68Ga-labeled fibroblast activation protein inhibitor (FAPI) PET/CT for locally advanced or recurrent pancreatic cancer staging and restaging after chemoradiotherapy.

Purpose: 68Ga-labeled fibroblast activation protein inhibitor (FAPI) is a novel PET tracer with great potential for staging pancreatic cancer. Data on locally advanced or recurrent disease is sparse, especially on tracer uptake before and after high dose chemoradiotherapy (CRT). The aim of this study was to evaluate [68Ga]Ga-FAPI-46 PET/CT staging in this setting. Methods: Twenty-seven patients with locally recurrent or locally advanced pancreatic adenocarcinoma (LRPAC n = 15, LAPAC n = 12) in stable disease or partial remission after chemotherapy underwent FAPI PET/CT and received consolidation CRT in stage M0 with follow-up FAPI PET/CT every three months until systemic progression. Quantitative PET parameters SUVmax, SUVmean, FAPI-derived tumor volume and total lesion FAPI-uptake were measured in baseline and follow-up PET/CT scans. Contrast-enhanced CT (ceCT) and PET/CT data were evaluated blinded and staged according to TNM classification. Results: FAPI PET/CT modified staging compared to ceCT alone in 23 of 27 patients in baseline, resulting in major treatment alterations in 52% of all patients (30%: target volume adjustment due to N downstaging, 15%: switch to palliative systemic chemotherapy only due to diffuse metastases, 7%: abortion of radiotherapy due to other reasons). Regarding follow-up scans, major treatment alterations after performing FAPI PET/CT were noted in eleven of 24 follow-up scans (46%) with switch to systemic chemotherapy or best supportive care due to M upstaging and ablative radiotherapy of distant lymph node and oligometastasis. Unexpectedly, in more than 90 % of the follow-up scans, radiotherapy did not induce local fibrosis related FAPI uptake. During the first follow-up, all quantitative PET metrics decreased, and irradiated lesions showed significantly lower FAPI uptake in locally controlled disease (SUVmax p = 0.047, SUVmean p = 0.0092) compared to local failure. Conclusion: Compared to ceCT, FAPI PET/CT led to major therapeutic alterations in patients with LRPAC and LAPAC prior to and after radiotherapy, which might help identify patients benefiting from adjustments in every treatment stage. FAPI PET/CT should be considered a useful diagnostic tool in LRPAC or LAPAC before and after CRT.

Quantitative PSMA-PET parameters in localized prostate cancer: prognostic and potential predictive value.

BACKGROUND: PSMA-PET is increasingly used for staging prostate cancer (PCA) patients. However, it is not clear if quantitative imaging parameters of positron emission tomography (PET) have an impact on disease progression and are thus important for the prognosis of localized PCA. METHODS: This is a monocenter retrospective analysis of 86 consecutive patients with localized intermediate or high-risk PCA and PSMA-PET before treatment The quantitative PET parameters maximum standardized uptake value (SUVmax), tumor asphericity (ASP), PSMA tumor volume (PSMA-TV), and PSMA total lesion uptake (PSMA-TLU = PSMA-TV × SUVmean) were assessed for their prognostic significance in patients with radiotherapy or surgery. Cox regression analyses were performed for biochemical recurrence-free survival, overall survival (OS), local control, and loco-regional control (LRC). RESULTS: 67% of patients had high-risk disease, 51 patients were treated with radiotherapy, and 35 with surgery. Analysis of metric PET parameters in the whole cohort revealed a significant association of PSMA-TV (p = 0.003), PSMA-TLU (p = 0.004), and ASP (p < 0.001) with OS. Upon binarization of PET parameters, several other parameters showed a significant association with clinical outcome. When analyzing high-risk patients according to the primary treatment approach, a previously published cut-off for SUVmax (8.6) showed a significant association with LRC in surgically treated (p = 0.048), but not in primary irradiated (p = 0.34) patients. In addition, PSMA-TLU (p = 0.016) seemed to be a very promising biomarker to stratify surgical patients. CONCLUSION: Our data confirm one previous publication on the prognostic impact of SUVmax in surgically treated patients with high-risk PCA. Our exploratory analysis indicates that PSMA-TLU might be even better suited. The missing association with primary irradiated patients needs prospective validation with a larger sample size to conclude a predictive potential. Trial registration Due to the retrospective nature of this research, no registration was carried out.

Multifrequency Magnetic Resonance Elastography Detects Small Abdominal Lymph Node Metastasis by High Stiffness.

OBJECTIVES: Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 is a clinical and research standard for evaluating malignant tumors and lymph node metastasis. However, quantitative analysis of nodal status is limited to measurement of short axis diameter (SAD), and metastatic lymph nodes below 10 mm in SAD are often not detected. The purpose of this study was to evaluate the value of multifrequency magnetic resonance elastography (MRE) when added to RECIST 1.1 for detection of lymph node metastasis. MATERIALS AND METHODS: Twenty-five benign and 82 metastatic lymph nodes were prospectively examined by multifrequency MRE at 1.5 T using tomoelastography postprocessing at 30, 40, 50, and 60 Hz (total scan time of 4 minutes). Shear wave speed as a surrogate of soft tissue stiffness was provided in m/s. Positron emission tomography-computed tomography was used as reference standard for identification of abdominal lymph node metastasis from histologically confirmed primary tumors. The diagnostic performance of MRE was compared with that of SAD according to RECIST 1.1 and evaluated by receiver operating characteristic curve analysis using generalized linear mixed models and binary logistic mixed models. Sensitivity, specificity, and predictive values were calculated for different cutoffs. RESULTS: Metastatic lymph nodes (1.90 ± 0.57 m/s) were stiffer than benign lymph nodes (0.98 ± 0.20 m/s, P < 0.001). An area under the curve of 0.95 for a cutoff of 1.32 m/s was calculated. Using a conservative approach with 1.0 specificity, we found sensitivity (SAD/MRE/MRE + SAD, 0.56/0.84/0.88), negative predictive values (0.41/0.66/0.71), and overall accuracy (0.66/0.88/0.91) to be improved using MRE and even higher for combined MRE and SAD. CONCLUSIONS: Multifrequency MRE improves metastatic abdominal lymph node detection by 25% based on higher tissue stiffness-even for lymph nodes with an SAD ≤10 mm. Stiffness information is quick to obtain and would be a promising supplement to RECIST.

Reevaluating the relevance of 18F-FDG PET findings for diagnosis of neurosarcoidosis: a case series.

OBJECTIVE: The diagnosis of neurosarcoidosis (NS) remains challenging due to the difficulty to obtain central nervous system (CNS) biopsies. Various diagnostic parameters are considered for the definition of possible, probable and definite NS. Magnetic resonance imaging (MRI) is the imaging gold standard and considered in diagnostic criteria. Fluorodeoxyglucose positron emission (18F-FDG PET) is sometimes performed additionally to identify possible systemic biopsy targets. However, at present, its findings are not incorporated into the diagnostic criteria for neurosarcoidosis (NS). METHODS: We conducted a single center retrospective search for the period 2020-2022, for patients with neurological symptoms in a diagnostic context of suspected NS who underwent MRI and additional 18F-FDG PET scans to identify potential hypermetabolism in the CNS and biopsy targets. RESULTS: We identified three cases of NS, where Gadolinium-enhanced MRI scans did not show abnormalities while 18F-FDG PET revealed hypermetabolic lesions in areas of the CNS. Additional MRI scans were still inconclusive for structural changes. We diagnosed a "probable" NS in all cases with histopathological confirmation of systemic sarcoidosis which led to an intensified therapy regime. DISCUSSION: 18F-FDG PET is an early indicator for metabolic changes. It appears to be a useful add-on to improve accuracy of diagnostic criteria in suspected NS without MRI findings.

ChatGPT: Can You Prepare My Patients for [18F]FDG PET/CT and Explain My Reports?

We evaluated whether the artificial intelligence chatbot ChatGPT can adequately answer patient questions related to [18F]FDG PET/CT in common clinical indications before and after scanning. Methods: Thirteen questions regarding [18F]FDG PET/CT were submitted to ChatGPT. ChatGPT was also asked to explain 6 PET/CT reports (lung cancer, Hodgkin lymphoma) and answer 6 follow-up questions (e.g., on tumor stage or recommended treatment). To be rated "useful" or "appropriate," a response had to be adequate by the standards of the nuclear medicine staff. Inconsistency was assessed by regenerating responses. Results: Responses were rated "appropriate" for 92% of 25 tasks and "useful" for 96%. Considerable inconsistencies were found between regenerated responses for 16% of tasks. Responses to 83% of sensitive questions (e.g., staging/treatment options) were rated "empathetic." Conclusion: ChatGPT might adequately substitute for advice given to patients by nuclear medicine staff in the investigated settings. Improving the consistency of ChatGPT would further increase reliability.

[177Lu]Lu-PSMA Therapy as an Individual Treatment Approach for Patients with High-Grade Glioma: Dosimetry Results and Critical Statement.

The theranostic use of prostate-specific membrane antigen (PSMA) appears to be promising in patients with high-grade glioma. This study investigated [177Lu]Lu-PSMA therapy as an individual treatment approach with a focus on intratherapeutic dosimetry. Methods: Three patients were treated with a median of 6.03 GBq (interquartile range [IQR], 5.74-6.10) of [177Lu]Lu-PSMA. Intratherapeutic dosimetry was performed using a hybrid scenario with planar whole-body scintigraphy at 2, 24, and 48 h after treatment injection and SPECT/CT at 48 h after injection. Additive whole-body scintigraphy at 8 d after injection was performed on 1 patient. Results: The median doses were 0.56 Gy (IQR, 0.36-1.25 Gy) to tumor, 0.27 Gy (IQR, 0.16-0.57 Gy) to risk organs, 2.13 Gy (IQR, 1.55-2.89 Gy) to kidneys, and 0.76 Gy (IQR, 0.70-1.20 Gy) to salivary glands. Whole-body exposure was 0.11 Gy (IQR, 0.06-0.18 Gy). Conclusion: Because the intratherapeutic tumor dose is lower than that used in external radiation oncology, the effectiveness of treatment is questionable.

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.

A machine learning tool to improve prediction of mediastinal lymph node metastases in non-small cell lung cancer using routinely obtainable [18F]FDG-PET/CT parameters.

BACKGROUND: In patients with non-small cell lung cancer (NSCLC), accuracy of [18F]FDG-PET/CT for pretherapeutic lymph node (LN) staging is limited by false positive findings. Our aim was to evaluate machine learning with routinely obtainable variables to improve accuracy over standard visual image assessment. METHODS: Monocentric retrospective analysis of pretherapeutic [18F]FDG-PET/CT in 491 consecutive patients with NSCLC using an analog PET/CT scanner (training + test cohort, n = 385) or digital scanner (validation, n = 106). Forty clinical variables, tumor characteristics, and image variables (e.g., primary tumor and LN SUVmax and size) were collected. Different combinations of machine learning methods for feature selection and classification of N0/1 vs. N2/3 disease were compared. Ten-fold nested cross-validation was used to derive the mean area under the ROC curve of the ten test folds ("test AUC") and AUC in the validation cohort. Reference standard was the final N stage from interdisciplinary consensus (histological results for N2/3 LNs in 96%). RESULTS: N2/3 disease was present in 190 patients (39%; training + test, 37%; validation, 46%; p = 0.09). A gradient boosting classifier (GBM) with 10 features was selected as the final model based on test AUC of 0.91 (95% confidence interval, 0.87-0.94). Validation AUC was 0.94 (0.89-0.98). At a target sensitivity of approx. 90%, test/validation accuracy of the GBM was 0.78/0.87. This was significantly higher than the accuracy based on "mediastinal LN uptake > mediastinum" (0.7/0.75; each p < 0.05) or combined PET/CT criteria (PET positive and/or LN short axis diameter > 10 mm; 0.68/0.75; each p < 0.001). Harmonization of PET images between the two scanners affected SUVmax and visual assessment of the LNs but did not diminish the AUC of the GBM. CONCLUSIONS: A machine learning model based on routinely available variables from [18F]FDG-PET/CT improved accuracy in mediastinal LN staging compared to established visual assessment criteria. A web application implementing this model was made available.

Optimized Whole-Body PET MRI Sequence Workflow in Pediatric Hodgkin Lymphoma Patients.

18F-FDG PET/MRI might be the diagnostic method of choice for Hodgkin lymphoma patients, as it combines significant metabolic information from PET with excellent soft-tissue contrast from MRI and avoids radiation exposure from CT. However, a major issue is longer examination times than for PET/CT, especially for younger children needing anesthesia. Thus, a targeted selection of suitable whole-body MRI sequences is important to optimize the PET/MRI workflow. Methods: The initial PET/MRI scans of 84 EuroNet-PHL-C2 study patients from 13 international PET centers were evaluated. In each available MRI sequence, 5 PET-positive lymph nodes were assessed. If extranodal involvement occurred, 2 splenic lesions, 2 skeletal lesions, and 2 lung lesions were also assessed. A detection rate was calculated dividing the number of visible, anatomically assignable, and measurable lesions in the respective MRI sequence by the total number of lesions. Results: Relaxation time-weighted (T2w) transverse sequences with fat saturation (fs) yielded the best result, with detection rates of 95% for nodal lesions, 62% for splenic lesions, 94% for skeletal lesions, and 83% for lung lesions, followed by T2w transverse sequences without fs (86%, 49%, 16%, and 59%, respectively) and longitudinal relaxation time-weighted contrast-enhanced transverse sequences with fs (74%, 35%, 57%, and 55%, respectively). Conclusion: T2w transverse sequences with fs yielded the highest detection rates and are well suited for accurate whole-body PET/MRI in lymphoma patients. There is no evidence to recommend the use of contrast agents.

CT radiomics to predict Deauville score 4 positive and negative Hodgkin lymphoma manifestations.

18F-FDG-PET/CT is standard to assess response in Hodgkin lymphoma by quantifying metabolic activity with the Deauville score. PET/CT, however, is time-consuming, cost-extensive, linked to high radiation and has a low availability. As an alternative, we investigated radiomics from non-contrast-enhanced computed tomography (NECT) scans. 75 PET/CT examinations of 43 patients on two different scanners were included. Target lesions were classified as Deauville score 4 positive (DS4+) or negative (DS4-) based on their SUVpeak and then segmented in NECT images. From these segmentations, 107 features were extracted with PyRadiomics. All further statistical analyses were then performed scanner-wise: differences between DS4+ and DS4- manifestations were assessed with the Mann-Whitney-U-test and single feature performances with the ROC-analysis. To further verify the reliability of the results, the number of features was reduced using different techniques. The feature median showed a high sensitivity for DS4+ manifestations on both scanners (scanner A: 0.91, scanner B: 0.85). It furthermore was the only feature that remained in both datasets after applying different feature reduction techniques. The feature median from NECT concordantly has a high sensitivity for DS4+ Hodgkin manifestations on two different scanners and thus could provide a surrogate for increased metabolic activity in PET/CT.

Inferring FDG-PET-positivity of lymph node metastases in proven lung cancer from contrast-enhanced CT using radiomics and machine learning.

BACKGROUND: We evaluated the role of radiomics applied to contrast-enhanced computed tomography (CT) in the detection of lymph node (LN) metastases in patients with known lung cancer compared to 18F-fluorodeoxyglucose positron emission tomography (PET)/CT as a reference. METHODS: This retrospective analysis included 381 patients with 1,799 lymph nodes (450 malignant, 1,349 negative). The data set was divided into a training and validation set. A radiomics analysis with 4 filters and 6 algorithms resulting in 24 different radiomics signatures and a bootstrap algorithm (Bagging) with 30 bootstrap iterations was performed. A decision curve analysis was applied to generate a net benefit to compare the radiomics signature to two expert radiologists as one-by-one and as a prescreening tool in combination with the respective radiologist and only the radiologists. RESULTS: All 24 modeling methods showed good and reliable discrimination for malignant/benign LNs (area under the curve 0.75-0.87). The decision curve analysis showed a net benefit for the least absolute shrinkage and selection operator (LASSO) classifier for the entire probability range and outperformed the expert radiologists except for the high probability range. Using the radiomics signature as a prescreening tool for the radiologists did not improve net benefit. CONCLUSIONS: Radiomics showed good discrimination power irrespective of the modeling technique in detecting LN metastases in patients with known lung cancer. The LASSO classifier was a suitable diagnostic tool and even outperformed the expert radiologists, except for high probabilities. Radiomics failed to improve clinical benefit as a prescreening tool.

[68Ga]Ga-PSMA PET/MRI, histological PSMA expression and preliminary experience with [177Lu]Lu-PSMA therapy in relapsing high-grade glioma.

Purpose: High-grade gliomas (HGG) are still associated with a dismal prognosis. Prostate specific membrane antigen (PSMA) is discussed as a theranostic target for PSMA-directed radioligand therapy ([177Lu]Lu-PSMA RLT). Here, we report on the correlation of [68Ga]Ga-PSMA uptake with histological PSMA expression and on our preliminary experience with [177Lu]Lu-PSMA RLT in relapsing HGG. Methods: Patients with relapsing HGG underwent [68Ga]Ga-PSMA PET/MRI to evaluate eligibility for an individualized treatment approach with [177Lu]Lu-PSMA. Standard uptake values (SUV) for tumor and liver and respective tumor-to-background ratios (compared to the liver) (TBR) on [68Ga]Ga-PSMA PET/MRI were assessed. Eligibility criteria for [177Lu]Lu-PSMA therapy were exhaustion of all standard treatment options available and TBRmax>1.0. In 11 samples, immunohistochemical PSMA expression was determined, quantified using the H-score and correlated with uptake on [68Ga]Ga-PSMA PET/MRI. Results: We included 20 patients with a median age of 53 years (IQR 42-57). The median SUV on [68Ga]Ga-PSMA PET/MRI was 4.5 (3.7-6.2) for SUVmax and 1.4 (1.1-1.7) for SUVmean. The respective TBR was maximum 0.6 (0.4-0.8) and mean 0.3 (0.2-0.4). High TBRmax correlated with increased endothelial PSMA expression [H-score of 65 (62.5-77.5)]. Three patients (15%) presented a TBRmax>1.0 and qualified for [177Lu]Lu-PSMA RLT. No treatment related toxicity was observed. Conclusion: Only a minority of patients with relapsing HGG qualified for [177Lu]Lu-PSMA RLT. Our data demonstrates that PSMA expression in the neo-vasculature corresponds to PSMA uptake on [68Ga]Ga-PSMA PET/MRI and might be used as a screening tool for patient selection. Future prospective studies need to focus the debate on TBRmax thresholds as inclusion criteria for PSMA RLT.

Therapeutic targeting of ATR in alveolar rhabdomyosarcoma.

Despite advances in multi-modal treatment approaches, clinical outcomes of patients suffering from PAX3-FOXO1 fusion oncogene-expressing alveolar rhabdomyosarcoma (ARMS) remain dismal. Here we show that PAX3-FOXO1-expressing ARMS cells are sensitive to pharmacological ataxia telangiectasia and Rad3 related protein (ATR) inhibition. Expression of PAX3-FOXO1 in muscle progenitor cells is not only sufficient to increase sensitivity to ATR inhibition, but PAX3-FOXO1-expressing rhabdomyosarcoma cells also exhibit increased sensitivity to structurally diverse inhibitors of ATR. Mechanistically, ATR inhibition leads to replication stress exacerbation, decreased BRCA1 phosphorylation and reduced homologous recombination-mediated DNA repair pathway activity. Consequently, ATR inhibitor treatment increases sensitivity of ARMS cells to PARP1 inhibition in vitro, and combined treatment with ATR and PARP1 inhibitors induces complete regression of primary patient-derived ARMS xenografts in vivo. Lastly, a genome-wide CRISPR activation screen (CRISPRa) in combination with transcriptional analyses of ATR inhibitor resistant ARMS cells identifies the RAS-MAPK pathway and its targets, the FOS gene family, as inducers of resistance to ATR inhibition. Our findings provide a rationale for upcoming biomarker-driven clinical trials of ATR inhibitors in patients suffering from ARMS.

Correlation Between Quantitative PSMA PET Parameters and Clinical Risk Factors in Non-Metastatic Primary Prostate Cancer Patients.

Background: PSMA PET is frequently used for staging of prostate cancer patients. Furthermore, there is increasing interest to use PET information for personalized local treatment approaches in surgery and radiotherapy, especially for focal treatment strategies. However, it is not well established which quantitative imaging parameters show highest correlation with clinical and histological tumor aggressiveness. Methods: This is a retrospective analysis of 135 consecutive patients with non-metastatic prostate cancer and PSMA PET before any treatment. Clinical risk parameters (PSA values, Gleason score and D'Amico risk group) were correlated with quantitative PET parameters maximum standardized uptake value (SUVmax), mean SUV (SUVmean), tumor asphericity (ASP) and PSMA tumor volume (PSMA-TV). Results: Most of the investigated imaging parameters were highly correlated with each other (correlation coefficients between 0.20 and 0.95). A low to moderate, however significant, correlation of imaging parameters with PSA values (0.19 to 0.45) and with Gleason scores (0.17 to 0.31) was observed for all parameters except ASP which did not show a significant correlation with Gleason score. Receiver operating characteristics for the detection of D'Amico high-risk patients showed poor to fair sensitivity and specificity for all investigated quantitative PSMA PET parameters (Areas under the curve (AUC) between 0.63 and 0.73). Comparison of AUC between quantitative PET parameters by DeLong test showed significant superiority of SUVmax compared to SUVmean for the detection of high-risk patients. None of the investigated imaging parameters significantly outperformed SUVmax. Conclusion: Our data confirm prior publications with lower number of patients that reported moderate correlations of PSMA PET parameters with clinical risk factors. With the important limitation that Gleason scores were only biopsy-derived in this study, there is no indication that the investigated additional parameters deliver superior information compared to SUVmax.

Radiation doses from low-dose CT scans in SPECT/CT and PET/CT examinations: A survey in Germany.

AIM: Recently, dose reference levels (DRLs) have been defined in Germany for auxiliary low-dose CT scans in hybrid SPECT/CT and PET/CT examinations, based on data from 2016/17. Here, another survey from 2020 was evaluated and compared with the new DRLs as well as with similar surveys from foreign countries. METHODS: The survey, which had already been conducted in the Nordic countries, queried for various examinations including the following values: patient weight and height, volume CT dose index (CTDIvol), dose length product (DLP). For each examination, statistical parameters such as the third quartile (Q3) were determined from all submitted CTDIvol and DLP values. Additionally, for examinations comprising datasets from at least 10 systems, the third quartile (Q3-Med) of the respective median values of each system was calculated. Q3 and Q3-Med were compared with the newly published DRLs from Germany and values from similar studies from other countries. RESULTS: Data from 15 SPECT/CT and 13 PET/CT systems from 15 nuclear medicine departments were collected. For the following examinations datasets from more than 10 systems were submitted: SPECT lung VQ, SPECT bone, SPECT&PET cardiac, PET brain, PET oncology. Especially for examinations of the thorax and heart, the new DRLs are very strict compared to this study. The CTDIvol values for examinations of the head were lower in this study than the DRLs prescribe now. CONCLUSIONS: For certain examination types, there is a need for dose optimization at some clinics and devices in order to take into account the new DRLs in Germany in the future.

Pindborg Tumor-An Uncommon Odontogenic Tumor Detected by 68Ga-DOTATOC.

A 62-year-old-woman with a suspected Tumor-induced-osteomalacia (TIO), a rare neoplastic syndrome that results in renal phosphate wasting with hypophosphatemia, underwent 68Ga-DOTATOC PET/CT on the suspicion of a mesenchymal tumor producing Fibroblast growth factor 23 (FGF23). Imaging revealed a small osteolytic, somatostatin receptor (SSTR) positive lesion containing calcifications in the alveolar process of the maxilla. No other SSTR-positive focus was found. A biopsy was performed by an oral and maxillofacial surgeon that revealed a calcifying epithelial odontogenic tumor (Pindborg tumor). This case shows that epithelial odontogenic tumors as an uncommon benign tumor entity can also be SSTR-positive.

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

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.

Selective Internal Radiation Therapy in Breast Cancer Liver Metastases: Outcome Assessment Applying a Prognostic Score.

Selective internal radiation therapy (SIRT) is a therapy option in patients with breast cancer liver metastasis (BCLM). This analysis aimed at identifying a prognostic score regarding overall survival (OS) after SIRT using routine pretherapeutic parameters. Retrospective analysis of 38 patients (age, 59 (39-84) years) with BCLM and 42 SIRT procedures. Cox regression for OS included clinical factors (age, ECOG and prior treatments), laboratory parameters, hepatic tumor load and dose reduction due to hepatopulmonary shunt. Elevated baseline ALT and/or AST was present if CTCAE grade ≥ 2 was fulfilled (>3 times the upper limit of normal). Median OS after SIRT was 6.4 months. In univariable Cox, ECOG ≥ 1 (hazard ratio (HR), 3.8), presence of elevated baseline ALT/AST (HR, 3.8), prior liver surgery (HR, 10.2), and dose reduction of 40% (HR, 8.1) predicted shorter OS (each p < 0.05). Multivariable Cox confirmed ECOG ≥ 1 (HR, 2.34; p = 0.012) and elevated baseline ALT/AST (HR, 4.16; p < 0.001). Combining both factors, median OS decreased from 19.2 months (0 risk factors; n = 14 procedures) to 5.9 months (1 factor; n = 20) or 2.2 months (2 factors; n = 8; p < 0.001). The proposed score may facilitate pretherapeutic identification of patients with unfavorable OS after SIRT. This may help to balance potential life prolongation with the hazards of invasive treatment and hospitalization.

Value of PET imaging for radiation therapy.

This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.