Radiomics Analysis of Multiparametric PET/MRI for N- and M-Staging in Patients with Primary Cervical Cancer.

PURPOSE: The aim of this study was to investigate the potential of multiparametric 18F-FDG PET/MR imaging as a platform for radiomics analysis and machine learning algorithms based on primary cervical cancers to predict N- and M-stage in patients. MATERIALS AND METHODS: A total of 30 patients with histopathological confirmation of primary and untreated cervical cancer were prospectively enrolled for a multiparametric 18F-FDG PET/MR examination, comprising a dedicated protocol for imaging of the female pelvis. The primary tumor in the uterine cervix was manually segmented on post-contrast T1-weighted images. Quantitative features were extracted from the segmented tumors using the Radiomic Image Processing Toolbox for the R software environment for statistical computing and graphics. 45 different image features were calculated from non-enhanced as well as post-contrast T1-weighted TSE images, T2-weighted TSE images, the ADC map, the parametric Ktrans, Kep, Ve and iAUC maps and PET images, respectively. Statistical analysis and modeling was performed using Python 3.5 and the scikit-learn software machine learning library for the Python programming language. RESULTS: Prediction of M-stage was superior when compared to N-stage. Prediction of M-stage using SVM with SVM-RFE as feature selection obtained the highest performance providing sensitivity of 91 % and specificity of 92 %. Using receiver operating characteristic (ROC) analysis of the pooled predictions, the area under the curve (AUC) was 0.97. Prediction of N-stage using RBF-SVM with MIFS as feature selection reached sensitivity of 83 %, specificity of 67 % and an AUC of 0.82. CONCLUSION: M- and N-stage can be predicted based on isolated radiomics analyses of the primary tumor in cervical cancers, thus serving as a template for noninvasive tumor phenotyping and patient stratification using high-dimensional feature vectors extracted from multiparametric PET/MRI data. KEY POINTS: · Radiomics analysis based on multiparametric PET/MRI enables prediction of the metastatic status of cervical cancers. · Prediction of M-stage is superior to N-stage. · Multiparametric PET/MRI displays a valuable platform for radiomics analyses .

Correlation of the apparent diffusion coefficient with the standardized uptake value in meningioma of the skull plane using [68]Ga-DOTATOC PET/MRI.

PURPOSE: To evaluate a correlation between an MRI-specific marker for cellular density [apparent diffusion coefficient (ADC)] and the expression of Somatostatin Receptors (SSTR) in patients with meningioma of the skull plane and orbital space. METHODS: 68 Ga-DOTATOC PET/MR imaging was performed in 60 Patients with suspected or diagnosed meningiomas of the skull base and eye socket. Analysis of ADC values succeeded in 32 patients. ADC values (ADC mean and ADC min ) were analyzed using a polygonal region of interest. Tracer-uptake of target lesions was assessed according to corresponding maximal (SUV max ) and mean (SUV mean ) values. Correlations between assessed parameters were evaluated using the Pearson correlation coefficient. RESULTS: One out of 32 patients (3%) was diagnosed with lymphoma by histopathological examination and therefore excluded from further analysis. Median ADC mean amounted to 822 × 10 -5  mm²/s -1 (95% CI: 570-1497) and median ADC min was 493 × 10 -5 mm 2 /s -1 (95% CI: 162-783). There were no significant correlations between SUV max and ADC min (r = 0.60; P  = 0.76) or ADC mean (r = -0.52; P  = 0.79), respectively. However, Pearson's test showed a weak, inverse but insignificant correlation between ADC mean and SUV mean (r = -0.33; P  = 0.07). CONCLUSION: The presented data displays no relevant correlations between increased SSTR expression and cellularity in patients with meningioma of the skull base. SSTR-PET and DWI thus may offer complementary information on tumor characteristics of meningioma.

Evaluation of [68Ga]-DOTATOC PET/MRI in Patients with Meningioma of the Subcranial and Intraorbital Space.

Meningiomas are known to express somatostatin receptor (SSTR) type 2 to a high degree. Therefore, radiolabeled somatostatin analogs, such as DOTATOC, have been introduced for PET imaging of meningiomas. However, the benefit of hybrid SSTR PET/MRI is still debated. Here, we report our experience with [68Ga]-DOTATOC PET/MRI. Methods: PET/MRI was performed in 60 patients with suspected or diagnosed meningiomas of the skull plane and eye socket. Acquired datasets were reported by 2 independent readers regarding local tumor extent and signal characteristics. Histopathologic results and follow-up imaging served as the reference standard. SUVs of target lesions were analyzed according to the corresponding maximal tracer uptake. The diagnostic accuracy of PET/MRI and conventional MRI was determined independently and compared with the reference standard. Results: In total, 60 target lesions were identified, with 54 considered to be meningiomas according to the reference standard. Sensitivity and specificity of PET/MRI versus MRI alone were 95% versus 96% and 75% versus 66%, respectively. The McNemar test was not able to distinguish any differences between PET/MRI and the reference standard or MRI and the reference standard. No differences were found between the 2 modalities with respect to local infiltration. Conclusion: SSTR PET/MRI and MRI yielded similar accuracy for the detection of meningiomas of the skull base and intraorbital space. Here, sequential low-dose SSTR PET/CT might be helpful for the planning of radioligand therapy or radiotherapy.

Adipopenia in body composition analysis: a promising imaging biomarker and potential predictive factor for patients undergoing transjugular intrahepatic portosystemic shunt placement.

OBJECTIVE: Body tissue composition plays a crucial role in the multisystemic processes of advanced liver disease and has been shown to be influenced by transjugular intrahepatic portosystemic shunt (TIPS). A differentiated analysis of the various tissue compartments has not been performed until now. The purpose of this study was to evaluate the value of imaging biomarkers derived from automated body composition analysis (BCA) to predict clinical and functional outcome. METHODS: A retrospective analysis of 56 patients undergoing TIPS procedure between 2013 and 2021 was performed. BCA on the base of pre-interventional CT examination was used to determine quantitative data as well as ratios of bone, muscle and fat masses. Furthermore, a BCA-derived sarcopenia marker was investigated. Regarding potential correlations between BCA imaging biomarkers and the occurrence of hepatic encephalopathy (HE) as well as 1-year survival, an exploratory analysis was conducted. RESULTS: No BCA imaging biomarker was associated with the occurrence of HE after TIPS placement. However, there were significant differences in alive and deceased patients regarding the BCA-derived sarcopenia marker (alive: 1.60, deceased: 1.83, p = 0.046), ratios of intra- and intermuscular fat/skeletal volume (alive: 0.53, deceased: 0.31, p = 0.015) and intra- and intermuscular fat/muscle volume (alive: 0.21, deceased: 0.14, p = 0.031). CONCLUSION: A lower amount of intra- and intermuscular adipose tissue might have protective effects regarding liver derived complications and survival. ADVANCES IN KNOWLEDGE: Precise characterization of body tissue components with automated BCA might provide prognostic information in patients with advanced liver disease undergoing TIPS procedure.

Utility of Integrated PET/MRI for the Primary Diagnostic Work-Up of Patients with Ewing Sarcoma: Preliminary Results.

BACKGROUND: This study was conducted to evaluate the clinical applicability of integrated PET/MRI for staging and monitoring the effectiveness of neoadjuvant chemotherapy in Ewing sarcoma patients. METHODS: A total of 11 juvenile patients with confirmed Ewing sarcoma, scheduled for induction polychemotherapy, were prospectively enrolled for a PET/MR examination before, during and after the end of treatment. Two experienced physicians analysed the imaging datasets. They were asked to perform a whole-body staging in all three examinations and to define treatment response according to the RECIST1.1 and PERCIST criteria for each patient. RESULTS: In eight patients lymph node and/or distant metastases were detected at initial diagnosis. According to the reference standard, three patients achieved complete response, six patients partial response, and one patient showed stable disease while another patient showed progressive disease. RECIST1.1 categorized the response to treatment in 5/11 patients correctly and showed a tendency to underestimate the response to treatment in the remaining six patients. PERCIST defined response to treatment in 9/11 patients correctly and misclassified two patients with a PR as CR. CONCLUSION: PET/MRI may serve as a valuable imaging tool for primary staging and response assessment of juvenile patients with Ewing sarcoma to induction chemotherapy, accompanied by a reasonable radiation dose for the patient.

Is preoperative CT-guided biopsy a valuable tool in the diagnostic workup of patients with visceral and retroperitoneal sarcoma?

PURPOSE: We aimed to analyze the diagnostic accuracy of preoperative CT-guided biopsy to identify patients that might profit from neoadjuvant chemotherapy in a specialized high-volume sarcoma center. MATERIAL AND METHODS: We retrospectively reviewed all patients with suspected soft tissue tumors of the abdomen cavity including the retroperitoneum, who received CT-guided biopsy followed by surgical tumor resection. Sensitivity, specificity, PPV and NPV were calculated in all patients with abdominal sarcomas at our hospital. A subgroup analysis was performed for patients with liposarcoma. RESULTS: A total of 82 patients (35 female, 47 male, age: 62.0 ± 14.7) received preoperative CT-guided biopsy followed by surgical resection. Overall accordance of CT-guided biopsy to identify final histology was 77 %. CT-guided biopsy revealed the diagnosis of liposarcoma in 23 patients whereas final analysis of the surgical specimen identified liposarcoma in 29 patients. Here, sensitivity, specificity, PPV and NPV was 79.3 %, 100.0 %, 100.0 % and 89.8 % respectively. Subgroup analysis revealed a better accuracy for correctly identifying patients with well-differentiated liposarcoma than patients with dedifferentiated liposarcoma (75.0 % vs 62.5 %). In patients with other sarcoma, sensitivity, specificity, PPV, NPV and diagnostic accuracy was 87.5 %, 95.5 %, 82.4 % and 96.9 %, respectively. CONCLUSION: CT-guided biopsy in a specialized high-volume sarcoma center is an accurate and effective method to assess patients with abdominal sarcoma and especially abdominal liposarcoma. Therefore, it is an indispensable tool in the pretherapeutic workup process. Nevertheless, our study underlines the previously reported difficulties in dedifferentiated liposarcoma diagnostics, whereby these patient cohort would profit the most from a neoadjuvant therapy regime.

Radiation exposure, organ and effective dose of CT-guided liver biopsy as a function of lesion depth and size.

Computed tomography (CT)-guided percutaneous biopsies play an important role in the diagnostic workup of liver lesions. Because radiation dose accumulates rapidly due to repeated image acquisition in a relatively small scan area, analysing radiation exposure is critical for improving radiation protection of CT-guided interventions. The aim of this study was to assess the radiation dose of CT-guided liver biopsies and the influence of lesion parameters, and to establish a local diagnostic reference level (DRL). In this observational retrospective cohort study, dose data of 60 CT-guided liver biopsies between September 2016 and July 2017 were analysed. Radiation exposure was reported for volume-weighted CT dose index (CTDIvol), size-specific dose estimate (SSDE), dose-length product (DLP) and effective dose (ED). Radiation dose of CT-guided liver biopsy was (median (interquartile range)): CTDIvol9.91 mGy (8.33-11.45 mGy), SSDE 10.42 mGy (9.39-11.70 mGy), DLP 542 mGy cm (410-733 mGy cm), ED 8.52 mSv (7.17-13.25 mSv). Radiation exposure was significantly higher in biopsies of deep liver lesions compared to superficial lesions (DLP 679 ± 285 mGy cm vs. 497 ± 167 mGy cm,p= 0.0046). No significant dose differences were observed for differences in lesion or needle size. With helical CT spirals additional to the biopsy-guiding axial CT scans, radiation exposure was significantly increased: 797 ± 287 mGy cm vs. 495 ± 162 mGy cm,p< 0.0001. The local DRL is CTDIvol9.91 mGy, DLP 542 mGy cm. Radiation dose is significantly increased in biopsies of deeper liver lesions compared with superficial lesions. Interventions with additional biopsy-guiding CT spirals lead to higher radiation doses. This study provides a detailed analysis of local radiation doses for CT-guided liver biopsies and provides a benchmark for optimising radiation protection in interventional radiology.

Streamlining Patient Management of Suspected COVID-19 Patients in the Emergency Department: Incorporation of Pulmonary CT Angiography into the Triaging Algorithm.

Purpose: To evaluate the use of pulmonary computed tomography (CT) angiography during initial admission at an emergency department (ED), to identify COVID-19 patients with accompanying pulmonary embolism (PE) and its impact on clinical management. Methods: We performed a retrospective analysis of COVID-19 patients that underwent pulmonary CT angiography at the ED. CT scans were evaluated for the presence and extent of PE and for imaging changes suspicious of COVID-19. Patients were subdivided into two groups: (1) Group A consisted of patients with proven COVID-19 based on real-time polymerase chain reaction (RT-PCR), and (2) Group B of patients suspected for COVID-19, comprising patients positive on RT-PCR and/or COVID-19-suspicious CT findings. To assess the differences between patients with and without pulmonary embolism, Fisher's exact test was used. Results: A total of 308 patients were admitted to the ED for diagnostic work-up of dyspnea and suspected COVID-19, and 95 patients underwent pulmonary CT angiography. PE was detected in 13.6% (3/22) of patients in Group A and 20.7% (6/29) in Group B. No significant differences were observed between patients with and without PE concerning hospitalization (Group B: 100% (6/6) vs. 91.3% (21/23)), the necessity of oxygen therapy (Group B: 66% (4/6) vs. 43.5% (10/23)), and death (Group B: 33% (2/6) vs. 4.3% (1/23) p > 0.05, respectively). Conclusions: In 20.7% of COVID-19 patients, PE was detected upon admission to the ED. Although the incorporation of early pulmonary CT angiography in patients suspicious of COVID-19 may be beneficial to identify concomitant PE, further studies are necessary to corroborate these findings.

Multiparametric 18F-FDG PET/MRI-Based Radiomics for Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.

BACKGROUND: The aim of this study was to assess whether multiparametric 18F-FDG PET/MRI-based radiomics analysis is able to predict pathological complete response in breast cancer patients and hence potentially enhance pretherapeutic patient stratification. METHODS: A total of 73 female patients (mean age 49 years; range 27-77 years) with newly diagnosed, therapy-naive breast cancer underwent simultaneous 18F-FDG PET/MRI and were included in this retrospective study. All PET/MRI datasets were imported to dedicated software (ITK-SNAP v. 3.6.0) for lesion annotation using a semi-automated method. Pretreatment biopsy specimens were used to determine tumor histology, tumor and nuclear grades, and immunohistochemical status. Histopathological results from surgical tumor specimens were used as the reference standard to distinguish between complete pathological response (pCR) and noncomplete pathological response. An elastic net was employed to select the most important radiomic features prior to model development. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated for each model. RESULTS: The best results in terms of AUCs and NPV for predicting complete pathological response in the entire cohort were obtained by the combination of all MR sequences and PET (0.8 and 79.5%, respectively), and no significant differences from the other models were observed. In further subgroup analyses, combining all MR and PET data, the best AUC (0.94) for predicting complete pathologic response was obtained in the HR+/HER2- group. No difference between results with/without the inclusion of PET characteristics was observed in the TN/HER2+ group, each leading to an AUC of 0.92 for all MR and all MR + PET datasets. CONCLUSION: 18F-FDG PET/MRI enables comprehensive high-quality radiomics analysis for the prediction of pCR in breast cancer patients, especially in those with HR+/HER2- receptor status.

Clinical Use of PET/MR in Oncology: An Update.

The combination of PET and MRI is one of the recent advances of hybrid imaging. Yet to date, the adoption rate of PET/MRI systems has been rather slow. This seems to be partially caused by the high costs of PET/MRI systems and the need to verify an incremental benefit over PET/CT or sequential PET/CT and MRI. In analogy to PET/CT, the MRI part of PET/MRI was primarily used for anatomical imaging. Though this can be advantageous, for example in diseases where the superior soft tissue contrast of MRI is highly appreciated, the sole use of MRI for anatomical orientation lessens the potential of PET/MRI. Consequently, more recent studies focused on its multiparametric potential and employed diffusion weighted sequences and other functional imaging sequences in PET/MRI. This integration puts the focus on a more wholesome approach to PET/MR imaging, in terms of releasing its full potential for local primary staging based on multiparametric imaging and an included one-stop shop approach for whole-body staging. This approach as well as the implementation of computational analysis, in terms of radiomics analysis, has been shown valuable in several oncological diseases, as will be discussed in this review article.

Evaluation of the Predictive Potential of 18F-FDG PET and DWI Data Sets for Relevant Prognostic Parameters of Primary Soft-Tissue Sarcomas.

BACKGROUND: To evaluate the potential of simultaneously acquired 18F-FDG PET- and MR-derived quantitative imaging data sets of primary soft-tissue sarcomas for the prediction of neoadjuvant treatment response, the metastatic status and tumor grade. METHODS: A total of 52 patients with a high-risk soft-tissue sarcoma underwent a 18F-FDG PET/MR examination within one week before the start of neoadjuvant treatment. For each patient, the maximum tumor size, metabolic activity (SUVs), and diffusion-restriction (ADC values) of the tumor manifestations were determined. A Mann-Whitney-U test was used, and ROC analysis was performed to evaluate the potential to predict histopathological treatment response, the metastatic status or tumor grade. The results from the histopathological analysis served as reference standard. RESULTS: Soft-tissue sarcomas with a histopathological treatment response revealed a significantly higher metabolic activity than tumors in the non-responder group. In addition, grade 3 tumors showed a significant higher 18F-FDG uptake than grade 2 tumors. Furthermore, no significant correlation between the different outcome variables and tumor size or calculated ADC-values could be identified. CONCLUSION: Measurements of the metabolic activity of primary and untreated soft-tissue sarcomas could non-invasively deliver relevant information that may be used for treatment planning and risk-stratification of high-risk sarcoma patients in a pretherapeutic setting.

Multiparametric Integrated 18F-FDG PET/MRI-Based Radiomics for Breast Cancer Phenotyping and Tumor Decoding.

BACKGROUND: This study investigated the performance of simultaneous 18F-FDG PET/MRI of the breast as a platform for comprehensive radiomics analysis for breast cancer subtype analysis, hormone receptor status, proliferation rate and lymphonodular and distant metastatic spread. METHODS: One hundred and twenty-four patients underwent simultaneous 18F-FDG PET/MRI. Breast tumors were segmented and radiomic features were extracted utilizing CERR software following the IBSI guidelines. LASSO regression was employed to select the most important radiomics features prior to model development. Five-fold cross validation was then utilized alongside support vector machines, resulting in predictive models for various combinations of imaging data series. RESULTS: The highest AUC and accuracy for differentiation between luminal A and B was achieved by all MR sequences (AUC 0.98; accuracy 97.3). The best results in AUC for prediction of hormone receptor status and proliferation rate were found based on all MR and PET data (ER AUC 0.87, PR AUC 0.88, Ki-67 AUC 0.997). PET provided the best determination of grading (AUC 0.71), while all MR and PET analyses yielded the best results for lymphonodular and distant metastatic spread (0.81 and 0.99, respectively). CONCLUSION: 18F-FDG PET/MRI enables comprehensive high-quality radiomics analysis for breast cancer phenotyping and tumor decoding, utilizing the perks of simultaneously acquired morphologic, functional and metabolic data.

Comparison of pre- and post-contrast-enhanced attenuation correction using a CAIPI-accelerated T1-weighted Dixon 3D-VIBE sequence in 68Ga-DOTATOC PET/MRI.

OBJECTIVES: To investigate the influence of contrast agent administration on attenuation correction (AC) based on a CAIPIRINHA (CAIPI)-accelerated T1-weighted Dixon 3D-VIBE sequence in 68Ga-DOTATOC PET/MRI. MATERIAL AND METHODS: Fifty-one patients with neuroendocrine tumors underwent whole-body 68Ga-DOTATOC PET/MRI for tumor staging. Two PET reconstructions were performed using AC-maps that were created using a high-resolution CAIPI-accelerated Dixon-VIBE sequence with an additional bone atlas and truncation correction using the HUGE (B0 homogenization using gradient enhancement) method before and after application of Gadolinium (Gd)-based contrast agent. Standardized uptake values (SUVs) of 21 volumes of interest (VOIs) were compared between in both PET data sets per patient. A student's t-test for paired samples was performed to test for potential differences between both AC-maps and both reconstructed PET data sets. Bonferroni correction was performed to prevent α-error accumulation, p < 0.0024 was considered to indicate statistical significance. RESULTS: Significant quantitative differences between SUVmax were found in the perirenal fat (19.65 ±â€¯48.03 %, p < 0.0001), in the axillary fat (17.46 ±â€¯63.67 %, p < 0.0001) and in the dorsal subcutaneous fat on level of lumbar vertebral body L4 (10.26 ±â€¯25.29 %, p < 0.0001). Significant differences were also evident in the lungs apical (5.80 ±â€¯10.53 %, p < 0.0001), dorsal at the level of the pulmonary trunk (15.04 ±â€¯19.09 %, p < 0.0001) and dorsal in the basal lung (51.27 ±â€¯147.61 %, p < 0.0001). CONCLUSION: The administration of (Gd)-contrast agents in this study has shown a considerable influence on the AC-maps in PET/MRI and, consequently impacted quantification in the reconstructed PET data. Therefore, dedicated PET/MRI staging protocols have to be adjusted so that AC-map acquisition is performed prior to contrast agent administration.

Evaluation of 18F-FDG PET and DWI Datasets for Predicting Therapy Response of Soft-Tissue Sarcomas Under Neoadjuvant Isolated Limb Perfusion.

Our purpose was to evaluate and compare the clinical utility of simultaneously obtained quantitative 18F-FDG PET and diffusion-weighted MRI datasets for predicting the histopathologic response of soft-tissue sarcoma (STS) to neoadjuvant isolated limb perfusion (ILP). Methods: In total, 37 patients with a confirmed STS of the extremities underwent 18F-FDG PET/MRI before and after ILP with melphalan and tumor necrosis factor-α. For each patient, the maximum tumor size, metabolic activity (SUV), and diffusion restriction (apparent diffusion coefficient, ADC) were determined in pre- and posttherapeutic examinations, and percentage changes during treatment were calculated. Mann-Whitney U testing and receiver-operating-characteristic analysis were used to compare the results of the different quantitative parameters to predict the histopathologic response to therapy. Results from histopathologic analysis after tumor resection served as the reference standard, and patients were defined as responders or nonresponders based on the grading scale by Salzer-Kuntschik. Results: Histopathologic analysis categorized 22 (59%) patients as responders (grades I-III) and 15 (41%) as nonresponders (grades IV-VI). Under treatment, tumors in responders showed a mean reduction in size (-9.7%) and metabolic activity (SUVpeak, -51.9%; SUVmean, -43.8%), as well as an increase of the ADC values (ADCmin, +29.4%; ADCmean, +32.8%). The percentage changes in nonresponders were -6.2% in tumor size, -17.3% in SUVpeak, -13.9% in SUVmean, +15.3% in ADCmin, and +14.6% in ADCmean Changes in SUV and ADCmean significantly differed between responders and nonresponders (<0.01), whereas differences in tumor size and ADCmin did not (>0.05). The corresponding AUCs were 0.63 for tumor size, 0.87 for SUVpeak, 0.82 for SUVmean, 0.63 for ADCmin, 0.84 for ADCmean, and 0.89 for ratio of ADCmean to SUVpeakConclusion: PET- and MRI-derived quantitative parameters (SUV and ADCmean) and their combination performed well in predicting the histopathologic therapy response of STS to neoadjuvant ILP. Therefore, integrated PET/MRI could serve as a valuable tool for pretherapeutic assessment as well as monitoring of neoadjuvant treatment strategies of STS.

Correlation of the apparent diffusion coefficient (ADC) and standardized uptake values (SUV) with overall survival in patients with primary non-small cell lung cancer (NSCLC) using 18F-FDG PET/MRI.

OBJECTIVES: To investigate if the combined analysis of the apparent diffusion coefficient (ADC) and standardized uptake values (SUV) measured in 18F-fluoro-deoxy-glucose-positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI) examinations correlates with overall survival in non-small cell lung cancer (NSCLC). MATERIAL AND METHODS: A total of 92 patients with newly diagnosed, histopathologically proven NSCLC (44 women and 48 men, mean age 63.1 ±â€¯9.9y) underwent a dedicated thoracic 18F-FDG PET/MRI examination. A manually drawn polygonal region of interest (ROI), encompassing the entire primary tumor mass, was placed over the primary tumor on fused PET/MR images to determine the maximum and mean standardized uptake values (SUVmax; SUVmean) as well as on the ADC maps to quantify the mean and minimum ADC values (ADCmean, ADCmin). The impact of these parameters to predict patient's overall survival was tested using hazard ratios (HR). Pearson's correlation coefficients were calculated to assess dependencies between the different values. A p-value < 0.05 indicated statistical significance. RESULTS: In all 92 patients (n = 59 dead at time of retrospective data collection, mean time till death: 19 ±â€¯16 month, n = 33 alive, mean time to last follow-up: 56 ±â€¯22 month) the Hazard ratios (HR) as independent predictors for overall survival (OS) of SUVmax were 2.37 (95 % CI: 1.23-4.59, p = 0.008) and for SUVmean 1.85 (95 % CI: 1.05-3.26, p = 0.03) while ADCmin showed a HR of 0.95 (95 % CI: 0.57-1.59, p = 0.842) and ADCmean a HR of 2.01 (95 % CI: 1.2-3.38, p = 0.007). Furthermore, a combined analysis for SUVmax/ADCmean, SUVmax / ADCmin and SUVmean/ADCmean revealed a HR of 2.01 (95 % CI: 1.10-3.67, p = 0.02), 1.75 (95 % CI: 0.97-3.15, p = 0.058) and 1.78 (95 % CI: 1.02-3.10, p = 0.04). CONCLUSION: SUVmax and SUVmean of the primary tumor are predictors for OS in therapy-naive NSCLC patients, whereas the combined analysis of SUV and ADC values does not improve these results. Therefore, ADC values do not further enhance the diagnostic value of SUV as a prognostic biomarker in NSCLC.

Diagnostic Performance of Simultaneous [18F]-FDG PET/MR for Assessing Endoscopically Active Inflammation in Patients with Ulcerative Colitis: A Prospective Study.

Background: To investigate the diagnostic performance of simultaneous 18F-fluoro-deoxyglucose ([18F]-FDG) PET/MR enterography in assessing and grading endoscopically active inflammation in patients with ulcerative colitis. Methods: 50 patients underwent PET/MR 24 h before ileocolonoscopy. Inflammatory activities of bowel segments were evaluated with both Mayo endoscopic subscore and Nancy histologic index. MR, DWI (Diffusion-weighted imaging) and PET were utilized as qualitative parameters for detecting endoscopically active inflammation. SUVmaxQuot in each segment (maximum of standard uptake value relative to liver) was calculated to quantify inflammation. Results: In the study arm without bowel purgation, combined reading of PET and MR resulted in significantly increased specificity against each submodality alone (0.944 vs. 0.82 for MR and 0.843 for PET, p < 0.05) and highest overall accuracy. In the study arm with bowel purgation, the significantly lower specificity of PET (0.595) could be markedly improved by a combined reading of PET and MR. Metabolic conditions in bowel segments with both endoscopic and histological remission were significantly lower than in segments with endoscopic remission but persistent microscopic inflammation (SUVmaxQuot 0.719 vs. 0.947, p < 0.001). SUVmaxQuot correlated highly with Mayo endoscopic subscore (ρ = 0.718 and 0.606) and enabled grading of inflammatory activity. Conclusions: Simultaneous [18F]-FDG PET/MR may be considered as an alternative to endoscopy in clinical trials.

Assessment of Suspected Malignancy or Infection in Immunocompromised Patients After Solid Organ Transplantation by [18F]FDG PET/CT and [18F]FDG PET/MRI.

PURPOSE: To study the value of 2-deoxy-2-[18F]fluoro-D-glucose([18F]FDG) positron emission tomography/computed tomography (PET/CT) and [18F]FDG positron emission tomography/magnetic resonance imaging (PET/MRI) in assessing immunocompromised patients with suspected malignancy or infection. METHODS: [18F]FDG-PET/CT and [18F]FDG-PET/MRI examinations of patients who were immunocompromised after receiving lung, heart, pancreas, kidney, liver, or combined kidney-liver transplants were analyzed in this retrospective study. Patients underwent whole-body hybrid-imaging because of clinical signs of malignancy and/or infection. Findings were assessed by molecular features ([18F]FDG-uptake) and morphological changes. The final diagnosis, which was arrived at after review of clinical, laboratory, and histopathologic analyses and follow-up imaging studies, served as the reference standard. RESULTS: Altogether, (i) 28 contrast-enhanced [18F]FDG-PET/CT scans (CE-PET/CT), (ii) 33 non-contrast [18F]FDG-PET/CT scans (NC-PET/CT), and (iii) 18 [18F]FDG-PET/MRI scans were included. Additionally, 12/62 patients underwent follow-up PET imaging to rule out vital tumor or metabolic active inflammatory processes. CE-PET/CT exhibited 94.4% sensitivity, 80.0% specificity, 89.5% positive predictive value (PPV), 88.9% negative predictive value (NPV), and 89.3% accuracy with regard to the reference standard. NC-PET/CT exhibited 91.3% sensitivity, 80.0% specificity, 91.3% PPV, 80.0% NPV, and 87.9% accuracy. PET/MRI exhibited 88.6% sensitivity, 99.2% specificity, 99.6% PPV, 81.3% NPV, and 94.4% accuracy. Exact McNemar statistical test (one-sided) showed significant difference between the CT-/MR-component alone and the integrated PET/CT and PET/MRI for diagnosis of malignancy or infection (p value < 0.001). Radiation exposure was 4- to 7-fold higher with PET/CT than with PET/MRI. CONCLUSION: For immunocompromised patients with clinically unresolved symptoms, to rule out vital tumor manifestations or metabolic active inflammation, [18F]FDG-PET/MRI, CE-[18F]FDG-PET/CT, and NC-[18F]FDG-PET/CT exhibit excellent performance in diagnosing malignancy or infection. The main strength of PET/MRI is its considerably lower level of radiation exposure than that associated with PET/CT.

A rapid volume of interest-based approach of radiomics analysis of breast MRI for tumor decoding and phenotyping of breast cancer.

BACKGROUND: Recently, radiomics has emerged as a non-invasive, imaging-based tissue characterization method in multiple cancer types. One limitation for robust and reproducible analysis lies in the inter-reader variability of the tumor annotations, which can potentially cause differences in the extracted feature sets and results. In this study, the diagnostic potential of a rapid and clinically feasible VOI (Volume of Interest)-based approach to radiomics is investigated to assess MR-derived parameters for predicting molecular subtype, hormonal receptor status, Ki67- and HER2-Expression, metastasis of lymph nodes and lymph vessel involvement as well as grading in patients with breast cancer. METHODS: A total of 98 treatment-naïve patients (mean 59.7 years, range 28.0-89.4) with BI-RADS 5 and 6 lesions who underwent a dedicated breast MRI prior to therapy were retrospectively included in this study. The imaging protocol comprised dynamic contrast-enhanced T1-weighted imaging and T2-weighted imaging. Tumor annotations were obtained by drawing VOIs around the primary tumor lesions followed by thresholding. From each segmentation, 13.118 quantitative imaging features were extracted and analyzed with machine learning methods. Validation was performed by 5-fold cross-validation with 25 repeats. RESULTS: Predictions for molecular subtypes obtained AUCs of 0.75 (HER2-enriched), 0.73 (triple-negative), 0.65 (luminal A) and 0.69 (luminal B). Differentiating subtypes from one another was highest for HER2-enriched vs triple-negative (AUC 0.97), followed by luminal B vs triple-negative (0.86). Receptor status predictions for Estrogen Receptor (ER), Progesterone Receptor (PR) and Hormone receptor positivity yielded AUCs of 0.67, 0.69 and 0.69, while Ki67 and HER2 Expressions achieved 0.81 and 0.62. Involvement of the lymph vessels could be predicted with an AUC of 0.8, while lymph node metastasis yielded an AUC of 0.71. Models for grading performed similar with an AUC of 0.71 for Elston-Ellis grading and 0.74 for the histological grading. CONCLUSION: Our preliminary results of a rapid approach to VOI-based tumor-annotations for radiomics provides comparable results to current publications with the perks of clinical suitability, enabling a comprehensive non-invasive platform for breast tumor decoding and phenotyping.

Radiomics Analysis of Multiparametric PET/MRI for N- and M-Staging in Patients with Primary Cervical Cancer.

ZIELSETZUNG: Ziel dieser Studie war die Evaluierung des prädiktiven Potenzials der Radiomics-Analyse zur Bestimmung des N- und M-Stadiums des primären Zervixkarzinoms anhand multiparametrischer 18F-FDG-PET/MRT-Bildgebung. MATERIAL UND METHODEN: 30 Patientinnen mit einem histologisch gesicherten, primären und therapienaiven Zervixkarzinom unterzogen sich einer multiparametrischen 18F-FDG-PET/MRT-Untersuchung unter Verwendung eines dedizierten Untersuchungsprotokolls des weiblichen Beckens. Nach Segmentierung der Primärtumoren wurden quantitative Bildparameter mittels der Radiomic-Image-Processing-Toolbox bestimmt. Insgesamt wurden 45 verschiedene quantitative Bildmerkmale jeweils anhand der T2-gewichteten TSE-Sequenzen, der nativen und kontrastmittelgestützten T1-gewichteten TSE-Sequenzen, der ADC-Map, verschiedenen Perfusionsparametern (Ktrans, Kep, Ve and iAUC) und den 18F-FDG-PET-Datensätzen für jeden Tumor extrahiert. Die statistische Analyse zur Bestimmung des N- und M-Stadiums erfolgte unter der Verwendung der Python 3.5 und Scikit-learn-Software-Bibliothek für maschinelles Lernen. ERGEBNISSE: Insgesamt zeigte sich eine höhere Genauigkeit zur Prädiktion des korrekten M-Stadiums im Vergleich zum N-Stadium. Zur Prädiktion des korrekten M-Stadiums zeigten sich unter der Verwendung von SVM und SVM-RFE zur Feature-Auswahl die besten Ergebnisse mit einer Sensitivität von 91 %, einer Spezifität von 92 % und einer Fläche unter der Kurve (AUC) von 0,97. Die höchste Genauigkeit für die Bestimmung des N-Stadiums erfolgte unter der Verwendung von RBF-SVM und MIFS zur Feature-Auswahl mit einer Sensitivität von 83 %, einer Spezifität von 67 % und einer Fläche unter der Kurve (AUC) von 0,82. SCHLUSSFOLGERUNG: Die Radiomics-Analyse von multiparametrischen PET/MR-Datensätzen ermöglicht eine präzise Prädiktion des M- und N-Stadiums von Patientinnen mit primärem Zervixkarzinom und könnte damit supportiv zur nichtinvasiven Tumor-Phänotypisierung und Patientenstratifizierung eingesetzt werden. KERNAUSSAGEN: · Die Radiomics-Analyse der multiparametrischen PET/MRT ermöglicht die Prädiktion des Metastasierungsstatus des Zervixkarzinoms.. · Die Prädiktion des M-Stadiums ist der Prädiktion des N-Stadiums überlegen.. · Die multiparametrische PET/MRT bietet eine valide Plattform für Radiomics-Analysen.. CITATION FORMAT: · Umutlu L, Nensa F, Demircioglu A et al. Radiomics Analysis of Multiparametric PET/MRI for N- and M-Staging in Patients with Primary Cervical Cancer. Fortschr Röntgenstr 2020; 192: 754 - 763.