Detection and characterization of tumor changes in 18F-FDG PET patient monitoring using parametric imaging

Deformable image registration with deep network priors: a study on longitudinal PET images

Objective. This paper proposes a novel approach for the longitudinal registration of PET imaging acquired for the monitoring of patients with metastatic breast cancer. Unlike with other image analysis tasks, the use of deep learning (DL) has not significantly improved the performance of image registration. With this work, we propose a new registration approach to bridge the performance gap between conventional and DL-based methods: medical image registration method regularized by architecture (MIRRBA). Approach. MIRRBA is a subject-specific deformable registration method which relies on a deep pyramidal architecture to parametrize the deformation field. Diverging from the usual deep-learning paradigms, MIRRBA does not require a learning database, but only a pair of images to be registered that is used to optimize the network's parameters. We applied MIRRBA on a private dataset of 110 whole-body PET images of patients with metastatic breast cancer. We used different architecture configurations to produce the deformation field and studied the results obtained. We also compared our method to several standard registration approaches: two conventional iterative registration methods (ANTs and Elastix) and two supervised DL-based models (LapIRN and Voxelmorph). Registration accuracy was evaluated using the Dice score, the target registration error, the average Hausdorff distance and the detection rate, while the realism of the registration obtained was evaluated using Jacobian's determinant. The ability of the different methods to shrink disappearing lesions was also computed with the disappearing rate. Main results. MIRRBA significantly improved all metrics when compared to DL-based approaches. The organ and lesion Dice scores of Voxelmorph improved by 6% and 52% respectively, while the ones of LapIRN increased by 5% and 65%. Regarding conventional approaches, MIRRBA presented comparable results showing the feasibility of our method. Significance. In this paper, we also demonstrate the regularizing power of deep architectures and present new elements to understand the role of the architecture in DL methods used for registration.

Penalized maximum likelihood simultaneous longitudinal PET image reconstruction with difference-image priors

PURPOSE

Many clinical contexts require the acquisition of multiple positron emission tomography (PET) scans of a single subject, for example, to observe and quantitate changes in functional behaviour in tumors after treatment in oncology. Typically, the datasets from each of these scans are reconstructed individually, without exploiting the similarities between them. We have recently shown that sharing information between longitudinal PET datasets by penalizing voxel-wise differences during image reconstruction can improve reconstructed images by reducing background noise and increasing the contrast-to-noise ratio of high-activity lesions. Here, we present two additional novel longitudinal difference-image priors and evaluate their performance using two-dimesional (2D) simulation studies and a three-dimensional (3D) real dataset case study.

METHODS

We have previously proposed a simultaneous difference-image-based penalized maximum likelihood (PML) longitudinal image reconstruction method that encourages sparse difference images (DS-PML), and in this work we propose two further novel prior terms. The priors are designed to encourage longitudinal images with corresponding differences which have (a) low entropy (DE-PML), and (b) high sparsity in their spatial gradients (DTV-PML). These two new priors and the originally proposed longitudinal prior were applied to 2D-simulated treatment response [¹⁸ F]fluorodeoxyglucose (FDG) brain tumor datasets and compared to standard maximum likelihood expectation-maximization (MLEM) reconstructions. These 2D simulation studies explored the effects of penalty strengths, tumor behaviour, and interscan coupling on reconstructed images. Finally, a real two-scan longitudinal data series acquired from a head and neck cancer patient was reconstructed with the proposed methods and the results compared to standard reconstruction methods.

RESULTS

Using any of the three priors with an appropriate penalty strength produced images with noise levels equivalent to those seen when using standard reconstructions with increased counts levels. In tumor regions, each method produces subtly different results in terms of preservation of tumor quantitation and reconstruction root mean-squared error (RMSE). In particular, in the two-scan simulations, the DE-PML method produced tumor means in close agreement with MLEM reconstructions, while the DTV-PML method produced the lowest errors due to noise reduction within the tumor. Across a range of tumor responses and different numbers of scans, similar results were observed, with DTV-PML producing the lowest errors of the three priors and DE-PML producing the lowest bias. Similar improvements were observed in the reconstructions of the real longitudinal datasets, although imperfect alignment of the two PET images resulted in additional changes in the difference image that affected the performance of the proposed methods.

CONCLUSION

Reconstruction of longitudinal datasets by penalizing difference images between pairs of scans from a data series allows for noise reduction in all reconstructed images. An appropriate choice of penalty term and penalty strength allows for this noise reduction to be achieved while maintaining reconstruction performance in regions of change, either in terms of quantitation of mean intensity via DE-PML, or in terms of tumor RMSE via DTV-PML. Overall, improving the image quality of longitudinal datasets via simultaneous reconstruction has the potential to improve upon currently used methods, allow dose reduction, or reduce scan time while maintaining image quality at current levels.

99m Tc-labeled DTPA-colchicine dimer with improved tumor uptake

This work reports the synthesis, radiolabeling, and biological studies of ^99m Tc-diethylene triamine pentaacetic acid (DTPA)-colchicine dimer in tumor-bearing mice. The novel colchicine dimer was successfully synthesized by conjugation of DTPA to 2 colchicine biomolecules. The ligand could be labeled by ^99m Tc in high yield to get ^99m Tc-DTPA-colchicine dimer, which was hydrophilic and stable at room temperature. Biodistribution and imaging studies in tumor-bearing mice showed that ^99m Tc-DTPA-colchicine dimer accumulated in the tumor with improved uptake and retention. The results indicate the need for synthetic modification of the parent colchicine derivative and the ^99m Tc-chelate with a view to improve the tumor-targeting efficacy and in vivo kinetic profiles.

A framework based on hidden Markov trees for multimodal PET/CT image co-segmentation

PURPOSE

The purpose of this study was to investigate the use of a probabilistic quad-tree graph (hidden Markov tree, HMT) to provide fast computation, robustness and an interpretational framework for multimodality image processing and to evaluate this framework for single gross tumor target (GTV) delineation from both positron emission tomography (PET) and computed tomography (CT) images.

METHODS

We exploited joint statistical dependencies between hidden states to handle the data stack using multi-observation, multi-resolution of HMT and Bayesian inference. This framework was applied to segmentation of lung tumors in PET/CT datasets taking into consideration simultaneously the CT and the PET image information. PET and CT images were considered using either the original voxels intensities, or after wavelet/contourlet enhancement. The Dice similarity coefficient (DSC), sensitivity (SE), positive predictive value (PPV) were used to assess the performance of the proposed approach on one simulated and 15 clinical PET/CT datasets of non-small cell lung cancer (NSCLC) cases. The surrogate of truth was a statistical consensus (obtained with the Simultaneous Truth and Performance Level Estimation algorithm) of three manual delineations performed by experts on fused PET/CT images. The proposed framework was applied to PET-only, CT-only and PET/CT datasets, and were compared to standard and improved fuzzy c-means (FCM) multimodal implementations.

RESULTS

A high agreement with the consensus of manual delineations was observed when using both PET and CT images. Contourlet-based HMT led to the best results with a DSC of 0.92 ± 0.11 compared to 0.89 ± 0.13 and 0.90 ± 0.12 for Intensity-based HMT and Wavelet-based HMT, respectively. Considering PET or CT only in the HMT led to much lower accuracy. Standard and improved FCM led to comparatively lower accuracy than HMT, even when considering multimodal implementations.

CONCLUSIONS

We evaluated the accuracy of the proposed HMT-based framework for PET/CT image segmentation. The proposed method reached good accuracy, especially with pre-processing in the contourlet domain.

PET/Computed Tomography Scanning and Precision Medicine: Esophageal Cancer

Esophageal cancer commonly has a poor prognosis, which requires an accurate diagnosis and early treatment to improve outcome. Other modalities for staging, such as endoscopic ultrasound imaging and computed tomography (CT) scans, have a role in diagnosis and staging. However, PET with fluorine-18 fluoro-2-deoxy-d-glucose/CT (FDG PET/CT) scanning allows for improved detection of distant metastatic disease and can help to prevent unnecessary interventions that would increase morbidity. FDG PET/CT scanning is valuable in the neoadjuvant chemotherapy assessment and predicting survival outcomes subsequent to surgery. FDG PET/CT scanning detects recurrent disease and metastases in follow-up.

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.

Quantitative Evaluation of Therapeutic Response by FDG-PET-CT in Metastatic Breast Cancer

PURPOSE

To assess the therapeutic response for metastatic breast cancer with (18)F-FDG position emission tomography (PET), this retrospective study aims to compare the performance of six different metabolic metrics with PERCIST, PERCIST with optimal thresholds, and an image-based parametric approach.

METHODS

Thirty-six metastatic breast cancer patients underwent 128 PET scans and 123 lesions were identified. In a per-lesion and per-patient analysis, the performance of six metrics: maximum standardized uptake value (SUVmax), SUVpeak, standardized added metabolic activity (SAM), SUVmean, metabolic volume (MV), total lesion glycolysis (TLG), and a parametric approach (SULTAN) were determined and compared to the gold standard (defined by clinical assessment and biological and conventional imaging according RECIST 1.1). The evaluation was performed using PERCIST thresholds (for per-patient analysis only) and optimal thresholds (determined by the Youden criterion from the receiver operating characteristic curves).

RESULTS

In the per-lesion analysis, 210 pairs of lesion evolutions were studied. Using the optimal thresholds, SUVmax, SUVpeak, SUVmean, SAM, and TLG were significantly correlated with the gold standard. SUVmax, SUVpeak, and SUVmean reached the best sensitivity (91, 88, and 83%, respectively), specificity (93, 95, and 97%, respectively), and negative predictive value (NPV, 90, 88, and 83%, respectively). For the per--patient analysis, 79 pairs of PET were studied. The optimal thresholds compared to the PERCIST threshold did not improve performance for SUVmax, SUVpeak, and SUVmean. Only SUVmax, SUVpeak, SUVmean, and TLG were correlated with the gold standard. SULTAN also performed equally: 83% sensitivity, 88% specificity, and NPV 86%.

CONCLUSION

This study showed that SUVmax and SUVpeak were the best parameters for PET evaluation of metastatic breast cancer lesions. Parametric imaging is helpful in evaluating serial studies.

A New Approach to Evaluate Drug Treatment Response of Ovarian Cancer Patients Based on Deformable Image Registration

Although Response Evaluation Criteria in Solid Tumors (RECIST) is the current clinical guideline to assess size change of solid tumors after therapeutic treatment, it has a relatively lower association to the clinical outcome of progression free survival (PFS) of the patients. In this paper, we presented a new approach to assess responses of ovarian cancer patients to new chemotherapy drugs in clinical trials. We first developed and applied a multi-resolution B-spline based deformable image registration method to register two sets of computed tomography (CT) image data acquired pre- and post-treatment. The B-spline difference maps generated from the co-registered CT images highlight the regions related to the volumetric growth or shrinkage of the metastatic tumors, and density changes related to variation of necrosis inside the solid tumors. Using a testing dataset involving 19 ovarian cancer patients, we compared patients' response to the treatment using the new image registration method and RECIST guideline. The results demonstrated that using the image registration method yielded higher association with the six-month PFS outcomes of the patients than using RECIST. The image registration results also provided a solid foundation of developing new computerized quantitative image feature analysis schemes in the future studies.

Molecular Imaging to Plan Radiotherapy and Evaluate Its Efficacy

Molecular imaging plays a central role in the management of radiation oncology patients. Specific uses of imaging, particularly to plan radiotherapy and assess its efficacy, require an additional level of reproducibility and image quality beyond what is required for diagnostic imaging. Specific requirements include proper patient preparation, adequate technologist training, careful imaging protocol design, reliable scanner technology, reproducible software algorithms, and reliable data analysis methods. As uncertainty in target definition is arguably the greatest challenge facing radiation oncology, the greatest impact that molecular imaging can have may be in the reduction of interobserver variability in target volume delineation and in providing greater conformity between target volume boundaries and true tumor boundaries. Several automatic and semiautomatic contouring methods based on molecular imaging are available but still need sufficient validation to be widely adopted. Biologically conformal radiotherapy (dose painting) based on molecular imaging-assessed tumor heterogeneity is being investigated, but many challenges remain to fully exploring its potential. Molecular imaging also plays increasingly important roles in both early (during treatment) and late (after treatment) response assessment as both a predictive and a prognostic tool. Because of potentially confounding effects of radiation-induced inflammation, treatment response assessment requires careful interpretation. Although molecular imaging is already strongly embedded in radiotherapy, the path to widespread and all-inclusive use is still long. The lack of solid clinical evidence is the main impediment to broader use. Recommendations for practicing physicians are still rather scarce. (18)F-FDG PET/CT remains the main molecular imaging modality in radiation oncology applications. Although other molecular imaging options (e.g., proliferation imaging) are becoming more common, their widespread use is limited by lack of tracer availability and inadequate reimbursement models. With the increasing presence of molecular imaging in radiation oncology, special emphasis should be placed on adequate training of radiation oncology personnel to understand the potential, and particularly the limitations, of quantitative molecular imaging applications. Similarly, radiologists and nuclear medicine specialists should be sensitized to the special need of the radiation oncologist in terms of quantification and reproducibility. Furthermore, strong collaboration between radiation oncology, nuclear medicine/radiology, and medical physics teams is necessary, as optimal and safe use of molecular imaging can be ensured only within appropriate interdisciplinary teams.

State-Of-The-Art and Recent Advances in Quantification for Therapeutic Follow-Up in Oncology Using PET

¹⁸F-fluoro-2-deoxyglucose (¹⁸F-FDG) positron emission tomography (PET) is an important tool in oncology. Its use has greatly progressed from initial diagnosis to staging and patient monitoring. The information derived from ¹⁸F-FDG-PET allowed the development of a wide range of PET quantitative analysis techniques ranging from simple semi-quantitative methods like the standardized uptake value (SUV) to “high order metrics” that require a segmentation step and additional image processing. In this review, these methods are discussed, focusing particularly on the available methodologies that can be used in clinical trials as well as their current applications in international consensus for PET interpretation in lymphoma and solid tumors.

Computerized PET/CT image analysis in the evaluation of tumour response to therapy

Current cancer therapy strategy is mostly population based, however, there are large differences in tumour response among patients. It is therefore important for treating physicians to know individual tumour response. In recent years, many studies proposed the use of computerized positron emission tomography/CT image analysis in the evaluation of tumour response. Results showed that computerized analysis overcame some major limitations of current qualitative and semiquantitative analysis and led to improved accuracy. In this review, we summarize these studies in four steps of the analysis: image registration, tumour segmentation, image feature extraction and response evaluation. Future works are proposed and challenges described.

High FDG uptake areas on pre-radiotherapy PET/CT identify preferential sites of local relapse after chemoradiotherapy for locally advanced oesophageal cancer

PURPOSE

The high failure rates in the radiotherapy (RT) target volume suggest that patients with locally advanced oesophageal cancer (LAOC) would benefit from increased total RT doses. High 2-deoxy-2-[(18)F]fluoro-D-glucose (FDG) uptake (hotspot) on pre-RT FDG positron emission tomography (PET)/CT has been reported to identify intra-tumour sites at increased risk of relapse after RT in non-small cell lung cancer and in rectal cancer. Our aim was to confirm these observations in patients with LAOC and to determine the optimal maximum standardized uptake value (SUVmax) threshold to delineate smaller RT target volumes that would facilitate RT dose escalation without impaired tolerance.

METHODS

The study included 98 consecutive patients with LAOC treated by chemoradiotherapy (CRT). All patients underwent FDG PET/CT at initial staging and during systematic follow-up in a single institution. FDG PET/CT acquisitions were coregistered on the initial CT scan. Various subvolumes within the initial tumour (30, 40, 50, 60, 70, 80 and 90% SUVmax thresholds) and in the subsequent local recurrence (LR, 40 and 90% SUVmax thresholds) were pasted on the initial CT scan and compared[Dice, Jaccard, overlap fraction (OF), common volume/baseline volume, common volume/recurrent volume].

RESULTS

Thirty-five patients had LR. The initial metabolic tumour volume was significantly higher in LR tumours than in the locally controlled tumours (mean 25.4 vs 14.2 cc; p = 0.002). The subvolumes delineated on initial PET/CT with a 30-60% SUVmax threshold were in good agreement with the recurrent volume at 40% SUVmax (OF = 0.60-0.80). The subvolumes delineated on initial PET/CT with a 30-60% SUVmax threshold were in good to excellent agreement with the core volume (90% SUVmax) of the relapse (common volume/recurrent volume and OF indices 0.61-0.89).

CONCLUSION

High FDG uptake on pretreatment PET/CT identifies tumour subvolumes that are at greater risk of recurrence after CRT in patients with LAOC. We propose a 60% SUVmax threshold to delineate high FDG uptake areas on initial PET/CT as reduced target volumes for RT dose escalation.

The surgical treatment of patients with colorectal cancer and liver metastases in the setting of the "liver first" approach

A surgical resection is the only curative method in the therapy of colorectal carcinoma and liver metastases. Along with the development of interventional radiological techniques the indications for surgery widen. The number of metastases and patients age should not present a contraindication for surgical resection. However, there are still some doubts concerns what to resect first in cases of synchronous colorectal carcinoma and liver metastases and how to ensure the proper remnant liver volume in order to avoid postoperative liver failure and achieve the best results. Through this review the surgical therapy of colorectal carcinoma and liver metastases was revised in the setting of "liver-first" approach and the problem of ensuring of remnant liver volume.

Voxel-based dual-time 18F-FDG parametric imaging for rectal cancer: differentiation of residual tumor from postchemoradiotherapy changes

Supplemental Digital Content is available in the text.

Introduction

¹⁸F-Fluorodeoxyglucose (¹⁸F-FDG) PET/computed tomography (CT) has been used for evaluation of the response of rectal cancer to neoadjuvant chemoradiotherapy (CRT), but differentiating residual tumor from post-treatment changes remains a problem. We propose a voxel-based dual-time ¹⁸F-FDG PET parametric imaging technique for the evaluation of residual rectal cancer after CRT.

Materials and methods

Eighty-six patients with locally advanced rectal cancer who underwent neoadjuvant CRT between March 2009 and February 2011 were selected retrospectively. Standard 60-min postinjection PET/CT scans followed by 90-min delayed images were coregistered by rigid-body transformation. A dual-time parametric image was generated, which divided delayed standardized uptake value (SUV) by 60-min SUV on a voxel-by-voxel basis. Maximum delayed-to-standard SUV ratios (DSR) measured on the parametric images as well as the percentage of SUV decrease from pre-CRT to post-CRT scans (pre/post-CRT response index) were obtained for each tumor and correlated with pathologic response classified by the Dworak tumor regression grade (TRG).

Results

With respect to the false-positive lesions in the nine post-CRT patients with false-positive standard ¹⁸F-FDG scans in case groups who responded to therapy (TRG 3 or 4 tumors), eight were undetectable on dual-time parametric images (P<0.05). The maximum DSR showed significantly higher accuracy for identification of tumor regression compared with the pre/post-CRT response index in receiver-operating characteristic analysis (P<0.01). With a 1.25 cutoff value for the maximum DSR, 85.0% sensitivity, 95.5% specificity, and 93.0% overall accuracy were obtained for identification of good response.

Conclusion

A voxel-based dual-time parametric imaging technique for evaluation of post-CRT rectal cancer holds promise for differentiating residual tumor from treatment-related nonspecific ¹⁸F-FDG uptake.

Predicting pathologic tumor response to chemoradiotherapy with histogram distances characterizing longitudinal changes in 18F-FDG uptake patterns

PURPOSE

A family of fluorine-18 ((18)F)-fluorodeoxyglucose ((18)F-FDG) positron-emission tomography (PET) features based on histogram distances is proposed for predicting pathologic tumor response to neoadjuvant chemoradiotherapy (CRT). These features describe the longitudinal change of FDG uptake distribution within a tumor.

METHODS

Twenty patients with esophageal cancer treated with CRT plus surgery were included in this study. All patients underwent PET/CT scans before (pre-) and after (post-) CRT. The two scans were first rigidly registered, and the original tumor sites were then manually delineated on the pre-PET/CT by an experienced nuclear medicine physician. Two histograms representing the FDG uptake distribution were extracted from the pre- and the registered post-PET images, respectively, both within the delineated tumor. Distances between the two histograms quantify longitudinal changes in FDG uptake distribution resulting from CRT, and thus are potential predictors of tumor response. A total of 19 histogram distances were examined and compared to both traditional PET response measures and Haralick texture features. Receiver operating characteristic analyses and Mann-Whitney U test were performed to assess their predictive ability.

RESULTS

Among all tested histogram distances, seven bin-to-bin and seven crossbin distances outperformed traditional PET response measures using maximum standardized uptake value (AUC = 0.70) or total lesion glycolysis (AUC = 0.80). The seven bin-to-bin distances were: L(2) distance (AUC = 0.84), χ(2) distance (AUC = 0.83), intersection distance (AUC = 0.82), cosine distance (AUC = 0.83), squared Euclidean distance (AUC = 0.83), L(1) distance (AUC = 0.82), and Jeffrey distance (AUC = 0.82). The seven crossbin distances were: quadratic-chi distance (AUC = 0.89), earth mover distance (AUC = 0.86), fast earth mover distance (AUC = 0.86), diffusion distance (AUC = 0.88), Kolmogorov-Smirnov distance (AUC = 0.88), quadratic form distance (AUC = 0.87), and match distance (AUC = 0.84). These crossbin histogram distance features showed slightly higher prediction accuracy than texture features on post-PET images.

CONCLUSIONS

The results suggest that longitudinal patterns in (18)F-FDG uptake characterized using histogram distances provide useful information for predicting the pathologic response of esophageal cancer to CRT.

Monitoring tumour response during chemo-radiotherapy: a parametric method using FDG-PET/CT images in patients with oesophageal cancer

Background

The objective of this study is to investigate the feasibility and the additional interest of a parametric imaging (PI) method to monitor the early tumour metabolic response in a prospective series of oesophageal cancer patients who underwent positron emission tomography with fluoro-2-deoxy-d-glucose (FDG-PET/CT) before and during curative-intent chemo-radiotherapy.

Methods

Fifty-seven patients with squamous cell carcinoma (SCC) of the oesophagus prospectively underwent FDG-PET/CT before chemo-radiotherapy (CRT) (PET₁) and at 21 ± 3 days after the beginning of CRT (PET₂). The outcome was assessed at 3 months and 1 year after the completion of CRT (clinical examination, CT scan or FDG-PET/CT, biopsy). For each patient, PET₁ and PET₂ were registered using CT images. The 2 PET image sets were subtracted, so the voxels with significant changes in FDG uptake were identified. A model-based analysis of this graph was used to identify the tumour voxels in which significant changes occurred between the two scans and yielded indices characterising these changes (green and red clusters). Quantitative parameters were compared with clinical outcome at 3 months and at 1 year.

Results

The baseline tumour FDG uptake decreased significantly at PET₂ (p < 0.0001). The tumour volume significantly decreased between PET₁ and PET₂ (p < 0.02). The initial functional volume of the lesion (TV₁) was significantly lower (p < 0.02) in patients in clinical response (CR) at 3 months and 1 year. The volume of the lesion during the treatment (TV₂) was significantly lower in patients identified as in CR at 3 months (p < 0.03), but did not predict the outcome at 1 year. Multivariate analyses of outcome at 3 months showed that the risk of failure/death increased with younger age (p = 0.001), larger metabolic volume on PET₁ (p = 0.009) and larger volume with decreased FDG uptake (p = 0.047). As for outcome at 1 year, the risk of failure/death increased with younger age (p = 0.006), nodal involvement (p = 0.08) and larger volumes with increased uptake (p = 0.03).

Conclusion

A parametric method to assess tumour response on serial FDG-PET performed during chemo-radiotherapy was evaluated. Early metabolic changes, i.e. variations in FDG uptake, provided additional prognostic information in multivariate analyses ClinicalTrials.gov NCT 00934505.

Trial registration

Current Controlled Trials ISRCTN7824458

Variance of SUVs for FDG-PET/CT is greater in clinical practice than under ideal study settings

PURPOSE

Measurement variance affects the clinical effectiveness of PET-based measurement as a semiquantitative imaging biomarker for cancer response in individual patients and for planning clinical trials. In this study, we measured test-retest reproducibility of SUV measurements under clinical practice conditions and recorded recognized deviations from protocol compliance.

METHODS

Instrument performance calibration, display, and analyses conformed to manufacture recommendations. Baseline clinical (18)F-FDG PET/CT examinations were performed and then repeated at 1 to 7 days. Intended scan initiation uptake period was to repeat the examinations at the same time for each study after injection of 12 mCi FDG tracer. Avidity of uptake was measured in 62 tumors in 21 patients as SUV for maximum voxel (SUV(max)) and for a mean of sampled tumor voxels (SUV(mean)).

RESULTS

The range of SUV(max) and SUV(mean) was 1.07 to 21.47 and 0.91 to 14.69, respectively. Intraclass correlation coefficient between log of SUV(max) and log of SUV(mean) was 0.93 (95% confidence interval [CI], 0.88-0.95) and 0.92 (95% CI, 0.87-0.95), respectively.Correlation analysis failed to show an effect on uptake period variation on SUV measurements between the 2 examinations, suggesting additional sources of noise.The threshold criteria for relative difference from baseline for the 95% CI were ± 49% or ± 44% for SUV(max) or SUV(mean), respectively.

CONCLUSIONS

Variance of SUV for FDG-PET/CT in current clinical practice in a single institution was greater than expected when compared with benchmarks reported under stringent efficacy study settings. Under comparable clinical practice conditions, interpretation of changes in tumor avidity in individuals and assumptions in planning clinical trials may be affected.

The oncosurgery approach to managing liver metastases from colorectal cancer: a multidisciplinary international consensus

An international panel of multidisciplinary experts convened to develop recommendations for the management of patients with liver metastases from colorectal cancer (CRC). The aim was to address the main issues facing the CRC hepatobiliary multidisciplinary team (MDT) when managing such patients and to standardize the treatment patients receive in different centers. Based on current evidence, the group agreed on a number of issues including the following: (a) the primary aim of treatment is achieving a long disease-free survival (DFS) interval following resection; (b) assessment of resectability should be performed with high-quality cross-sectional imaging, staging the liver with magnetic resonance imaging and/or abdominal computed tomography (CT), depending on local expertise, staging extrahepatic disease with thoracic and pelvic CT, and, in selected cases, fluorodeoxyglucose positron emission tomography with ultrasound (preferably contrast-enhanced ultrasound) for intraoperative staging; (c) optimal first-line chemotherapy-doublet or triplet chemotherapy regimens combined with targeted therapy-is advisable in potentially resectable patients; (d) in this situation, at least four courses of first-line chemotherapy should be given, with assessment of tumor response every 2 months; (e) response assessed by the Response Evaluation Criteria in Solid Tumors (conventional chemotherapy) or nonsize-based morphological changes (antiangiogenic agents) is clearly correlated with outcome; no imaging technique is currently able to accurately diagnose complete pathological response but high-quality imaging is crucial for patient management; (f) the duration of chemotherapy should be as short as possible and resection achieved as soon as technically possible in the absence of tumor progression; (g) the number of metastases or patient age should not be an absolute contraindication to surgery combined with chemotherapy; (h) for synchronous metastases, it is not advisable to undertake major hepatic surgery during surgery for removal of the primary CRC; the reverse surgical approach (liver first) produces as good an outcome as the conventional approach in selected cases; (i) for patients with resectable liver metastases from CRC, perioperative chemotherapy may be associated with a modestly better DFS outcome; and (j) whether initially resectable or unresectable, cure or at least a long survival duration is possible after complete resection of the metastases, and MDT treatment is essential for improving clinical and survival outcomes. The group proposed a new system to classify initial unresectability based on technical and oncological contraindications.

Lesion-based detection of early chemosensitivity using serial static FDG PET/CT in metastatic colorectal cancer

PURPOSE

Medical oncology needs early identification of patients that are not responding to systemic therapy. (18)F-Fluorodeoxyglucose (FDG) positron emission tomography (PET) performed before and early during treatment has been proposed for this purpose. However, the best way to assess the change in FDG uptake between two scans has not been identified. We studied cutoff thresholds to identify responding tumours as a function of the method used to measure tumour uptake.

METHODS

The study included 28 metastatic colorectal cancer (mCRC) patients who underwent 2 FDG PET/CT scans (baseline and at day 14 of the first course of polychemotherapy). For 78 tumour lesions, 4 standardized uptake value (SUV) indices were measured: maximum SUV (SUV(max)) and mean SUV in a region obtained using an isocontour (SUV(40 %)), with each of these SUV normalized either by the patient body weight (BW) or body surface area (BSA). The per cent change and absolute change in tumour uptake between the baseline and the early PET scans were measured based on these four indices. These changes were correlated to the RECIST 1.0-based response using contrast-enhanced CT at baseline and at 6-8 weeks on treatment.

RESULTS

The 78 tumours were classified as non-responding (NRL, n = 58) and responding lesions (RL, n = 20). Receiver-operating characteristic (ROC) curves characterizing the performance in NRL/RL classification using early FDG PET uptake had areas under the curve between 0.75 and 0.84, without significant difference between the indices. The cutoff threshold in FDG uptake per cent change to get a 95 % sensitivity of RL detection depended on the way uptake was measured: -14 % (specificity of 53 %) and -22 % (specificity of 64 %) for SUV(max) and SUV(40 %), respectively. Thresholds expressed as absolute SUV decrease instead of per cent change were less sensitive to the SUV definition: an SUV decline by 1.2 yielded a sensitivity of RL detection of 95 % for SUV(max) and SUV(40 %). For a given cutoff threshold, the sensitivity was the same whatever the normalization (by BSA or BW).

CONCLUSION

A 14 % drop of tumour FDG SUV(max), 22 % drop of SUV(40 %) or 1.2 drop of SUV(max) or SUV(mean) after one single course of polychemotherapy predicts objective response in mCRC lesions with a high sensitivity, potentially allowing the early identification of non-responding patients.

Relative Function: Nuclear Brain Imaging in United States Courts

Neuropsychological testing—medical imaging of the brain structure and function—allows the expert to inform the court on the brain structure and function of the forensic examinee. Supported by extensive clinical use, neuropsychological testing and structural imaging in the form of computerized tomography and structural magnetic resonance imaging have achieved general acceptance in court. However, functional imaging such as functional MRI and nuclear medicine techniques, such as positron emission tomography (PET), have faced more admissibility challenges. While functional imaging is becoming an increasingly important tool in assessing neuropsychiatric illness, we surmise that evidentiary challenges are largely related to the phase of trial in which the nuclear study is offered as evidence. This article will review the basic science of functional nuclear imaging including PET and single photon emission computed tomography. We will then review cases where admissibility of these techniques has been challenged and consider whether and how nuclear brain imaging can influence the outcome of the trial.

An innovative iterative thresholding algorithm for tumour segmentation and volumetric quantification on SPECT images: Monte Carlo-based methodology and validation

PURPOSE

Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging play an important role in the segmentation of functioning parts of organs or tumours, but an accurate and reproducible delineation is still a challenging task. In this work, an innovative iterative thresholding method for tumour segmentation has been proposed and implemented for a SPECT system. This method, which is based on experimental threshold-volume calibrations, implements also the recovery coefficients (RC) of the imaging system, so it has been called recovering iterative thresholding method (RIThM). The possibility to employ Monte Carlo (MC) simulations for system calibration was also investigated.

METHODS

The RIThM is an iterative algorithm coded using MATLAB: after an initial rough estimate of the volume of interest, the following calculations are repeated: (i) the corresponding source-to-background ratio (SBR) is measured and corrected by means of the RC curve; (ii) the threshold corresponding to the amended SBR value and the volume estimate is then found using threshold-volume data; (iii) new volume estimate is obtained by image thresholding. The process goes on until convergence. The RIThM was implemented for an Infinia Hawkeye 4 (GE Healthcare) SPECT/CT system, using a Jaszczak phantom and several test objects. Two MC codes were tested to simulate the calibration images: SIMIND and SimSet. For validation, test images consisting of hot spheres and some anatomical structures of the Zubal head phantom were simulated with SIMIND code. Additional test objects (flasks and vials) were also imaged experimentally. Finally, the RIThM was applied to evaluate three cases of brain metastases and two cases of high grade gliomas.

RESULTS

Comparing experimental thresholds and those obtained by MC simulations, a maximum difference of about 4% was found, within the errors (+/- 2% and +/- 5%, for volumes > or = 5 ml or < 5 ml, respectively). Also for the RC data, the comparison showed differences (up to 8%) within the assigned error (+/- 6%). ANOVA test demonstrated that the calibration results (in terms of thresholds or RCs at various volumes) obtained by MC simulations were indistinguishable from those obtained experimentally. The accuracy in volume determination for the simulated hot spheres was between -9% and 15% in the range 4-270 ml, whereas for volumes less than 4 ml (in the range 1-3 ml) the difference increased abruptly reaching values greater than 100%. For the Zubal head phantom, errors ranged between 9% and 18%. For the experimental test images, the accuracy level was within +/- 10%, for volumes in the range 20-110 ml. The preliminary test of application on patients evidenced the suitability of the method in a clinical setting.

CONCLUSIONS

The MC-guided delineation of tumor volume may reduce the acquisition time required for the experimental calibration. Analysis of images of several simulated and experimental test objects, Zubal head phantom and clinical cases demonstrated the robustness, suitability, accuracy, and speed of the proposed method. Nevertheless, studies concerning tumors of irregular shape and/or nonuniform distribution of the background activity are still in progress.