PD-L1 immunohistochemistry correlates only moderately with patient survival and response to PD-(L)1 treatment. Heterogeneity of tumor PD-L1 expression might limit the predictive value of small ...biopsies. Here we show that tumor PD-L1 and PD-1 expression can be quantified non-invasively using PET-CT in patients with non-small-cell lung cancer. Whole body PD-(L)1 PET-CT reveals significant tumor tracer uptake heterogeneity both between patients, as well as within patients between different tumor lesions.
Brain imaging in diffuse glioma is used for diagnosis, treatment planning, and follow-up.
In this meta-analysis, we address the diagnostic accuracy of imaging to delineate diffuse glioma.
We ...systematically searched studies of adults with diffuse gliomas and correlation of imaging with histopathology.
Study inclusion was based on quality criteria. Individual patient data were used, if available.
A hierarchic summary receiver operating characteristic method was applied. Low- and high-grade gliomas were analyzed in subgroups.
Sixty-one studies described 3532 samples in 1309 patients. The mean Standard for Reporting of Diagnostic Accuracy score (13/25) indicated suboptimal reporting quality. For diffuse gliomas as a whole, the diagnostic accuracy was best with T2-weighted imaging, measured as area under the curve, false-positive rate, true-positive rate, and diagnostic odds ratio of 95.6%, 3.3%, 82%, and 152. For low-grade gliomas, the diagnostic accuracy of T2-weighted imaging as a reference was 89.0%, 0.4%, 44.7%, and 205; and for high-grade gliomas, with T1-weighted gadolinium-enhanced MR imaging as a reference, it was 80.7%, 16.8%, 73.3%, and 14.8. In high-grade gliomas, MR spectroscopy (85.7%, 35.0%, 85.7%, and 12.4) and
C methionine-PET (85.1%, 38.7%, 93.7%, and 26.6) performed better than the reference imaging.
True-negative samples were underrepresented in these data, so false-positive rates are probably less reliable than true-positive rates. Multimodality imaging data were unavailable.
The diagnostic accuracy of commonly used imaging is better for delineation of low-grade gliomas than high-grade gliomas on the basis of limited evidence. Improvement is indicated from advanced techniques, such as MR spectroscopy and PET.
Purpose
In order to achieve comparability of image quality, harmonisation of PET system performance is imperative. In this study, prototype harmonisation criteria for PET brain studies were ...developed.
Methods
Twelve clinical PET/CT systems (4 GE, 4 Philips, 4 Siemens, including SiPM-based “digital” systems) were used to acquire 30-min PET scans of a Hoffman 3D Brain phantom filled with ~ 33 kBq·mL
−1
18
FFDG. Scan data were reconstructed using various reconstruction settings. The images were rigidly coregistered to a template (voxel size 1.17 × 1.17 × 2.00 mm
3
) onto which several volumes of interest (VOIs) were defined. Recovery coefficients (RC) and grey matter to white matter ratios (GMWMr) were derived for eroded (denoted in the text by subscript e) and non-eroded grey (GM) and white (WM) matter VOIs as well as a mid-phantom cold spot (VOI
cold
) and VOIs from the Hammers atlas. In addition, left-right hemisphere differences and voxel-by-voxel differences compared to a reference image were assessed.
Results
Systematic differences were observed for reconstructions with and without point-spread-function modelling (PSF
ON
and PSF
OFF
, respectively). Normalising to image-derived activity, upper and lower limits ensuring image comparability were as follows: for PSF
ON
, RC
GMe
= 0.97–1.01 and GMWMr
e
= 3.51–3.91 for eroded VOI and RC
GM
= 0.78–0.83 and GMWMr = 1.77–2.06 for non-eroded VOI, and for PSF
OFF
, RC
GMe
= 0.92–0.99 and GMWMr
e
= 3.14–3.68 for eroded VOI and RC
GM
= 0.75–0.81 and GMWMr = 1.72–1.95 for non-eroded VOI.
Conclusions
To achieve inter-scanner comparability, we propose selecting reconstruction settings based on RC
GMe
and GMWMr
e
as specified in
“Results”
. These proposed standards should be tested prospectively to validate and/or refine the harmonisation criteria.
The 6th annual meeting to address key issues in positron emission tomography (PET)/magnetic resonance imaging (MRI) was held again in Tübingen, Germany, from March 27 to 29, 2017. Over three days of ...invited plenary lectures, round table discussions and dialogue board deliberations, participants critically assessed the current state of PET/MRI, both clinically and as a research tool, and attempted to chart future directions. The meeting addressed the use of PET/MRI and workflows in oncology, neurosciences, infection, inflammation and chronic pain syndromes, as well as deeper discussions about how best to characterise the tumour microenvironment, optimise the complementary information available from PET and MRI, and how advanced data mining and bioinformatics, as well as information from liquid biomarkers (circulating tumour cells and nucleic acids) and pathology, can be integrated to give a more complete characterisation of disease phenotype. Some issues that have dominated previous meetings, such as the accuracy of MR-based attenuation correction (AC) of the PET scan, were finally put to rest as having been adequately addressed for the majority of clinical situations. Likewise, the ability to standardise PET systems for use in multicentre trials was confirmed, thus removing a perceived barrier to larger clinical imaging trials. The meeting openly questioned whether PET/MRI should, in all cases, be used as a whole-body imaging modality or whether in many circumstances it would best be employed to give an in-depth study of previously identified disease in a single organ or region. The meeting concluded that there is still much work to be done in the integration of data from different fields and in developing a common language for all stakeholders involved. In addition, the participants advocated joint training and education for individuals who engage in routine PET/MRI. It was agreed that PET/MRI can enhance our understanding of normal and disrupted biology, and we are in a position to describe the
in vivo
nature of disease processes, metabolism, evolution of cancer and the monitoring of response to pharmacological interventions and therapies. As such, PET/MRI is a key to advancing medicine and patient care.
•Baseline 18F-FDG–PET radiomics features can select patients at high risk more accurately than the IPI risk score.•The clinical PET model that was developed in the HOVON-84 data set remained ...predictive of the outcome in 6 independent studies.
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The objective of this study is to externally validate the clinical positron emission tomography (PET) model developed in the HOVON-84 trial and to compare the model performance of our clinical PET model using the international prognostic index (IPI). In total, 1195 patients with diffuse large B-cell lymphoma (DLBCL) were included in the study. Data of 887 patients from 6 studies were used as external validation data sets. The primary outcomes were 2-year progression-free survival (PFS) and 2-year time to progression (TTP). The metabolic tumor volume (MTV), maximum distance between the largest lesion and another lesion (Dmaxbulk), and peak standardized uptake value (SUVpeak) were extracted. The predictive values of the IPI and clinical PET model (MTV, Dmaxbulk, SUVpeak, performance status, and age) were tested. Model performance was assessed using the area under the curve (AUC), and diagnostic performance, using the positive predictive value (PPV). The IPI yielded an AUC of 0.62. The clinical PET model yielded a significantly higher AUC of 0.71 (P < .001). Patients with high-risk IPI had a 2-year PFS of 61.4% vs 51.9% for those with high-risk clinical PET, with an increase in PPV from 35.5% to 49.1%, respectively. A total of 66.4% of patients with high-risk IPI were free from progression or relapse vs 55.5% of patients with high-risk clinical PET scores, with an increased PPV from 33.7% to 44.6%, respectively. The clinical PET model remained predictive of outcome in 6 independent first-line DLBCL studies, and had higher model performance than the currently used IPI in all studies.
Eertink and colleagues externally validate the clinical positron emission tomography (PET) assessment developed in the HOVON-84 trial of diffuse large B-cell lymphoma. Based on metabolic tumor volume, maximum distance between the largest lesion and another lesion, and the peak standardized uptake value, clinicalPET successfully predicted the outcomes in 6 independent studies and appeared to perform better than the international prognostic index.
Background
The aim of this study was to assess radiomics features on pre-treatment
18
FFDG positron emission tomography (PET) as potential biomarkers for response and survival in patients with ...metastatic colorectal cancer (mCRC).
Methods
Patients with mCRC underwent
18
FFDG PET/computed tomography (CT) prior to first- or third-line palliative systemic treatment. Tumour lesions were semiautomatically delineated and standard uptake value (SUV), metabolically active tumour volume (MATV), total lesion glycolysis (TLG), entropy, area under the curve of the cumulative SUV-volume histogram (AUC-CSH), compactness and sphericity were obtained.
Results
Lesions of 47 patients receiving third-line systemic treatment had higher SUV
max
, SUV
peak
, SUV
mean
, MATV and TLG, and lower AUC-CSH, compactness and sphericity compared to 52 patients receiving first-line systemic treatment. Therefore, first- and third-line groups were evaluated separately. In the first-line group, anatomical changes on CT correlated negatively with TLG (ρ = 0.31) and MATV (ρ = 0.36), and positively with compactness (ρ = −0.27) and sphericity (ρ = −0.27). Patients without benefit had higher mean entropy (
p
= 0.021). Progression-free survival (PFS) and overall survival (OS) were worse with a decreased mean AUC hazard ratio (HR) 0.86, HR 0.77 and increase in mean MATV (HR 1.15, HR 1.22), sum MATV (HR 1.14, HR 1.19), mean TLG (HR 1.16, HR 1.22) and sum TLG (HT1.12, HR1.18). In the third-line group, AUC-CSH correlated negatively with anatomical change (ρ = 0.21). PFS and OS were worse with an increased mean MATV (HR 1.27, HR 1.68), sum MATV (HR 1.35, HR 2.04), mean TLG (HR 1.29, HR 1.52) and sum TLG (HT 1.27, HR 1.80). SUV
max
and SUV
peak
negatively correlated with OS (HR 1.19, HR 1.21). Cluster analysis of the 10 radiomics features demonstrated no complementary value in identifying aggressively growing lesions or patients with impaired survival.
Conclusion
We demonstrated an association between improved clinical outcome and pre-treatment low tumour volume and heterogeneity as well as high sphericity on
18
FFDG PET. Future PET imaging research should include radiomics features that incorporate tumour volume and heterogeneity when correlating PET data with clinical outcome.
Purpose
Quantification of positron emission tomography/magnetic resonance imaging (PET/MRI) studies is hampered by inaccurate MR-based attenuation correction (MR-AC). To date, most studies on MR-AC ...have been performed using PET/MR systems without time of flight (TOF). Maximum likelihood reconstruction of attenuation and activity (MLAA), however, has the potential to improve MR-AC by exploiting TOF. The purpose of this study is to assess the impact of MR-AC on PET image quantification for TOF-PET/MR systems and to evaluate PET accuracy when using TOF in combination with MLAA (TOF-MLAA).
Procedures
Simulations were designed to evaluate (1) the impact of MR-AC on PET quantification for different TOF windows (667, 500, 333 and 167 ps) and (2) use of TOF-MLAA for improving PET quantification. TOF-ordered subset expectation maximisation (OSEM) and TOF-MLAA reconstructions using MR-AC were compared with those obtained using TOF-OSEM with computed tomography-based AC (CT-AC).
Results
OSEM reconstructions without TOF showed a negative MR-AC-induced bias of −50 % in the bone. TOF-OSEM was able to reduce this bias down to −15 %, with more accurate results for better TOF. TOF-MLAA was able to reduce the bias to within 5 % but at the cost of a ∼40 % increase in image variance.
Conclusions
TOF-MLAA can improve quantitative PET accuracy of PET/MR studies. Further improvements are anticipated with improving TOF performance.
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