCLC patients. The combination of both parameters seems to be a very promising approach for improvement of risk stratification in a group of patients with urgent need for a more personalized treatment approach.

A convolutional neural network with self-attention for fully automated metabolic tumor volume delineation of head and neck cancer in [Formula: see text]F]FDG PET/CT

PURPOSE

PET-derived metabolic tumor volume (MTV) and total lesion glycolysis of the primary tumor are known to be prognostic of clinical outcome in head and neck cancer (HNC). Including evaluation of lymph node metastases can further increase the prognostic value of PET but accurate manual delineation and classification of all lesions is time-consuming and prone to interobserver variability. Our goal, therefore, was development and evaluation of an automated tool for MTV delineation/classification of primary tumor and lymph node metastases in PET/CT investigations of HNC patients.

METHODS

Automated lesion delineation was performed with a residual 3D U-Net convolutional neural network (CNN) incorporating a multi-head self-attention block. 698 [Formula: see text]F]FDG PET/CT scans from 3 different sites and 5 public databases were used for network training and testing. An external dataset of 181 [Formula: see text]F]FDG PET/CT scans from 2 additional sites was employed to assess the generalizability of the network. In these data, primary tumor and lymph node (LN) metastases were interactively delineated and labeled by two experienced physicians. Performance of the trained network models was assessed by 5-fold cross-validation in the main dataset and by pooling results from the 5 developed models in the external dataset. The Dice similarity coefficient (DSC) for individual delineation tasks and the primary tumor/metastasis classification accuracy were used as evaluation metrics. Additionally, a survival analysis using univariate Cox regression was performed comparing achieved group separation for manual and automated delineation, respectively.

RESULTS

In the cross-validation experiment, delineation of all malignant lesions with the trained U-Net models achieves DSC of 0.885, 0.805, and 0.870 for primary tumor, LN metastases, and the union of both, respectively. In external testing, the DSC reaches 0.850, 0.724, and 0.823 for primary tumor, LN metastases, and the union of both, respectively. The voxel classification accuracy was 98.0% and 97.9% in cross-validation and external data, respectively. Univariate Cox analysis in the cross-validation and the external testing reveals that manually and automatically derived total MTVs are both highly prognostic with respect to overall survival, yielding essentially identical hazard ratios (HR) ([Formula: see text]; [Formula: see text] vs. [Formula: see text]; [Formula: see text] in cross-validation and [Formula: see text]; [Formula: see text] vs. [Formula: see text]; [Formula: see text] in external testing).

CONCLUSION

To the best of our knowledge, this work presents the first CNN model for successful MTV delineation and lesion classification in HNC. In the vast majority of patients, the network performs satisfactory delineation and classification of primary tumor and lymph node metastases and only rarely requires more than minimal manual correction. It is thus able to massively facilitate study data evaluation in large patient groups and also does have clear potential for supervised clinical application.

18F-Fluorodeoxyglucose Positron Emission Tomography of Head and Neck Cancer: Location and HPV Specific Parameters for Potential Treatment Individualization

Purpose

18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is utilized for staging and treatment planning of head and neck squamous cell carcinomas (HNSCC). Some older publications on the prognostic relevance showed inconclusive results, most probably due to small study sizes. This study evaluates the prognostic and potentially predictive value of FDG-PET in a large multi-center analysis.

Methods

Original analysis of individual FDG-PET and patient data from 16 international centers (8 institutional datasets, 8 public repositories) with 1104 patients. All patients received curative intent radiotherapy/chemoradiation (CRT) and pre-treatment FDG-PET imaging. Primary tumors were semi-automatically delineated for calculation of SUV_max, SUV_mean, metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Cox regression analyses were performed for event-free survival (EFS), overall survival (OS), loco-regional control (LRC) and freedom from distant metastases (FFDM).

Results

FDG-PET parameters were associated with patient outcome in the whole cohort regarding clinical endpoints (EFS, OS, LRC, FFDM), in uni- and multivariate Cox regression analyses. Several previously published cut-off values were successfully validated. Subgroup analyses identified tumor- and human papillomavirus (HPV) specific parameters. In HPV positive oropharynx cancer (OPC) SUV_max was well suited to identify patients with excellent LRC for organ preservation. Patients with SUV_max of 14 or less were unlikely to develop loco-regional recurrence after definitive CRT. In contrast FDG PET parameters deliver only limited prognostic information in laryngeal cancer.

Conclusion

FDG-PET parameters bear considerable prognostic value in HNSCC and potential predictive value in subgroups of patients, especially regarding treatment de-intensification and organ-preservation. The potential predictive value needs further validation in appropriate control groups. Further research on advanced imaging approaches including radiomics or artificial intelligence methods should implement the identified cut-off values as benchmark routine imaging parameters.

Effect of Bayesian penalty likelihood algorithm on 18F-FDG PET/CT image of lymphoma

OBJECTIVE

Recently, a new Bayesian penalty likelihood (BPL) reconstruction algorithm has been applied in PET, which is expected to provide better image resolution than the widely used ordered subset expectation maximization (OSEM). The purpose of this study is to compare the differences between these two algorithms in terms of image quality and effects on clinical diagnostics and quantification of lymphoma.

METHODS

A total of 246 FDG-positive lesions in 70 patients with lymphoma were retrospectively analyzed by using BPL and OSEM + time-of-flight + point spread function algorithms. Visual analysis was used to evaluate the effects of different reconstruction algorithms on clinical image quality and diagnostic certainty. Quantitative analysis was used to compare the differences between pathology and lesion size.

RESULTS

There were significant differences in lesion-related SUVmax, total-lesion-glycolysis (TLG), and signal-to-background ratio (SBR) (P < 0.01). The variation Δ SUVmax% and Δ SBR% caused by the two reconstruction algorithms were negatively correlated with tumor diameter, while Δ MTV% and Δ TLG% were positively correlated with tumor diameter. In the grouped analysis based on pathology, there were significant differences in lesion SUVmax, lesion SUVmean, and SBR. In non-Hodgkin's lymphoma (diffuse large B cells and follicular lymphoma), diversities were significantly found in SUVmax, SUVmean, SBR, and TLG of the lesions (P < 0.05). According to the grouped analysis based on lesion size, for lesions smaller than 1 cm and 2 cm, there was a significant difference in SUVmean, SUVmax, SBR, and MTV, but not in lesions larger than or equal to 2 cm (P > 0.05), and the liver background SUVmean (P > 0.05) remained unchanged.

CONCLUSION

BPL reconstruction algorithm could effectively improve clinical image quality and diagnostic certainty. In quantitative analysis, there were no significant differences among different pathological groups, but there were significant diversities in lesion sizes. Especially for small lesions, lesion SUVmax increased and SBR was significantly improved, which may better assist in the diagnosis of small lesions of lymphoma.

Clinical Perspectives for 18F-FDG PET Imaging in Pediatric Oncology: Μetabolic Tumor Volume and Radiomics

Pediatric cancer, although rare, requires the most optimized treatment approach to obtain high survival rates and minimize serious long-term side effects in early adulthood. 18F-FDG PET/CT is most helpful and widely used in staging, recurrence detection, and response assessment in pediatric oncology. The well-known 18F-FDG PET metabolic indices of metabolic tumor volume (MTV) and tumor lesion glycolysis (TLG) have already revealed an independent significant prognostic value for survival in oncologic patients, although the corresponding cut-off values remain study-dependent and not validated for use in clinical practice. Advanced tumor “radiomic” analysis sheds new light into these indices. Numerous patterns of texture 18F-FDG uptake features can be extracted from segmented PET tumor images due to new powerful computational systems supporting complex “deep learning” algorithms. This high number of “quantitative” tumor imaging data, although not decrypted in their majority and once standardized for the different imaging systems and segmentation methods, could be used for the development of new “clinical” models for specific cancer types and, more interestingly, for specific age groups. In addition, data from novel techniques of tumor genome analysis could reveal new genes as biomarkers for prognosis and/or targeted therapies in childhood malignancies. Therefore, this ever-growing information of “radiogenomics”, in which the underlying tumor “genetic profile” could be expressed in the tumor-imaging signature of “radiomics”, possibly represents the next model for precision medicine in pediatric cancer management. This paper reviews 18F-FDG PET image segmentation methods as applied to pediatric sarcomas and lymphomas and summarizes reported findings on the values of metabolic and radiomic features in the assessment of these pediatric tumors.

Prognostic Value of Pretherapeutic Primary Tumor MTV from [18F]FDG PET in Radically Treated Cervical Cancer Patients

The aim of this study was to assess the usefulness of pretherapeutic primary tumor metabolic tumor volume (MTV) in the prognosis of radically treated cervical cancer patients. Retrospective, single-centre analysis was performed on a group of 508 cervical cancer patients. All patients underwent a pretreatment [¹⁸F]FDG PET/CT study for the assessment of the disease stage. Several PET-derived parameters—namely, maximum standardized uptake value (SUV_max), mean standardized uptake value (SUV_mean), total lesion glycolysis (TLG) and MTV, as well as the clinical parameters, were analysed in terms of the overall survival (OS), event-free survival (EFS), locoregional control (LRC) and freedom from distant metastases (FFDM). Hyperthermia and brachytherapy were prognostic for EFS, OS, and LRC.FIGO stage > II showed a significant effect on EFS, OS, and FFDM. Moreover, hysterectomy was prognostic for OS and histology was prognostic for FFDM. From the PET-derived parameters only MTV of the primary tumor had a significant influence on OS (cutoff point: >12.7 mL, HR: 2.8, 1.75–4.48 95% CI, p < 0.001), LRC (cutoff point: >13.7 mL, HR 2.82, 1.42–5.61 95% CI, p = 0.003), EFS (cutoff point: >10.4 mL, HR: 2.57, 1.67–3.97 95% CI, p < 0.001) and FFDM (cutoff point: >10.4 mL, HR: 5.04, 1.82–13.99 95% CI, p = 0.002). Pretreatment MTV from the primary tumor is the only independent prognostic parameter in OS, LRC, EFS, and FFDM in radically treated cervical cancer patients and should be used in clinical practice in assessing prognosis in these patients.

Added Value of Tomoelastography for Characterization of Pancreatic Neuroendocrine Tumor Aggressiveness Based on Stiffness

Simple Summary

The prediction of pancreatic neuroendocrine tumor (PNET) aggressiveness is important for treatment planning. The aim of this study was to evaluate the diagnostic performance of magnetic resonance elastography (MRE) with tomoelastography postprocessing (tomoelastography) in differentiating PNET from healthy pancreatic tissue and to correlate PNET stiffness with aggressiveness using asphericity derived from positron emission tomography (PET) as reference. In this prospective study we showed in a group of 13 patients with PNET that tomoelastography detected PNET by increased stiffness (p < 0.01) with a high diagnostic performance (AUC = 0.96). PNET was positively correlated with PET derived asphericity (r = 0.81). Tomoelastography provides quantitative imaging markers for the detection of PNET and the prediction of greater tumor aggressiveness by increased stiffness.

Abstract

Purpose: To evaluate the diagnostic performance of tomoelastography in differentiating pancreatic neuroendocrine tumors (PNETs) from healthy pancreatic tissue and to assess the prediction of tumor aggressiveness by correlating PNET stiffness with PET derived asphericity. Methods: 13 patients with PNET were prospectively compared to 13 age-/sex-matched heathy volunteers (CTR). Multifrequency MR elastography was combined with tomoelastography-postprocessing to provide high-resolution maps of shear wave speed (SWS in m/s). SWS of pancreatic neuroendocrine tumor (PNET-T) were compared with nontumorous pancreatic tissue in patients with PNET (PNET-NT) and heathy pancreatic tissue (CTR). The diagnostic performance of tomoelastography was evaluated by ROC-AUC analysis. PNET-SWS correlations were calculated with Pearson’s r. Results: SWS was higher in PNET-T (2.02 ± 0.61 m/s) compared to PNET-NT (1.31 ± 0.18 m/s, p < 0.01) and CTR (1.26 ± 0.09 m/s, p < 0.01). An SWS-cutoff of 1.46 m/s distinguished PNET-T from PNET-NT (AUC = 0.89; sensitivity = 0.85; specificity = 0.92) and a cutoff of 1.49 m/s differentiated pancreatic tissue of CTR from PNET-T (AUC = 0.96; sensitivity = 0.92; specificity = 1.00). The SWS of PNET-T was positively correlated with PET derived asphericity (r = 0.81; p = 0.01). Conclusions: Tomoelastography provides quantitative imaging markers for the detection of PNET and the prediction of greater tumor aggressiveness by increased stiffness.

A Multiprocessing Scheme for PET Image Pre-Screening, Noise Reduction, Segmentation and Lesion Partitioning

OBJECTIVE

Accurate segmentation and partitioning of lesions in PET images provide computer-aided procedures and doctors with parameters for tumour diagnosis, staging and prognosis. Currently, PET segmentation and lesion partitioning are manually measured by radiologists, which is time consuming and laborious, and tedious manual procedures might lead to inaccurate measurement results. Therefore, we designed a new automatic multiprocessing scheme for PET image pre-screening, noise reduction, segmentation and lesion partitioning in this study. PET image pre-screening can reduce the time cost of noise reduction, segmentation and lesion partitioning methods, and denoising can enhance both quantitative metrics and visual quality for better segmentation accuracy. For pre-screening, we propose a new differential activation filter (DAF) to screen the lesion images from whole-body scanning. For noise reduction, neural network inverse (NN inverse) as the inverse transformation of generalized Anscombe transformation (GAT), which does not depend on the distribution of residual noise, was presented to improve the SNR of images. For segmentation and lesion partitioning, definition density peak clustering (DDPC) was proposed to realize instance segmentation of lesion and normal tissue with unsupervised images, which helped reduce the cost of density calculation and completely deleted the cluster halo. The experimental results of clinical data demonstrate that our proposed methods have good results and better performance in noise reduction, segmentation and lesion partitioning compared with state-of-the-art methods.

Motion-compensated FDG PET/CT for oesophageal cancer

PURPOSE

Respiratory-induced motion of oesophageal tumours and lymph nodes can influence positron-emission tomography/computed tomography (PET/CT). The aim was to compare standard three-dimensional (3D) and motion-compensated PET/CT regarding standardized uptake value (SUV), metabolic tumour volume (MTV) and detection of lymph node metastases.

METHODS

This prospective observational study (NCT02424864) included 37 newly diagnosed oesophageal cancer patients. Diagnostic PET/CT was reconstructed in 3D and motion-compensated PET/CT. MTVs of the primary tumour were calculated using an automated region-growing algorithm with SUV thresholds of 2.5 (MTV2.5) and ≥ 50% of SUVmax (MTV50%). Blinded for reconstruction method, a nuclear medicine physician assessed all lymph nodes showing ¹⁸F‑fluorodeoxyglucose uptake for their degree of suspicion.

RESULTS

The mean (95% CI) SUVmax of the primary tumour was 13.1 (10.6-15.5) versus 13.0 (10.4-15.6) for 3D and motion-compensated PET/CT, respectively. MTVs were also similar between the two techniques. Bland-Altman analysis showed mean differences between both measurements (95% limits of agreement) of 0.08 (-3.60-3.75), -0.26 (-2.34-1.82), 4.66 (-29.61-38.92) cm³ and -0.95 (-19.9-18.0) cm³ for tumour SUVmax, lymph node SUVmax, MTV2.5 and MTV50%, respectively. Lymph nodes were classified as highly suspicious (30/34 nodes), suspicious (20/22) and dubious (66/59) for metastases on 3D/motion-compensated PET/CT. No additional lymph node metastases were found on motion-compensated PET/CT. SUVmax of the most intense lymph nodes was similar for both scans: mean (95% CI) 6.6 (4.3-8.8) and 6.8 (4.5-9.1) for 3D and motion-compensated, respectively.

CONCLUSION

SUVmax of the primary oesophageal tumour and lymph nodes was comparable on 3D and motion-compensated PET/CT. The use of motion-compensated PET/CT did not improve lymph node detection.

PET measured hypoxia and MRI parameters in re-irradiated head and neck squamous cell carcinomas: findings of a prospective pilot study

Background: Tumor hypoxia measured by dedicated tracers like [ ¹⁸F]fluoromisonidazole (FMISO) is a well-established prognostic factor in head and neck squamous cell carcinomas (HNSCC) treated with definitive chemoradiation (CRT). However, prevalence and characteristics of positron emission tomography (PET) measured hypoxia in patients with relapse after previous irradiation is missing. Here we report imaging findings of a prospective pilot study in HNSCC patients treated with re-irradiation.

Methods: In 8 patients with recurrent HNSCC, diagnosed at a median of 18 months after initial radiotherapy/CRT, [ ¹⁸F]fluorodeoxyglucose (FDG)-PET/CT (n=8) and FMISO-PET/MRI (n=7) or FMISO-PET/CT (n=1) were performed. Static FMISO-PET was performed after 180 min. MRI sequences in PET/MRI included diffusion-weighted imaging with apparent diffusion coefficient (ADC) values and contrast enhanced T1w imaging (StarVIBE). Lesions (primary tumor recurrence, 4; cervical lymph node, 1; both, 3) were delineated on FDG-PET and FMISO-PET data using a background-adapted threshold-based method. SUV _max and SUV _mean in FDG- and FMISO-PET were derived, as well as maximum tumor-to-muscle ratio (TMR _max) and hypoxic volume with 1.6-fold muscle SUV _mean (HV _1.6) in FMISO-PET. Intensity of lesional contrast enhancement was rated relative to contralateral normal tissue. Average ADC values were derived from a 2D region of interest in the tumor.

Results: In FMISO-PET, median TMR _max was 1.7 (range: 1.1-1.8). Median HV _1.6 was 0.05 ml (range: 0-7.3 ml). Only in 2/8 patients, HV _1.6 was ≥1.0 ml. In FDG-PET, median SUV _max was 9.3 (range: 5.0-20.1). On contrast enhanced imaging four lesions showed decreased and four lesions increased contrast enhancement compared to non-pathologic reference tissue. Median average ADC was 1,060 ×10 ⁶ mm ²/s (range: 840-1,400 ×10 ⁶ mm ²/s).

Conclusions: This pilot study implies that hypoxia detectable by FMISO-PET may not be as prevalent as expected among loco-regional recurrent, HPV negative HNSCC. ADC values were only mildly reduced, and contrast enhancement was variable. The results require confirmation in larger sample sizes.

Asphericity of tumor FDG uptake in non-small cell lung cancer: reproducibility and implications for harmonization in multicenter studies

Background

Asphericity (ASP) of the primary tumor’s metabolic tumor volume (MTV) in FDG-PET/CT is independently predictive for survival in patients with non-small cell lung cancer (NSCLC). However, comparability between PET systems may be limited. Therefore, reproducibility of ASP was evaluated at varying image reconstruction and acquisition times to assess feasibility of ASP assessment in multicenter studies.

Methods

This is a retrospective study of 50 patients with NSCLC (female 20; median age 69 years) undergoing pretherapeutic FDG-PET/CT (median 3.7 MBq/kg; 180 s/bed position). Reconstruction used OSEM with TOF_4/16 (iterations 4; subsets 16; in-plane filter 2.0, 6.4 or 9.5 mm), TOF_4/8 (4 it; 8 ss; filter 2.0/6.0/9.5 mm), PSF + TOF_2/17 (2 it; 17 ss; filter 2.0/7.0/10.0 mm) or Bayesian-penalized likelihood (Q.Clear; beta, 600/1750/4000). Resulting reconstructed spatial resolution (FWHM) was determined from hot sphere inserts of a NEMA IEC phantom. Data with approx. 5-mm FWHM were retrospectively smoothed to achieve 7-mm FWHM. List mode data were rebinned for acquisition times of 120/90/60 s. Threshold-based delineation of primary tumor MTV was followed by evaluation of relative ASP/SUVmax/MTV differences between datasets and resulting proportions of discordantly classified cases.

Results

Reconstructed resolution for narrow/medium/wide in-plane filter (or low/medium/high beta) was approx. 5/7/9 mm FWHM. Comparing different pairs of reconstructed resolution between TOF_4/8, PSF + TOF_2/17, Q.Clear and the reference algorithm TOF_4/16, ASP differences was lowest at FWHM of 7 versus 7 mm. Proportions of discordant cases (ASP > 19.5% vs. ≤ 19.5%) were also lowest at 7 mm (TOF_4/8, 2%; PSF + TOF_2/17, 4%; Q.Clear, 10%). Smoothing of 5-mm data to 7-mm FWHM significantly reduced discordant cases (TOF_4/8, 38% reduced to 2%; PSF + TOF_2/17, 12% to 4%; Q.Clear, 10% to 6%), resulting in proportions comparable to original 7-mm data. Shorter acquisition time only increased proportions of discordant cases at < 90 s.

Conclusions

ASP differences were mainly determined by reconstructed spatial resolution, and multicenter studies should aim at comparable FWHM (e.g., 7 mm; determined by in-plane filter width). This reduces discordant cases (high vs. low ASP) to an acceptable proportion for TOF and PSF + TOF of < 5% (Q.Clear: 10%). Data with better resolution (i.e., lower FWHM) could be retrospectively smoothed to the desired FWHM, resulting in a comparable number of discordant cases.

Circulating Tumor DNA Allows Early Treatment Monitoring in BRAF- and NRAS-Mutant Malignant Melanoma

PURPOSE

We evaluated circulating tumor DNA (ctDNA) for detecting tumor burden in melanoma and examined whether early changes in the number of ctDNA copies predict response to treatment.

PATIENTS AND METHODS

We included 12 patients with stage III and 50 patients with stage IV melanoma with BRAF exon 15 or NRAS exon 3 mutations in tumor tissue. We used droplet digital polymerase chain reaction to retrospectively analyze serial plasma samples for mutation-positive ctDNA.

RESULTS

Matched plasma and serum samples were positive for ctDNA, lactate dehydrogenase, and S100 in 113 (45.8%), 108 (43.7%; not significant), and 58 (23.5%; P < .0001) of 247 samples from 50 patients with stage IV melanoma, and in 17 (63%), eight (29.6%; P = .014), and five (18.5%; P < .0001) of 27 samples from 12 patients with stage III melanoma. The number of mutant ctDNA copies correlated with concentrations of lactate dehydrogenase (r = 0.50) and S100 (r = 0.64), tumor volume (r² = 0.58), and tumor metabolic activity (r² = 0.83). Within 30 days before surgery, initiation of treatment, or change in treatment, ctDNA, LDH, and S100 were positive in 76.8%, 53.6% (P = .01), and 46.4% (P < .001) of patients, respectively. In patients with stage III or IV melanoma, early changes in ctDNA within 1 month after initiation of treatment correctly predicted RECIST response categories in 19 of 20 patients. Detectable ctDNA within 30 days after surgery or initiation of systemic treatment predicted inferior progression-free survival in patients with stage III disease (P = .018). In patients with stage IV disease, 10 or more copies of ctDNA per mL at first follow-up indicated shorter progression-free survival (3.8 v 9 months; hazard ratio, 4.05; 95% CI, 1.56 to 10.53).

CONCLUSION

ctDNA indicated active tumor and was an adverse prognostic marker for tumor progression. Dynamic changes in ctDNA allowed prediction of response early after initiation of treatment. These data support the use of ctDNA to guide treatment in melanoma.

A FDG-PET radiomics signature detects esophageal squamous cell carcinoma patients who do not benefit from chemoradiation

Detection of patients with esophageal squamous cell carcinoma (ESCC) who do not benefit from standard chemoradiation (CRT) is an important medical need. Radiomics using 18-fluorodeoxyglucose (FDG) positron emission tomography (PET) is a promising approach. In this retrospective study of 184 patients with locally advanced ESCC. 152 patients from one center were grouped into a training cohort (n = 100) and an internal validation cohort (n = 52). External validation was performed with 32 patients treated at a second center. Primary endpoint was disease-free survival (DFS), secondary endpoints were overall survival (OS) and local control (LC). FDG-PET radiomics features were selected by Lasso-Cox regression analyses and a separate radiomics signature was calculated for each endpoint. In the training cohort radiomics signatures containing up to four PET derived features were able to identify non-responders in regard of all endpoints (DFS p < 0.001, LC p = 0.003, OS p = 0.001). After successful internal validation of the cutoff values generated by the training cohort for DFS (p = 0.025) and OS (p = 0.002), external validation using these cutoffs was successful for DFS (p = 0.002) but not for the other investigated endpoints. These results suggest that pre-treatment FDG-PET features may be useful to detect patients who do not respond to CRT and could benefit from alternative treatment.

Asphericity of Somatostatin Receptor Expression in Neuroendocrine Tumors: An Innovative Predictor of Outcome in Everolimus Treatment?

Background: in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NET), the mTOR inhibitor everolimus is associated with significant improvement in progression-free survival (PFS). This study evaluated the lesional asphericity (ASP) in pretherapeutic somatostatin receptor (SSR) imaging as the first imaging-based prognostic marker for PFS. Methods: this retrospective bicentric cohort study included 30 patients (f = 13, median age, 66.5 (48–81) years) with pretherapeutic [¹¹¹In-DTPA⁰]octreotide scintigraphy (Octreoscan^®). ASP of functional volumes of up to three leading lesions per patient (n = 74) was calculated after semiautomatic, background-adapted segmentation. Uni- and multivariable Cox regression regarding PFS for clinical factors and the maximum ASP per patient was obtained. Results: all 30 patients showed metachronous or progressive liver metastases. ASP, primary tumor site, metastases pattern, and prior peptide receptor radionuclide therapy (PRRT) were significantly associated with PFS in univariable Cox regression. Only ASP > 12.9% (hazard ratio (HR), 3.33; p = 0.024) and prior PRRT (HR, 0.35; p = 0.043) remained significant in multivariable Cox. Median PFS was 6.7 months for ASP > 12.9% (95% confidence interval (CI), 2.1–11.4 months) versus 14.4 (12.5–16.3) months for ASP ≤ 12.9% (log-rank, p = 0.028). Conclusion: pretherapeutic ASP of SSR positive lesions independently predicted PFS for treatment with everolimus in GEP-NET. ASP may supplement risk-benefit assessment before patient inclusion to treatment.

Prognostic value of baseline [18F]-fluorodeoxyglucose positron emission tomography parameters MTV, TLG and asphericity in an international multicenter cohort of nasopharyngeal carcinoma patients

Purpose

[¹⁸F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) parameters have shown prognostic value in nasopharyngeal carcinomas (NPC), mostly in monocenter studies. The aim of this study was to assess the prognostic impact of standard and novel PET parameters in a multicenter cohort of patients.

Methods

The established PET parameters metabolic tumor volume (MTV), total lesion glycolysis (TLG) and maximal standardized uptake value (SUV_max) as well as the novel parameter tumor asphericity (ASP) were evaluated in a retrospective multicenter cohort of 114 NPC patients with FDG-PET staging, treated with (chemo)radiation at 8 international institutions. Uni- and multivariable Cox regression and Kaplan-Meier analysis with respect to overall survival (OS), event-free survival (EFS), distant metastases-free survival (FFDM), and locoregional control (LRC) was performed for clinical and PET parameters.

Results

When analyzing metric PET parameters, ASP showed a significant association with EFS (p = 0.035) and a trend for OS (p = 0.058). MTV was significantly associated with EFS (p = 0.026), OS (p = 0.008) and LRC (p = 0.012) and TLG with LRC (p = 0.019). TLG and MTV showed a very high correlation (Spearman’s rho = 0.95), therefore TLG was subesequently not further analysed. Optimal cutoff values for defining high and low risk groups were determined by maximization of the p-value in univariate Cox regression considering all possible cutoff values. Generation of stable cutoff values was feasible for MTV (p<0.001), ASP (p = 0.023) and combination of both (MTV+ASP = occurrence of one or both risk factors, p<0.001) for OS and for MTV regarding the endpoints OS (p<0.001) and LRC (p<0.001). In multivariable Cox (age >55 years + one binarized PET parameter), MTV >11.1ml (hazard ratio (HR): 3.57, p<0.001) and ASP > 14.4% (HR: 3.2, p = 0.031) remained prognostic for OS. MTV additionally remained prognostic for LRC (HR: 4.86 p<0.001) and EFS (HR: 2.51 p = 0.004). Bootstrapping analyses showed that a combination of high MTV and ASP improved prognostic value for OS compared to each single variable significantly (p = 0.005 and p = 0.04, respectively). When using the cohort from China (n = 57 patients) for establishment of prognostic parameters and all other patients for validation (n = 57 patients), MTV could be successfully validated as prognostic parameter regarding OS, EFS and LRC (all p-values <0.05 for both cohorts).

Conclusions

In this analysis, PET parameters were associated with outcome of NPC patients. MTV showed a robust association with OS, EFS and LRC. Our data suggest that combination of MTV and ASP may potentially further improve the risk stratification of NPC patients.

Individual patient data meta-analysis of FMISO and FAZA hypoxia PET scans from head and neck cancer patients undergoing definitive radio-chemotherapy

BACKGROUND AND PURPOSE

Tumor hypoxia plays an important role in head and neck squamous cell carcinomas (HNSCC). Various positron emission tomography (PET) tracers promise non-invasive assessment of tumor hypoxia. So far, the applicability of hypoxia PET is hampered by monocentric imaging trials with few patients.

MATERIALS AND METHODS

Multicenter individual patient data based meta-analysis of the original PET data from four prospective imaging trials was performed. All patients had localized disease and were treated with curatively intended radio(-chemo)therapy. Hypoxia PET imaging was performed with ¹⁸F-Fluoromisonidazole (FMISO, 102 patients) or ¹⁸F-Fluoroazomycin-arabinoside (FAZA, 51 patients). Impact of hypoxia PET parameters on loco-regional control (LRC) and overall survival (OS) was analyzed by uni- and multivariable Cox regression.

RESULTS

Baseline characteristics between participating centers differed significantly, especially regarding T stage (p < 0.001), tumor volume (p < 0.001) and p16 status (p = 0.009). The commonly used hypoxia parameters, maximal tumor-to-muscle ratio (TMR_max) and hypoxic volume with 1.6 threshold (HV_1.6), showed a strong association with LRC (p = 0.001) and OS (p < 0.001). These findings were irrespective of the radiotracer and the same cut-off values could be applied for FMISO and FAZA (TMR_max > 2.0 or HV_1.6 > 1.5 ml). The effect size of TMR_max was similar for subgroups of patients defined by radiotracer, p16 status and FDG-PET parameters for LRC and OS, respectively.

CONCLUSION

PET measured hypoxia is robust and has a strong impact on LRC and OS in HNSCC. The most commonly investigated tracers FMISO and FAZA can probably be used equivalently in multicenter trials. Optimal strategies to improve the dismal outcome of hypoxic tumors remain elusive.

Use of Baseline 18 F-FDG PET/CT to Identify Initial Sub-Volumes Associated With Local Failure After Concomitant Chemoradiotherapy in Locally Advanced Cervical Cancer

Introduction: Locally advanced cervical cancer (CC) patients treated by chemoradiotherapy (CRT) have a significant local recurrence rate. The objective of this work was to assess the overlap between the initial high-uptake sub-volume (V1) on baseline 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) scans and the metabolic relapse (V2) sites after CRT in locally advanced CC. Methods: PET/CT performed before treatment and at relapse in 21 patients diagnosed with LACC and treated with CRT were retrospectively analyzed. CT images at the time of recurrence were registered to baseline CT using the 3D Slicer TM Expert Automated Registration module. The corresponding PET images were then registered using the corresponding transform. The fuzzy locally adaptive Bayesian (FLAB) algorithm was implemented using 3 classes (one for the background and the other two for tumor) in PET1 to simultaneously define an overall tumor volume and the sub-volume V1. In PET2, FLAB was implemented using 2 classes (one for background, one for tumor), in order to define V2. Four indices were used to determine the overlap between V1 and V2 (Dice coefficients, overlap fraction, X = (V1nV2)/V1 and Y = (V1nV2)/V2). Results: The mean (±standard deviation) follow-up was 26 ± 11 months. The measured overlaps between V1 and V2 were moderate to good according to the four metrics, with 0.62-0.81 (0.72 ± 0.05), 0.72-1.00 (0.85 ± 0.10), 0.55-1.00 (0.73 ± 0.16) and 0.50-1.00 (0.76 ± 0.12) for Dice, overlap fraction, X and Y, respectively. Conclusion: In our study, the overlaps between the initial high-uptake sub-volume and the recurrent metabolic volume showed moderate to good concordance. These results now need to be confirmed in a larger cohort using a more standardized patient repositioning procedure for sequential PET/CT imaging, as there is potential for RT dose escalation exploiting the pre-treatment PET high-uptake sub-volume.

Transcriptomics in cancer revealed by Positron Emission Tomography radiomics

Metabolic images from Positron Emission Tomography (PET) are used routinely for diagnosis, follow-up or treatment planning purposes of cancer patients. In this study we aimed at determining if radiomic features extracted from 18F-Fluoro Deoxy Glucose (FDG) PET images could mirror tumor transcriptomics. In this study we analyzed 45 patients with locally advanced head and neck cancer (H&N) that underwent FDG-PET scans at the time of diagnosis and transcriptome analysis using RNAs from both cancer and healthy tissues on microarrays. Association between PET radiomics and transcriptomics was carried out with the Genomica software and a functional annotation was used to associate PET radiomics, gene expression and altered biological pathways. We identified relationships between PET radiomics and genes involved in cell-cycle, disease, DNA repair, extracellular matrix organization, immune system, metabolism or signal transduction pathways, according to the Reactome classification. Our results suggest that these FDG PET radiomic features could be used to infer tissue gene expression and cellular pathway activity in H&N cancers. These observations strengthen the value of radiomics as a promising approach to personalize treatments through targeting tumor-specific molecular processes.

Combined tumor plus nontumor interim FDG-PET parameters are prognostic for response to chemoradiation in squamous cell esophageal cancer

We have investigated the prognostic value of two novel interim ¹⁸ F-fluorodeoxyglucose positron emission tomography (FDG-PET) parameters in patients undergoing chemoradiation (CRT) for esophageal squamous cell carcinoma (ESCC): one tumor parameter (maximal standardized uptake ratio rSUR) and one normal tissue parameter (change of FDG uptake within irradiated nontumor-affected esophagus ∆SUV_NTO ). PET data of 134 European and Chinese patients were analyzed. Parameter establishment was based on 36 patients undergoing preoperative CRT plus surgery, validation was performed in 98 patients receiving definitive CRT. Patients received PET imaging prior and during fourth week of CRT. Clinical parameters, baseline PET parameters, and interim PET parameters (rSUR and ∆SUV_NTO ) were analyzed and compared to event-free survival (EFS), overall survival (OS), loco-regional control (LRC) and freedom from distant metastases (FFDM). Combining rSUR and ∆SUV_NTO revealed a strong prognostic impact on EFS, OS, LRC and FFDM in patients undergoing preoperative CRT. In the definitive CRT cohort, univariate analysis with respect to EFS revealed several staging plus both previously established interim PET parameters as significant prognostic factors. Multivariate analyses revealed only rSUR and ∆SUV_NTO as independent prognostic factors (p = 0.003, p = 0.008). Combination of these parameters with the cutoff established in preoperative CRT revealed excellent discrimination of patients with a long or short EFS (73% vs. 17% at 2 years, respectively) and significantly discriminated all other endpoints (OS, p < 0.001; LRC, p < 0.001; FFDM, p = 0.02), even in subgroups. Combined use of interim FDG-PET derived parameters ∆SUV_NTO and rSUR seems to have predictive potential, allowing to select responders for definitive CRT and omission of surgery.

Revisiting the identification of tumor sub-volumes predictive of residual uptake after (chemo)radiotherapy: influence of segmentation methods on 18F-FDG PET/CT images

Our aim was to evaluate the impact of the accuracy of image segmentation techniques on establishing an overlap between pre-treatment and post-treatment functional tumour volumes in 18FDG-PET/CT imaging. Simulated images and a clinical cohort were considered. Three different configurations (large, small or non-existent overlap) of a single simulated example was used to elucidate the behaviour of each approach. Fifty-four oesophageal and head and neck (H&N) cancer patients treated with radiochemotherapy with both pre- and post-treatment PET/CT scans were retrospectively analysed. Images were registered and volumes were determined using combinations of thresholds and the fuzzy locally adaptive Bayesian (FLAB) algorithm. Four overlap metrics were calculated. The simulations showed that thresholds lead to biased overlap estimation and that accurate metrics are obtained despite spatially inaccurate volumes. In the clinical dataset, only 17 patients exhibited residual uptake smaller than the pre-treatment volume. Overlaps obtained with FLAB were consistently moderate for esophageal and low for H&N cases across all metrics. Overlaps obtained using threshold combinations varied greatly depending on thresholds and metrics. In both cases overlaps were variable across patients. Our findings do not support optimisation of radiotherapy planning based on pre-treatment 18FDG-PET/CT image definition of high-uptake sub-volumes. Combinations of thresholds may have led to overestimation of overlaps in previous studies.

Validation of Independent Prognostic Value of Asphericity of 18F-Fluorodeoxyglucose Uptake in Non-Small-Cell Lung Cancer Patients Undergoing Treatment With Curative Intent

BACKGROUND

In patients with non-small-cell lung cancer (NSCLC), asphericity (ASP) of the primary tumor's metabolic tumor volume (MTV) has shown prognostic significance. This study aimed at validation in an independent and sufficiently large cohort.

PATIENTS AND METHODS

A retrospective study was performed of 311 NSCLC patients undergoing ¹⁸F-fluorodeoxyglucose positron emission tomography / computed tomography (¹⁸F-FDG PET/CT) before curatively intended treatment (always including surgery). A total of 140 patients had International Union Against Cancer (UICC) stage I disease, 78 had stage II disease, and 93 had stage III disease (adenocarcinoma, n = 153; squamous-cell carcinoma, n = 141). Primary tumor MTV was delineated with semiautomated background-adapted threshold relative to the standardized maximum uptake value (SUV_max). Cox regression (progression-free survival [PFS] and overall survival [OS]) analysis for positron emission tomography (MTV, ASP, SUV_max) as well as for clinical (T/N descriptor, UICC stages), histologic, and treatment variables (Rx/1 vs. R0 resection, chemotherapy/radiotherapy yes/no) were performed.

RESULTS

Events (progression and relapse) occurred in 167 of 311 patients; 137 died (median survivor follow-up, 37 months). In multivariable Cox regression for OS, ASP > 33.3% (hazard ratio, 1.58 [1.04-2.39]), male sex (1.84), age (1.04 per year), Eastern Cooperative Oncology Group performance status ≥ 2 versus 0/1 (2.68), stage II versus I (1.96), and Rx/1 versus R0 resection (2.1) were significant. Among separate UICC stages, ASP only predicted OS in stage II (optimal, > 19.5%; median OS, 33 vs. 59 months). Regarding PFS, ASP > 21.2%, male sex, Eastern Cooperative Oncology Group performance status ≥ 2, stage II versus I disease, and Rx/1 resection were prognostic. ASP remained prognostic for stage II disease (optimal, > 19.5%; PFS, 12 vs. 47 months). Log-rank test for ASP was significant at any cutoff ≥ 18% (OS) or from 9% to 59% (PFS).

CONCLUSION

ASP was validated as prognostic factor for PFS and OS in patients with NSCLC and curative treatment intent, especially stage II. High ASP in stage II could imply intensified treatment or intensified follow-up.

Simultaneous respiratory motion correction and image reconstruction in 4D-multi pinhole small animal SPECT

PURPOSE

Respiratory motion in the chest region during single photon emission computed tomography (SPECT) is a major degrading factor that reduces the accuracy of image quantification. This effect is more notable when the tumor is very small, or the spatial resolution of the imaging system is less than the respiratory motion amplitude. Small animals imaging systems with sub-millimeter spatial resolution need more attention to the respiratory motion for quantitative studies. We developed a motion-embedded four-dimensional (4D)-multi pinhole SPECT (MPS) reconstruction algorithm for respiratory motion correction. This algorithm makes full use of projection statistics for reconstruction of every individual frame.

METHODS

The ROBY phantom with small tumors in liver was generated in eight different phases during one respiratory cycle. The MPS projections were modeled using a fast ray tracing method simulating an MPS acquisition. Individual frames were reconstructed and used for motion estimation. The Demons non-rigid registration algorithm was used to calculate deformation vector fields (DVFs) for simultaneous motion correction and image reconstruction. A motion-embedded 4D-MPS method was used to reconstruct images using all the projections and corresponding DVFs, simultaneously. The 4D-MPS reconstructed images were compared to the low-count single frame (LCSF) reconstructed image, the three-dimensional (3D)-MPS images reconstructed using individual frames, and post reconstruction registration (PRR) that aligns all individual phases to a reference frame using Demons-derived DVFs. The tumor volume relative error (TVE), tumor contrast relative error (TCE), and dice index (DI) for 2, 3, and 4 mm liver were calculated and compared for different reconstruction methods.

RESULTS

For the 4D-MPS reconstruction method, TVE was reduced and DI was higher compared to PRR, 3D-MPS, and LCSF. The extent of the improvement was higher for the small tumor size (i.e. 2 mm). For the biggest tumor in contrast 3 (i.e. 4 mm) TVE for 4D-MPS, PRR, 3D-MPS and, LCSF were 1.33%, 8%, 8%, and 14.67%, respectively.

CONCLUSIONS

The results suggest that motion-embedded 4D-MPS method is an effective and practical way for respiratory motion correction. It reconstructs high quality gated frames while using all projection data to reconstruct each frame.

The association of intra-therapeutic heterogeneity of somatostatin receptor expression with morphological treatment response in patients undergoing PRRT with [177Lu]-DOTATATE

Aim

Purpose of this study was to evaluate the association of the spatial heterogeneity (asphericity, ASP) in intra-therapeutic SPECT/ CT imaging of somatostatin receptor (SSR) positive metastatic gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) for morphological treatment response to peptide receptor radionuclide therapy (PRRT). Secondly, we correlated ASP derived form a pre-therapeutic OctreoScan (ASP_[In]) and an intra-therapeutic [¹⁷⁷Lu]-SPECT/CT (ASP_[Lu]).

Materials and methods

Data from first therapy cycle [¹⁷⁷Lu-DOTA⁰-Tyr³]octreotate ([¹⁷⁷Lu]-DOTATATE)-PRRT was retrospectively analyzed in 33 patients (m = 20; w = 13; median age, 72 [46–88] years). The evaluation of response to PRRT was performed according to RECIST 1.1 in responding lesions [RL (SD, PR, CR), n = 104] and non-responding lesions [NRL (PD), n = 27]. The association of SSR tumor heterogeneity with morphological response was evaluated by Kruskal-Wallis test and receiver operating characteristic curve (ROC). The optimal threshold for separation (RL vs. NRL) was calculated using the Youden-index. Relationship between pre- and intra-therapeutic ASP was determined with Spearman’s rank correlation coefficient (ρ) and Bland-Altman plots.

Results

A total of 131 lesions (liver: n = 59, lymph nodes: n = 48, bone: n = 19, pancreas: n = 5) were analyzed. Lesions with higher ASP values showed a significantly poorer response to PRRT (PD, median: 11.3, IQR: 8.5–15.5; SD, median: 3.4, IQR: 2.1–4.5; PR, median 1.7, IQR: 0.9–2.8; CR, median: 0.5, IQR: 0.0–1.3); Kruskal-Wallis, p<0.001). ROC analyses revealed a significant separation between RL and NRL for ASP after 4 months (AUC 0.85, p<0.001) and after 12 months (AUC 0.94, p<0.001). The optimal threshold for ASP was >5.45% (sensitivity 96% and specificity 82%). The correlation coefficient of pre- and intra-therapeutic ASP revealed ρ = 0.72 (p <0.01). The mean absolute difference between ASP_[In] and ASP_[Lu] was -0.04 (95% Limits of Agreement, -6.1–6.0).

Conclusion

Pre- and intra-therapeutic ASP shows a strong correlation and might be an useful tool for therapy monitoring.

Confirmation of the prognostic value of pretherapeutic tumor SUR and MTV in patients with esophageal squamous cell carcinoma

PURPOSE

The prognosis for patients with inoperable esophageal carcinoma is still poor and the reliability of individual therapy outcome prediction based on clinical parameters is not convincing. In a recent publication, we were able to show that PET can provide independent prognostic information in such a patient group and that the tumor-to-blood standard uptake ratio (SUR) can improve the prognostic value of tracer uptake values. The present investigation addresses the question of whether the distinctly improved prognostic value of SUR can be confirmed in a similar patient group that was examined and treated at a different site.

METHODS

¹⁸F-FDG PET/CT was performed in 147 consecutive patients (115 male, 32 female, mean age: 62 years) with newly diagnosed esophageal squamous cell carcinoma prior to definitive radiochemotherapy. In the PET images, the metabolic active volume (MTV) of the primary tumor was delineated with an adaptive threshold method. For the resulting ROIs, SUV_max and total lesion glycolysis (TLG = MTV × SUV_mean) were computed. The blood SUV was determined by manually delineating the aorta in the low-dose CT. SUR values were computed as ratio of tumor SUV and blood SUV. Univariate Cox regression and Kaplan-Meier analysis with respect to overall survival (OS), distant-metastases-free survival (DM), and locoregional control (LRC) was performed. Additionally, a multivariate Cox regression including clinically relevant parameters was performed.

RESULTS

Univariate Cox regression revealed MTV, TLG, and SUR_max as significant prognostic factors for OS. MTV as well as TLG were significant prognostic factors for LRC while SUR_max showed only a trend for significance. None of the PET parameters was prognostic for DM. In univariate analysis, SUV_max was not prognostic for any of the investigated clinical endpoints. In multivariate analysis (T-stage, N-stage, MTV, and SUR_max), MTV was an independent prognostic factor for OS and showed a trend for significance for LRC. SUR_max was not an independent predictor for OS or LRC. When including the PET parameters separately in multivariate analysis, MTV as well as SUR_max were prognostic factors for OS indicating that SUR_max is independent from the clinical parameters but not from MTV. In addition, MTV was an independent prognostic factor for LRC in this separate analysis.

CONCLUSIONS

Our study revealed a clearly improved prognostic value of tumor SUR compared to tumor SUV and confirms our previously published findings regarding OS. Furthermore, SUR delivers prognostic information beyond that provided by the clinical parameters alone, but does not add prognostic information beyond that provided by MTV in this patient group. Therefore, our results suggest that pretherapeutic MTV is the parameter of choice for PET-based risk stratification in the considered setting but further investigations are necessary to demonstrate that this suggestion is correct.

Prognostic value of SUR in patients with trimodality treatment of locally advanced esophageal carcinoma

The prognosis of patients with esophageal carcinoma remains dismal despite ongoing efforts to improve treatment options. For locally advanced tumors, several randomized trials have shown the benefit of neoadjuvant chemoradiation followed by surgery compared to surgery alone. The aim of this exploratory study was to evaluate the prognostic value of different baseline positron emission tomography (PET) parameters and their potentially additional prognostic impact at the end of neoadjuvant radiochemotherapy. Furthermore, the standard uptake ratio (SUR) as a new parameter for quantification of tumor metabolism was compared to the conventional PET parameters metabolic active volume (MTV), total lesion glycolysis (TLG), and standardized uptake value (SUV) taking into account known basic parameters. Methods:18F-FDG-PET/CT was performed in 76 consecutive patients ((60±10) years, 71 males) with newly diagnosed esophageal cancer before and during the last week of neoadjuvant radiochemotherapy. MTV of the primary tumor was delineated with an adaptive threshold method. The blood SUV was determined by manually delineating the aorta in the low dose CT. SUR values were computed as scan time corrected ratio of tumor SUVmax and mean blood SUV. Univariate Cox regression and Kaplan-Meier analysis with respect to locoregional control (LRC), freedom from distant metastases (FFDM), and overall survival (OS) was performed. Additionally, independence of PET parameters from standard clinical factors was analyzed with multivariate Cox regression. Results: In multivariate analysis two parameters showed a significant correlation with all endpoints: restaging MTV and restaging SUR. Furthermore, restaging TLG was prognostic for LCR and FFDM. For all endpoints the largest effect size was found for restaging SUR. The only basic factors remaining significant in multivariate analyses were histology for OS and FFDM and age for LRC. Conclusion: PET provides independent prognostic information for OS, LRC, and FFDM in addition to standard clinical parameters in this patient cohort. Our results suggest that the prognostic value of tracer uptake can be improved when characterized by SUR rather than by SUV. Overall, our investigation revealed a higher prognostic value of restaging parameters compared to baseline PET; therapy-adjustments would still be possible at this point of time. Further investigations are required to confirm these hypothesis-generating results.

Textural features of cervical cancers on FDG-PET/CT associate with survival and local relapse in patients treated with definitive chemoradiotherapy

We retrospectively reviewed the records of 142 patients with stage IB–IIIB cervical cancer who underwent ¹⁸F-FDG-PET/CT before external beam radiotherapy plus intracavitary brachytherapy and concurrent chemotherapy. The patients were divided into training and validation cohorts to confirm the reliability of predictors for recurrence. Kaplan–Meier analysis was performed and a Cox regression model was used to examine the effects of variables on overall survival (OS), progression-free survival (PFS), distant metastasis-free survival (DMFS), and pelvic relapse-free survival (PRFS). High gray-level run emphasis (HGRE) derived from gray-level run-length matrix most accurately and consistently predicted the presence of pelvic residual or recurrent tumors for both cohorts. In multivariate analysis, stages IIIA–IIIB (P = 0.001, hazard ratio [HR] = 4.07) and a low HGRE (P < 0.0001, HR = 4.34) were prognostic factors for low OS, whereas a low HGRE (P = 0.001, HR = 2.86) and nonsquamous cell histology (P = 0.003, HR = 2.76) were prognostic factors for inferior PFS. The nonsquamous cell histology (P < 0.0001, HR = 9.19) and a low HGRE (P = 0.001, HR = 4.69) were predictors for low PRFS. In cervical cancer patients receiving definitive chemoradiotherapy, pretreatment textural features on ¹⁸F-FDG-PET/CT can supplement the prognostic information.

Pretherapeutic FDG-PET total metabolic tumor volume predicts response to induction therapy in pediatric Hodgkin's lymphoma

Background

Standardized treatment in pediatric patients with Hodgkin’s lymphoma (HL) follows risk stratification by tumor stage, erythrocyte sedimentation rate and tumor bulk. We aimed to identify quantitative parameters from pretherapeutic FDG-PET to assist prediction of response to induction chemotherapy.

Methods

Retrospective analysis in 50 children with HL (f:18; m:32; median age, 14.8 [4–18] a) consecutively treated according to EuroNet-PHL-C1 (n = 42) or -C2 treatment protocol (n = 8). Total metabolic tumor volume (MTV) in pretherapeutic FDG-PET was defined using a semi-automated, background-adapted threshold. Metabolic (SUVmax, SUVmean, SUVpeak, total lesion glycolysis [MTV*SUVmean]) and heterogeneity parameters (asphericity [ASP], entropy, contrast, local homogeneity, energy, and cumulative SUV-volume histograms) were derived. Early response assessment (ERA) was performed after 2 cycles of induction chemotherapy according to treatment protocol and verified by reference rating. Prediction of inadequate response (IR) in ERA was based on ROC analysis separated by stage I/II (1 and 26 patients) and stage III/IV disease (7 and 16 patients) or treatment group/level (TG/TL) 1 to 3.

Results

IR was seen in 28/50 patients (TG/TL 1, 6/12 patients; TG/TL 2, 10/17; TG/TL 3, 12/21). Among all PET parameters, MTV best predicted IR; ASP was the best heterogeneity parameter. AUC of MTV was 0.84 (95%-confidence interval, 0.69–0.99) in stage I/II and 0.86 (0.7–1.0) in stage III/IV. In patients of TG/TL 1, AUC of MTV was 0.92 (0.74–1.0); in TG/TL 2 0.71 (0.44–0.99), and in TG/TL 3 0.85 (0.69–1.0). Patients with high vs. low MTV had IR in 86 vs. 0% in TG/TL 1, 80 vs. 29% in TG/TL 2, and 90 vs. 27% in TG/TL 3 (cut-off, > 80 ml, > 160 ml, > 410 ml).

Conclusions

In this explorative study, high total MTV best predicted inadequate response to induction therapy in pediatric HL of all pretherapeutic FDG-PET parameters – in both low and high stages as well as the 3 different TG/TL.

Trial registration

Ethics committee number: EA2/151/16 (retrospectively registered).

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4432-4) contains supplementary material, which is available to authorized users.

Increased evidence for the prognostic value of FDG uptake on late-treatment PET in non-tumour-affected oesophagus in irradiated patients with oesophageal carcinoma

PURPOSE

¹⁸F-FDG uptake in irradiated non-tumour-affected oesophagus (NTO) on restaging PET is a potential surrogate for the measurement of radiation-induced inflammation. Radiation-induced inflammation itself has been shown to be of high prognostic relevance in patients undergoing preoperative radiochemotherapy (RCT) for locally advanced oesophageal cancer. We assessed the prognostic relevance of FDG uptake in the NTO in an independent cohort of patients treated with definitive RCT.

METHODS

This retrospective evaluation included 72 patients with oesophageal squamous cell carcinoma treated with definitive RCT with curative intent. All patients underwent pretreatment and restaging FDG PET after receiving a radiation dose of 40-50 Gy. Standardized uptake values (SUV_max/SUV_mean), metabolic tumour volume (MTV) and relative changes from pretreatment to restaging PET (∆SUV_max/∆SUV_mean) were determined within the tumour and NTO. Univariate Cox regression with respect to overall survival (OS), local control (LC), distant metastases (DM) and treatment failure (TF) was performed. Independence of parameters was tested by multivariate Cox regression.

RESULTS

∆SUV_max NTO and MTV were prognostic factors for all investigated clinical endpoints (OS, LC, DM, TF). Inclusion of clinical and PET tumour parameters in multivariate analysis showed that ∆SUV_max NTO was an independent prognostic factor. Furthermore, multivariate analysis of ∆SUV_max NTO using previously published cut-off values from preoperatively treated patients revealed that ∆SUV_max NTO was independent prognostic factor for OS (HR = 1.88, p = 0.038), TF (HR = 2.11, p = 0.048) and DM (HR = 3.02, p = 0.047).

CONCLUSION

NTO-related tracer uptake during the course of treatment in patients with oesophageal carcinoma was shown to be of high prognostic relevance. Thus, metabolically activity of NTO measured in terms of ∆SUV_max NTO is a potential candidate for future treatment individualization (i.e. organ preservation).

Quantitative 4D-PET reconstruction for small animal using SMEIR-reconstructed 4D-CBCT

Respiratory motions in small animals PET cause image degradation during reconstruction. This work aims to develop a motion compensated 4D-PET reconstruction method using accurate motion corrections and attenuation corrections from 4D-CBCT images reconstructed using a simultaneous motion estimation and image reconstruction (SMEIR) method. Projections of 4D-CBCT were calculated using a ray-tracing method on a digital 4D rat phantom, and list-mode data of 4D-PET with matched respiratory phases were simulated using the GATE Monte Carlo package. The respiratory rate was set at 1.0 second per cycle with 10 phases of 30 projection images each. 4D-CBCT images were reconstructed using the SMEIR method and motion information and linear attenuation from 4D-CBCT were subsequently used for motion compensated 4D-PET reconstruction and attenuation corrections. We quantitatively evaluate the reconstructed 4D-PET using the errors of tumor volume and standard uptake values of tumors with different sizes. The tumor motion was successfully reconstructed and showed good agreement with the original phantom. The proposed method reduced tumor volume errors and standard uptake value errors. For tumor diameters of 3.0, 4.5, and 6.0 mm, the tumor volume errors are 32.5%, 29.2% and 19.4% respectively with motion compensation and 45.1%, 37.5% and 20.2% respectively without compensation.

Predictive Value of Asphericity in Pretherapeutic [111In]DTPA-Octreotide SPECT/CT for Response to Peptide Receptor Radionuclide Therapy with [177Lu]DOTATATE

PURPOSE

The purpose of this study was to assess the value of the spatial heterogeneity of somatostatin receptor (SSR) volume, quantified as asphericity (ASP), and to predict response to peptide receptor radionuclide therapy (PRRT) in patients with metastatic gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN).

PROCEDURES

From June 2011 to May 2013, patients suffering from GEP-NEN who underwent pretherapeutic [¹¹¹In-DTPA⁰]octreotide scintigraphy (Octreoscan®) prior to [¹⁷⁷Lu-DOTA⁰-Tyr³]octreotate ([¹⁷⁷Lu]DOTATATE)-PRRT were enrolled in this retrospective evaluation. SSR expression in 20 NEN patients was qualitatively and quantitatively assessed using the Krenning score, the metastasis to liver uptake ratio (M/L ratio), and ASP at baseline. Response to PRRT was evaluated based on lesions, which were classified as responding lesions (RL) and non-responding lesions (NRL) after 4- and 12-month follow-ups. The values of the Krenning score, M/L ratio, and ASP for response prediction were compared by using the Mann-Whitney U test, Kruskal-Wallis test, and receiver operating characteristic (ROC) curves.

RESULTS

Seventy-seven metastases (liver, n = 40; lymph node, n = 24; bone, n = 11; pancreas, n = 2) showed SSR expression. A higher ASP level was significantly associated with poorer response at both time points. ROC analyses revealed the highest area under the curve (AUC) for discrimination between RL and NRL for ASP after 4 months (AUC 0.97; p = 0.019) and after 12 months (AUC 0.96; p < 0.001), followed by the Krenning score (AUC 0.74; p = 0.082 and AUC 0.85; p < 0.001, respectively) and M/L ratio (AUC 0.77; p = 0.107 and AUC 0.82; p < 0.001). The optimal cutoff value for ASP was 5.12 % (sensitivity, 90 %; specificity, 93 %).

CONCLUSION

Asphericity of SSR-expressing lesions in pretherapeutic single-photon emission computed tomography with integrated computed tomography (SPECT/CT) is a promising parameter for predicting response to PRRT in gastroenteropancreatic neuroendocrine neoplasms.

Potential of asphericity as a novel diagnostic parameter in the evaluation of patients with 68Ga-PSMA-HBED-CC PET-positive prostate cancer lesions

BACKGROUND

The aim of this study was to evaluate the diagnostic value of the asphericity (ASP) as a novel quantitative parameter, reflecting the spatial heterogeneity of tracer uptake, in the staging process of patients with ⁶⁸Ga-PSMA-HBED-CC positron emission tomography (PET)-positive prostate cancer (PC). In this study, 37 patients (median age 72 years, range 52-82 years) with newly diagnosed PC, who received a ⁶⁸Ga-PSMA-HBED-CC PET fused with computed tomography (⁶⁸Ga-PSMA-PET/CT), a magnetic resonance imaging (MRI) of the prostate, and a core needle biopsy (within 74.2 ± 80.2 days) with an available Gleason score (GSc) were extracted from the local database. The ASP and the viable tumor volume (VTV) was calculated using the rover software (ABX GmbH, Radeberg, Germany), a segmentation tool for automated tumor volume delineation. Additionally, parameters including total lesion binding rate (TLB), maximum, mean and peak standardized uptake value (SUVmax/mean/peak), prostate-specific antigen (PSA), D'Amico classification, and prostate imaging reporting and data system (PI-RADS) were analyzed.

RESULTS

The ASP mean differed significantly (p ≤ 0.05) between the different GSc groups: GSc 6-7: 11.9 ± 4.8%, GSc 8: 25.5 ± 4.8%, GSc 9-10: 33.3 ± 6.8%. A significant correlation between ASP and GSc (rho = 0.88; CI 0.78-0.94; p < 0.05) was measured. The ASP enabled an independent (p > 0.05) prediction of the GSc. A moderate correlation was measured between ASP and the D'Amico classification (rho = 0.6; CI 0.32-0.78; p < 0.05). The VTV showed a moderate correlation with the SUVmax (rho = 0.58; CI 0.32-0.76; p < 0.05) and the GSc (rho = 0.51; CI 0.23-0.72; p < 0.05).

CONCLUSION

The asphericity in ⁶⁸Ga-PSMA-PET could represent a promising novel quantitative parameter for an improved non-invasive tumor staging of patients with PC.

Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211

PURPOSE

The purpose of this educational report is to provide an overview of the present state-of-the-art PET auto-segmentation (PET-AS) algorithms and their respective validation, with an emphasis on providing the user with help in understanding the challenges and pitfalls associated with selecting and implementing a PET-AS algorithm for a particular application.

APPROACH

A brief description of the different types of PET-AS algorithms is provided using a classification based on method complexity and type. The advantages and the limitations of the current PET-AS algorithms are highlighted based on current publications and existing comparison studies. A review of the available image datasets and contour evaluation metrics in terms of their applicability for establishing a standardized evaluation of PET-AS algorithms is provided. The performance requirements for the algorithms and their dependence on the application, the radiotracer used and the evaluation criteria are described and discussed. Finally, a procedure for algorithm acceptance and implementation, as well as the complementary role of manual and auto-segmentation are addressed.

FINDINGS

A large number of PET-AS algorithms have been developed within the last 20 years. Many of the proposed algorithms are based on either fixed or adaptively selected thresholds. More recently, numerous papers have proposed the use of more advanced image analysis paradigms to perform semi-automated delineation of the PET images. However, the level of algorithm validation is variable and for most published algorithms is either insufficient or inconsistent which prevents recommending a single algorithm. This is compounded by the fact that realistic image configurations with low signal-to-noise ratios (SNR) and heterogeneous tracer distributions have rarely been used. Large variations in the evaluation methods used in the literature point to the need for a standardized evaluation protocol.

CONCLUSIONS

Available comparison studies suggest that PET-AS algorithms relying on advanced image analysis paradigms provide generally more accurate segmentation than approaches based on PET activity thresholds, particularly for realistic configurations. However, this may not be the case for simple shape lesions in situations with a narrower range of parameters, where simpler methods may also perform well. Recent algorithms which employ some type of consensus or automatic selection between several PET-AS methods have potential to overcome the limitations of the individual methods when appropriately trained. In either case, accuracy evaluation is required for each different PET scanner and scanning and image reconstruction protocol. For the simpler, less robust approaches, adaptation to scanning conditions, tumor type, and tumor location by optimization of parameters is necessary. The results from the method evaluation stage can be used to estimate the contouring uncertainty. All PET-AS contours should be critically verified by a physician. A standard test, i.e., a benchmark dedicated to evaluating both existing and future PET-AS algorithms needs to be designed, to aid clinicians in evaluating and selecting PET-AS algorithms and to establish performance limits for their acceptance for clinical use. The initial steps toward designing and building such a standard are undertaken by the task group members.

Test-Retest Variability in Lesion SUV and Lesion SUR in 18F-FDG PET: An Analysis of Data from Two Prospective Multicenter Trials

Quantitative assessment of radio- and chemotherapy response with ¹⁸F-FDG whole-body PET has attracted increasing interest in recent years. In most published work, SUV has been used for this purpose. In the context of therapy response assessment, the reliability of lesion SUVs, notably their test-retest stability, thus becomes crucial. However, a recent study demonstrated substantial test-retest variability (TRV) in SUVs. The purpose of the present study was to investigate whether the tumor-to-blood SUV ratio (SUR) can improve TRV in tracer uptake. Methods: 73 patients with advanced non-small cell lung cancer from the prospective multicenter trials ACRIN 6678 (n = 34) and MK-0646-008 (n = 39) were included in this study. All patients underwent two ¹⁸F-FDG PET/CT investigations on two different days (time difference, 3.6 ± 2.1 d; range, 1-7 d) before therapy. For each patient, up to 7 tumor lesions were evaluated. For each lesion, SUV_max and SUV_peak were determined. Blood SUV was determined as the mean value of a 3-dimensional aortic region of interest that was delineated on the attenuation CT image and transferred to the PET image. SURs were computed as the ratio of tumor SUV to blood SUV and were uptake time-corrected to 75 min after injection. TRV was quantified as 1.96 multiplied by the root-mean-square deviation of the fractional paired differences in SUV and SUR. The combined effect of blood normalization and uptake time correction was inspected by considering R_TRV (TRV_SUR/TRV_SUV), a ratio reflecting the reduction in the TRV in SUR relative to SUV. R_TRV was correlated with the group-averaged-value difference (δ) in CF_mean (δCF_mean) of the quantity δCF = |CF - 1|, where CF is the numeric factor that converts individual ratios of paired SUVs into corresponding SURs. This correlation analysis was performed by successively increasing a threshold value δCF_min and computing δCF_mean and R_TRV for the remaining subgroup of patients/lesions with δCF ≥ δCF_minResults: The group-averaged TRV_SUV and TRV_SUR were 32.1 and 29.0, respectively, which correspond to a reduction of variability in SUR by an R_TRV factor of 0.9 in comparison to SUV. This rather marginal improvement can be understood to be a consequence of the atypically low intrasubject variability in blood SUV and uptake time and the accordingly small δCF values in the investigated prospective study groups. In fact, subgroup analysis with increasing δCF_min thresholds revealed a pronounced negative correlation (Spearman ρ = -0.99, P < 0.001) between R_TRV and δCF_mean, where R_TRV ≈ 0.4 in the δCF_min = 20% subgroup, corresponding to a more than 2-fold reduction of TRV_SUR compared with TRV_SUVConclusion: Variability in blood SUV and uptake time has been identified as a causal factor in the TRV in lesion SUV. Therefore, TRV in lesion uptake measurements can be reduced by replacing SUV with SUR as the uptake measure. The improvement becomes substantial for the level of variability in blood SUV and uptake time typically observed in the clinical context.

PET Radiomics in NSCLC: state of the art and a proposal for harmonization of methodology

Imaging with positron emission tomography (PET)/computed tomography (CT) is crucial in the management of cancer because of its value in tumor staging, response assessment, restaging, prognosis and treatment responsiveness prediction. In the last years, interest has grown in texture analysis which provides an "in-vivo" lesion characterization, and predictive information in several malignances including NSCLC; however several drawbacks and limitations affect these studies, especially because of lack of standardization in features calculation, definitions and methodology reporting. The present paper provides a comprehensive review of literature describing the state-of-the-art of FDG-PET/CT texture analysis in NSCLC, suggesting a proposal for harmonization of methodology.

A Dirichlet process mixture model for automatic (18)F-FDG PET image segmentation: Validation study on phantoms and on lung and esophageal lesions

PURPOSE

The aim of this study was to implement a Dirichlet process mixture (DPM) model for automatic tumor edge identification on (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) images by optimizing the parameters on which the algorithm depends, to validate it experimentally, and to test its robustness.

METHODS

The DPM model belongs to the class of the Bayesian nonparametric models and uses the Dirichlet process prior for flexible nonparametric mixture modeling, without any preliminary choice of the number of mixture components. The DPM algorithm implemented in the statistical software package R was used in this work. The contouring accuracy was evaluated on several image data sets: on an IEC phantom (spherical inserts with diameter in the range 10-37 mm) acquired by a Philips Gemini Big Bore PET-CT scanner, using 9 different target-to-background ratios (TBRs) from 2.5 to 70; on a digital phantom simulating spherical/uniform lesions and tumors, irregular in shape and activity; and on 20 clinical cases (10 lung and 10 esophageal cancer patients). The influence of the DPM parameters on contour generation was studied in two steps. In the first one, only the IEC spheres having diameters of 22 and 37 mm and a sphere of the digital phantom (41.6 mm diameter) were studied by varying the main parameters until the diameter of the spheres was obtained within 0.2% of the true value. In the second step, the results obtained for this training set were applied to the entire data set to determine DPM based volumes of all available lesions. These volumes were compared to those obtained by applying already known algorithms (Gaussian mixture model and gradient-based) and to true values, when available.

RESULTS

Only one parameter was found able to significantly influence segmentation accuracy (ANOVA test). This parameter was linearly connected to the uptake variance of the tested region of interest (ROI). In the first step of the study, a calibration curve was determined to automatically generate the optimal parameter from the variance of the ROI. This "calibration curve" was then applied to contour the whole data set. The accuracy (mean discrepancy between DPM model-based contours and reference contours) of volume estimation was below (1 ± 7)% on the whole data set (1 SD). The overlap between true and automatically segmented contours, measured by the Dice similarity coefficient, was 0.93 with a SD of 0.03.

CONCLUSIONS

The proposed DPM model was able to accurately reproduce known volumes of FDG concentration, with high overlap between segmented and true volumes. For all the analyzed inserts of the IEC phantom, the algorithm proved to be robust to variations in radius and in TBR. The main advantage of this algorithm was that no setting of DPM parameters was required in advance, since the proper setting of the only parameter that could significantly influence the segmentation results was automatically related to the uptake variance of the chosen ROI. Furthermore, the algorithm did not need any preliminary choice of the optimum number of classes to describe the ROIs within PET images and no assumption about the shape of the lesion and the uptake heterogeneity of the tracer was required.

Attenuation correction in 4D-PET using a single-phase attenuation map and rigidity-adaptive deformable registration

PURPOSE

Four-dimensional positron emission tomography (4D-PET) imaging is a potential solution to the respiratory motion effect in the thoracic region. Computed tomography (CT)-based attenuation correction (AC) is an essential step toward quantitative imaging for PET. However, due to the temporal difference between 4D-PET and a single attenuation map from CT, typically available in routine clinical scanning, motion artifacts are observed in the attenuation-corrected PET images, leading to errors in tumor shape and uptake. We introduced a practical method to align single-phase CT with all other 4D-PET phases for AC.

METHODS

A penalized non-rigid Demons registration between individual 4D-PET frames without AC provides the motion vectors to be used for warping single-phase attenuation map. The non-rigid Demons registration was used to derive deformation vector fields (DVFs) between PET matched with the CT phase and other 4D-PET images. While attenuated PET images provide useful data for organ borders such as those of the lung and the liver, tumors cannot be distinguished from the background due to loss of contrast. To preserve the tumor shape in different phases, an ROI-covering tumor was excluded from nonrigid transformation. Instead the mean DVF of the central region of the tumor was assigned to all voxels in the ROI. This process mimics a rigid transformation of the tumor along with a nonrigid transformation of other organs. A 4D-XCAT phantom with spherical lung tumors, with diameters ranging from 10 to 40 mm, was used to evaluate the algorithm. The performance of the proposed hybrid method for attenuation map estimation was compared to (a) the Demons nonrigid registration only and (b) a single attenuation map based on quantitative parameters in individual PET frames.

RESULTS

Motion-related artifacts were significantly reduced in the attenuation-corrected 4D-PET images. When a single attenuation map was used for all individual PET frames, the normalized root-mean-square error (NRMSE) values in tumor region were 49.3% (STD: 8.3%), 50.5% (STD: 9.3%), 51.8% (STD: 10.8%) and 51.5% (STD: 12.1%) for 10-mm, 20-mm, 30-mm, and 40-mm tumors, respectively. These errors were reduced to 11.9% (STD: 2.9%), 13.6% (STD: 3.9%), 13.8% (STD: 4.8%), and 16.7% (STD: 9.3%) by our proposed method for deforming the attenuation map. The relative errors in total lesion glycolysis (TLG) values were -0.25% (STD: 2.87%) and 3.19% (STD: 2.35%) for 30-mm and 40-mm tumors, respectively, in proposed method. The corresponding values for Demons method were 25.22% (STD: 14.79%) and 18.42% (STD: 7.06%). Our proposed hybrid method outperforms the Demons method especially for larger tumors. For tumors smaller than 20 mm, nonrigid transformation could also provide quantitative results.

CONCLUSION

Although non-AC 4D-PET frames include insignificant anatomical information, they are still useful to estimate the DVFs to align the attenuation map for accurate AC. The proposed hybrid method can recover the AC-related artifacts and provide quantitative AC-PET images.

Hybrid positron emission tomography segmentation of heterogeneous lung tumors using 3D Slicer: improved GrowCut algorithm with threshold initialization

This paper presents an improved GrowCut (IGC), a positron emission tomography-based segmentation algorithm, and tests its clinical applicability. Contrary to the traditional method that requires the user to provide the initial seeds, the IGC algorithm starts with a threshold-based estimate of the tumor and a three-dimensional morphologically grown shell around the tumor as the foreground and background seeds, respectively. The repeatability of IGC from the same observer at multiple time points was compared with the traditional GrowCut algorithm. The algorithm was tested in 11 nonsmall cell lung cancer lesions and validated against the clinician-defined manual contour and compared against the clinically used 25% of the maximum standardized uptake value [SUV-(max)], 40% [Formula: see text], and adaptive threshold methods. The time to edit IGC-defined functional volume to arrive at the gross tumor volume (GTV) was compared with that of manual contouring. The repeatability of the IGC algorithm was very high compared with the traditional GrowCut ([Formula: see text]) and demonstrated higher agreement with the manual contour with respect to threshold-based methods. Compared with manual contouring, editing the IGC achieved the GTV in significantly less time ([Formula: see text]). The IGC algorithm offers a highly repeatable functional volume and serves as an effective initial guess that can well minimize the time spent on labor-intensive manual contouring.

Characterization of PET/CT images using texture analysis: the past, the present… any future?

After seminal papers over the period 2009 - 2011, the use of texture analysis of PET/CT images for quantification of intratumour uptake heterogeneity has received increasing attention in the last 4 years. Results are difficult to compare due to the heterogeneity of studies and lack of standardization. There are also numerous challenges to address. In this review we provide critical insights into the recent development of texture analysis for quantifying the heterogeneity in PET/CT images, identify issues and challenges, and offer recommendations for the use of texture analysis in clinical research. Numerous potentially confounding issues have been identified, related to the complex workflow for the calculation of textural features, and the dependency of features on various factors such as acquisition, image reconstruction, preprocessing, functional volume segmentation, and methods of establishing and quantifying correspondences with genomic and clinical metrics of interest. A lack of understanding of what the features may represent in terms of the underlying pathophysiological processes and the variability of technical implementation practices makes comparing results in the literature challenging, if not impossible. Since progress as a field requires pooling results, there is an urgent need for standardization and recommendations/guidelines to enable the field to move forward. We provide a list of correct formulae for usual features and recommendations regarding implementation. Studies on larger cohorts with robust statistical analysis and machine learning approaches are promising directions to evaluate the potential of this approach.

The asphericity of the metabolic tumour volume in NSCLC: correlation with histopathology and molecular markers

PURPOSE

Asphericity (ASP) is a tumour shape descriptor based on the PET image. It quantitates the deviation from spherical of the shape of the metabolic tumour volume (MTV). In order to identify its biological correlates, we investigated the relationship between ASP and clinically relevant histopathological and molecular signatures in non-small-cell lung cancer (NSCLC).

METHODS

The study included 83 consecutive patients (18 women, aged 66.4 ± 8.9 years) with newly diagnosed NSCLC in whom PET/CT with ¹⁸F-FDG had been performed prior to therapy. Primary tumour resection specimens and core biopsies were used for basic histopathology and determination of the Ki-67 proliferation index. EGFR status, VEGF, p53 and ALK expression were obtained in a subgroup of 44 patients. The FDG PET images of the primary tumours were delineated using an automatic algorithm based on adaptive thresholding taking into account local background. In addition to ASP, SUVmax, MTV and some further descriptors of shape and intratumour heterogeneity were assessed as semiquantitative PET measures.

RESULTS

SUVmax, MTV and ASP were associated with pathological T stage (Kruskal-Wallis, p = 0.001, p < 0.0005 and p < 0.0005, respectively) and N stage (p = 0.017, p = 0.003 and p = 0.002, respectively). Only ASP was associated with M stage (p = 0.026). SUVmax, MTV and ASP were correlated with Ki-67 index (Spearman's rho = 0.326/p = 0.003, rho = 0.302/p = 0.006 and rho = 0.271/p = 0.015, respectively). The latter correlations were considerably stronger in adenocarcinomas than in squamous cell carcinomas. ASP, but not SUVmax or MTV, showed a tendency for a significant association with the extent of VEGF expression (p = 0.058). In multivariate Cox regression analysis, ASP (p < 0.0005) and the presence of distant metastases (p = 0.023) were significantly associated with progression-free survival. ASP (p = 0.006), the presence of distant metastases (p = 0.010), and Ki-67 index (p = 0.062) were significantly associated with overall survival.

CONCLUSION

The ASP of primary NSCLCs on FDG PET images is associated with tumour dimensions and molecular markers of proliferation and angiogenesis.

Respiratory motion correction in 4D-PET by simultaneous motion estimation and image reconstruction (SMEIR)

In conventional 4D positron emission tomography (4D-PET), images from different frames are reconstructed individually and aligned by registration methods. Two issues that arise with this approach are as follows: (1) the reconstruction algorithms do not make full use of projection statistics; and (2) the registration between noisy images can result in poor alignment. In this study, we investigated the use of simultaneous motion estimation and image reconstruction (SMEIR) methods for motion estimation/correction in 4D-PET. A modified ordered-subset expectation maximization algorithm coupled with total variation minimization (OSEM-TV) was used to obtain a primary motion-compensated PET (pmc-PET) from all projection data, using Demons derived deformation vector fields (DVFs) as initial motion vectors. A motion model update was performed to obtain an optimal set of DVFs in the pmc-PET and other phases, by matching the forward projection of the deformed pmc-PET with measured projections from other phases. The OSEM-TV image reconstruction was repeated using updated DVFs, and new DVFs were estimated based on updated images. A 4D-XCAT phantom with typical FDG biodistribution was generated to evaluate the performance of the SMEIR algorithm in lung and liver tumors with different contrasts and different diameters (10-40 mm). The image quality of the 4D-PET was greatly improved by the SMEIR algorithm. When all projections were used to reconstruct 3D-PET without motion compensation, motion blurring artifacts were present, leading up to 150% tumor size overestimation and significant quantitative errors, including 50% underestimation of tumor contrast and 59% underestimation of tumor uptake. Errors were reduced to less than 10% in most images by using the SMEIR algorithm, showing its potential in motion estimation/correction in 4D-PET.

Comparative evaluation of SUV, tumor-to-blood standard uptake ratio (SUR), and dual time point measurements for assessment of the metabolic uptake rate in FDG PET

Background

We have demonstrated recently that the tumor-to-blood standard uptake ratio (SUR) is superior to tumor standardized uptake value (SUV) as a surrogate of the metabolic uptake rate K_m of fluorodeoxyglucose (FDG), overcoming several of the known shortcomings of the SUV approach: excellent linear correlation of SUR and K_m from Patlak analysis was found using dynamic imaging of liver metastases. However, due to the perfectly standardized uptake period used for SUR determination and the comparatively short uptake period, these results are not automatically valid and applicable for clinical whole-body examinations in which the uptake periods (T) are distinctly longer and can vary considerably. Therefore, the aim of this work was to investigate the correlation between SUR derived from clinical static whole-body scans and K_m-surrogate derived from dual time point (DTP) measurements.

Methods

DTP ¹⁸F-FDG PET/CT was performed in 90 consecutive patients with histologically proven non-small cell lung cancer (NSCLC). In the PET images, the primary tumor was delineated with an adaptive threshold method. For determination of the blood SUV, an aorta region of interest (ROI) was delineated manually in the attenuation CT and transferred to the PET image. Blood SUV was computed as the mean value of the aorta ROI. SUR values were computed as ratio of tumor SUV and blood SUV. SUR values from the early time point of each DTP measurement were scan time corrected to 75 min postinjection (SUR_tc). As surrogate of K_m, we used the SUR(T) slope, K_slope, derived from DTP measurements since it is proportional to the latter under the given circumstances. The correlation of SUV and SUR_tc with K_slope was investigated. The prognostic value of SUV, SUR_tc, and K_slope for overall survival (OS) and progression-free survival (PFS) was investigated with univariate Cox regression in a homogeneous subgroup (N=31) treated with primary chemoradiation.

Results

Correlation analysis revealed for both, SUV and SUR_tc, a clear linear correlation with K_slope (P<0.001). Correlation SUR vs. K_slope was considerably stronger than correlation SUV vs. K_slope (R²=0.92 and R²=0.69, respectively, P<0.001). Univariate Cox regression revealed SUR_tc and K_slope as significant prognostic factors for PFS (hazard ratio (HR) =3.4/ P=0.017 and HR =4.3/ P=0.020, respectively). For SUV, no significant effect was found. None of the investigated parameters was prognostic for OS.

Conclusions

Scan-time-corrected SUR is a significantly better surrogate of tumor FDG metabolism in clinical whole-body PET compared to SUV. The very high linear correlation of SUR and DTP-derived K_slope (which is proportional to actual K_m) implies that for histologically proven malignant lesions, FDG-DTP does not provide added value in comparison to the SUR approach in NSCLC.

On the assessment of spatial resolution of PET systems with iterative image reconstruction

Spatial resolution is an important metric for performance characterization in PET systems. Measuring spatial resolution is straightforward with a linear reconstruction algorithm, such as filtered backprojection, and can be performed by reconstructing a point source scan and calculating the full-width-at-half-maximum (FWHM) along the principal directions. With the widespread adoption of iterative reconstruction methods, it is desirable to quantify the spatial resolution using an iterative reconstruction algorithm. However, the task can be difficult because the reconstruction algorithms are nonlinear and the non-negativity constraint can artificially enhance the apparent spatial resolution if a point source image is reconstructed without any background. Thus, it was recommended that a background should be added to the point source data before reconstruction for resolution measurement. However, there has been no detailed study on the effect of the point source contrast on the measured spatial resolution. Here we use point source scans from a preclinical PET scanner to investigate the relationship between measured spatial resolution and the point source contrast. We also evaluate whether the reconstruction of an isolated point source is predictive of the ability of the system to resolve two adjacent point sources. Our results indicate that when the point source contrast is below a certain threshold, the measured FWHM remains stable. Once the contrast is above the threshold, the measured FWHM monotonically decreases with increasing point source contrast. In addition, the measured FWHM also monotonically decreases with iteration number for maximum likelihood estimate. Therefore, when measuring system resolution with an iterative reconstruction algorithm, we recommend using a low-contrast point source and a fixed number of iterations.

A Segmentation Algorithm for Quantitative Analysis of Heterogeneous Tumors of the Cervix With ¹⁸F-FDG PET/CT

As positron-emission tomography (PET) images have low spatial resolution and much noise, accurate image segmentation is one of the most challenging issues in tumor quantification. Tumors of the uterine cervix present a particular challenge because of urine activity in the adjacent bladder. Here, we propose and validate an automatic segmentation method adapted to cervical tumors. Our proposed methodology combined the gradient field information of both the filtered PET image and the level set function into a level set framework by constructing a new evolution equation. Furthermore, we also constructed a new hyperimage to recognize a rough tumor region using the fuzzy c-means algorithm according to the tissue specificity as defined by both PET (uptake) and computed tomography (attenuation) to provide the initial zero level set, which could make the segmentation process fully automatic. The proposed method was verified based on simulation and clinical studies. For simulation studies, seven different phantoms, representing tumors with homogenous/heterogeneous-low/high uptake patterns and different volumes, were simulated with five different noise levels. Twenty-seven cervical cancer patients at different stages were enrolled for clinical evaluation of the method. Dice similarity coefficients (DSC) and Hausdorff distance (HD) were used to evaluate the accuracy of the segmentation method, while a Bland-Altman analysis of the mean standardized uptake value (SUVmean) and metabolic tumor volume (MTV) was used to evaluate the accuracy of the quantification. Using this method, the DSCs and HDs of the homogenous and heterogeneous phantoms under clinical noise level were 93.39 ±1.09% and 6.02 ±1.09 mm, 93.59 ±1.63% and 8.92 ±2.57 mm, respectively. The DSCs and HDs in patients measured 91.80 ±2.46% and 7.79 ±2.18 mm. Through Bland-Altman analysis, the SUVmean and the MTV using our method showed high correlation with the clinical gold standard. The results of both simulation and clinical studies demonstrated the accuracy, effectiveness, and robustness of the proposed method. Further assessment of the quantitative indices indicates the feasibility of this algorithm in accurate quantitative analysis of cervical tumors in clinical practice.

Asphericity of pretherapeutic tumour FDG uptake provides independent prognostic value in head-and-neck cancer

OBJECTIVE

To propose a novel measure, namely the 'asphericity' (ASP), of spatial irregularity of FDG uptake in the primary tumour as a prognostic marker in head-and-neck cancer.

METHODS

PET/CT was performed in 52 patients (first presentation, n = 36; recurrence, n = 16). The primary tumour was segmented based on thresholding at the volume-reproducible intensity threshold after subtraction of the local background. ASP was used to characterise the deviation of the tumour's shape from sphere symmetry. Tumour stage, tumour localisation, lymph node metastases, distant metastases, SUVmax, SUVmean, metabolic tumour volume (MTV) and total lesion glycolysis (TLG) were also considered. The association of overall (OAS) and progression-free survival (PFS) with these parameters was analysed.

RESULTS

Cox regression revealed high SUVmax [hazard ratio (HR) = 4.4/7.4], MTV (HR = 4.6/5.7), TLG (HR = 4.8/8.9) and ASP (HR = 7.8/7.4) as significant predictors with respect to PFS/OAS in case of first tumour manifestation. The combination of high MTV and ASP showed very high HRs of 22.7 for PFS and 13.2 for OAS. In case of recurrence, MTV (HR = 3.7) and the combination of MTV/ASP (HR = 4.2) were significant predictors of PFS.

CONCLUSIONS

ASP of pretherapeutic FDG uptake in the primary tumour improves the prediction of tumour progression in head-and-neck cancer at first tumour presentation.

KEY POINTS

Asphericity (ASP) characterises the spatial heterogeneity of FDG uptake in tumours. ASP is a promising prognostic parameter in head-and-neck cancer. ASP is useful for identification of high-risk patients with head-and-neck cancer.

A review on segmentation of positron emission tomography images

Positron Emission Tomography (PET), a non-invasive functional imaging method at the molecular level, images the distribution of biologically targeted radiotracers with high sensitivity. PET imaging provides detailed quantitative information about many diseases and is often used to evaluate inflammation, infection, and cancer by detecting emitted photons from a radiotracer localized to abnormal cells. In order to differentiate abnormal tissue from surrounding areas in PET images, image segmentation methods play a vital role; therefore, accurate image segmentation is often necessary for proper disease detection, diagnosis, treatment planning, and follow-ups. In this review paper, we present state-of-the-art PET image segmentation methods, as well as the recent advances in image segmentation techniques. In order to make this manuscript self-contained, we also briefly explain the fundamentals of PET imaging, the challenges of diagnostic PET image analysis, and the effects of these challenges on the segmentation results.