Total Body PET-CT Protocols in Oncology.

Recently developed long axial field of view (LAFOV) PET-CT scanners, including total body scanners, are already in use in a few centers worldwide. These systems have some major advantages over standard axial field of view (SAFOV) PET-CT scanners, mainly due to up to 20 times higher sensitivity and therefore improved lesion detectability. Other advantages are the reduction of the PET acquisition time for a static whole-body measurement, the reduction of the administered radiotracer dose, and the ability to perform delayed scans with good image quality, which is important for imaging radionuclides with long half-lives and pharmaceuticals with long biodistribution times, such as 89Zr-labeled antibodies. The reduction of the applied tracer dose leads to less radiation exposure and may facilitate longitudinal studies, especially in oncological patients, for the evaluation of therapy. The reduction in acquisition time for a static whole body (WB) study allows a markedly higher patient throughput. Furthermore, LAFOV PET-CT scanners enable for the first-time WB dynamic PET scanning and WB parametric imaging with an improved image quality due to increased sensitivity and time resolution. WB tracer kinetics is of particular interest for the characterization of novel radiopharmaceuticals and for a better biological characterization of cancer diseases, as well as for a more accurate assessment of the response to new targeted therapies. Further technological developments based on artificial intelligence (AI) approaches are underway and may in the future allow CT-less attenuation correction or ultralow dose CT for attenuation correction as well as segmentation algorithms for the evaluation of total metabolic tumor volume. The aim of this review is to present dedicated PET acquisition protocols for oncological studies with LAFOV scanners, including static and dynamic acquisition as well as parametric scans, and to present literature data to date on this topic.

Artificial intelligence-based, volumetric assessment of the bone marrow metabolic activity in [18F]FDG PET/CT predicts survival in multiple myeloma.

PURPOSE: Multiple myeloma (MM) is a highly heterogeneous disease with wide variations in patient outcome. [18F]FDG PET/CT can provide prognostic information in MM, but it is hampered by issues regarding standardization of scan interpretation. Our group has recently demonstrated the feasibility of automated, volumetric assessment of bone marrow (BM) metabolic activity on PET/CT using a novel artificial intelligence (AI)-based tool. Accordingly, the aim of the current study is to investigate the prognostic role of whole-body calculations of BM metabolism in patients with newly diagnosed MM using this AI tool. MATERIALS AND METHODS: Forty-four, previously untreated MM patients underwent whole-body [18F]FDG PET/CT. Automated PET/CT image segmentation and volumetric quantification of BM metabolism were based on an initial CT-based segmentation of the skeleton, its transfer to the standardized uptake value (SUV) PET images, subsequent application of different SUV thresholds, and refinement of the resulting regions using postprocessing. In the present analysis, ten different uptake thresholds (AI approaches), based on reference organs or absolute SUV values, were applied for definition of pathological tracer uptake and subsequent calculation of the whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Correlation analysis was performed between the automated PET values and histopathological results of the BM as well as patients' progression-free survival (PFS) and overall survival (OS). Receiver operating characteristic (ROC) curve analysis was used to investigate the discrimination performance of MTV and TLG for prediction of 2-year PFS. The prognostic performance of the new Italian Myeloma criteria for PET Use (IMPeTUs) was also investigated. RESULTS: Median follow-up [95% CI] of the patient cohort was 110 months [105-123 months]. AI-based BM segmentation and calculation of MTV and TLG were feasible in all patients. A significant, positive, moderate correlation was observed between the automated quantitative whole-body PET/CT parameters, MTV and TLG, and BM plasma cell infiltration for all ten [18F]FDG uptake thresholds. With regard to PFS, univariable analysis for both MTV and TLG predicted patient outcome reasonably well for all AI approaches. Adjusting for cytogenetic abnormalities and BM plasma cell infiltration rate, multivariable analysis also showed prognostic significance for high MTV, which defined pathological [18F]FDG uptake in the BM via the liver. In terms of OS, univariable and multivariable analysis showed that whole-body MTV, again mainly using liver uptake as reference, was significantly associated with shorter survival. In line with these findings, ROC curve analysis showed that MTV and TLG, assessed using liver-based cut-offs, could predict 2-year PFS rates. The application of IMPeTUs showed that the number of focal hypermetabolic BM lesions and extramedullary disease had an adverse effect on PFS. CONCLUSIONS: The AI-based, whole-body calculations of BM metabolism via the parameters MTV and TLG not only correlate with the degree of BM plasma cell infiltration, but also predict patient survival in MM. In particular, the parameter MTV, using the liver uptake as reference for BM segmentation, provides solid prognostic information for disease progression. In addition to highlighting the prognostic significance of automated, global volumetric estimation of metabolic tumor burden, these data open up new perspectives towards solving the complex problem of interpreting PET scans in MM with a simple, fast, and robust method that is not affected by operator-dependent interventions.

Combined whole-body dynamic and static PET/CT with low-dose [18F]PSMA-1007 in prostate cancer patients.

AIM: In addition to significant improvements in sensitivity and image quality, the recent introduction of long axial field-of-view (LAFOV) PET/CT scanners has enabled dynamic whole-body imaging for the first time. We aim herein to determine an appropriate acquisition time range for static low-dose [18F]PSMA-1007 PET imaging and to investigate the whole-body pharmacokinetics of [18F]PSMA-1007 by dynamic PET with the LAFOV Biograph Vision Quadra PET/CT in a group of prostate cancer patients. METHODOLOGY: In total, 38 prostate cancer patients were enrolled in the analysis for staging or re-staging purposes. Thirty-four patients underwent dynamic whole-body PET/CT (60 min) followed by static whole-body PET/CT and four patients underwent static whole-body PET/CT only. The activity applied was 2 MBq/kg [18F]PSMA-1007. The static PET images of 10-min duration (PET-10) were reconstructed and further split into 8-min (PET-8), 6-min (PET-6), 5-min (PET-5), 4-min (PET-4), and 2-min (PET-2) duration groups. Comparisons were made between the different reconstructed scan times in terms of lesion detection rate and image quality based on SUV calculations of tumor lesions and the spleen, which served as background. Analysis of the dynamic PET/CT data was based on a two-tissue compartment model using an image-derived input function obtained from the descending aorta. RESULTS: Analysis of lesion detection rate showed no significant differences when reducing PET acquisitions from 10 up to 5 min. In particular, a total of 169 lesions were counted with PET-10, and the corresponding lesion detection rates (95% CI for the 90% quantile of the differences in tumor lesions) for shorter acquisitions were 100% (169/169) for PET-8 (95% CI: 0-0), 98.8% (167/169) for PET-6 (95% CI: 0-1), 95.9% (162/169) for PET-5 (95% CI: 0-3), 91.7% (155/169) for PET-4 (95% CI: 1-2), and 85.2% (144/169) for PET-2 (95% CI: 1-6). With the exception of PET-2, the differences observed between PET-10 and the other shorter acquisition protocols would have no impact on any patient in terms of clinical management. Objective evaluation of PET/CT image quality showed no significant decrease in tumor-to-background ratio (TBR) with shorter acquisition times, despite a gradual decrease in signal-to-noise ratio (SNR) in the spleen. Whole-body quantitative [18F]PSMA-1007 pharmacokinetic analysis acquired with full dynamic PET scanning was feasible in all patients. Two-tissue compartment modeling revealed significantly higher values for the parameter k3 in tumor lesions and parotid gland compared to liver and spleen, reflecting a higher specific tracer binding to the PSMA molecule and internalization rate in these tissues, a finding also supported by the respective time-activity curves. Furthermore, correlation analysis demonstrated a significantly strong positive correlation (r = 0.72) between SUV and k3 in tumor lesions. CONCLUSIONS: In prostate cancer, low-dose (2 MBq/kg) [18F]PSMA-1007 LAFOV PET/CT can reduce static scan time by 50% without significantly compromising lesion detection rate and objective image quality. In addition, dynamic PET can elucidate molecular pathways related to the physiology of [18F]PSMA-1007 in both tumor lesions and normal organs at the whole-body level. These findings unfold many of the potentials of the new LAFOV PET/CT technology in the field of PSMA-based diagnosis and theranostics of prostate cancer.

Application of an artificial intelligence-based tool in [18F]FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma.

PURPOSE: [18F]FDG PET/CT is an imaging modality of high performance in multiple myeloma (MM). Nevertheless, the inter-observer reproducibility in PET/CT scan interpretation may be hampered by the different patterns of bone marrow (BM) infiltration in the disease. Although many approaches have been recently developed to address the issue of standardization, none can yet be considered a standard method in the interpretation of PET/CT. We herein aim to validate a novel three-dimensional deep learning-based tool on PET/CT images for automated assessment of the intensity of BM metabolism in MM patients. MATERIALS AND METHODS: Whole-body [18F]FDG PET/CT scans of 35 consecutive, previously untreated MM patients were studied. All patients were investigated in the context of an open-label, multicenter, randomized, active-controlled, phase 3 trial (GMMG-HD7). Qualitative (visual) analysis classified the PET/CT scans into three groups based on the presence and number of focal [18F]FDG-avid lesions as well as the degree of diffuse [18F]FDG uptake in the BM. The proposed automated method for BM metabolism assessment is based on an initial CT-based segmentation of the skeleton, its transfer to the SUV PET images, the subsequent application of different SUV thresholds, and refinement of the resulting regions using postprocessing. In the present analysis, six different SUV thresholds (Approaches 1-6) were applied for the definition of pathological tracer uptake in the skeleton [Approach 1: liver SUVmedian × 1.1 (axial skeleton), gluteal muscles SUVmedian × 4 (extremities). Approach 2: liver SUVmedian × 1.5 (axial skeleton), gluteal muscles SUVmedian × 4 (extremities). Approach 3: liver SUVmedian × 2 (axial skeleton), gluteal muscles SUVmedian × 4 (extremities). Approach 4: ≥ 2.5. Approach 5: ≥ 2.5 (axial skeleton), ≥ 2.0 (extremities). Approach 6: SUVmax liver]. Using the resulting masks, subsequent calculations of the whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in each patient were performed. A correlation analysis was performed between the automated PET values and the results of the visual PET/CT analysis as well as the histopathological, cytogenetical, and clinical data of the patients. RESULTS: BM segmentation and calculation of MTV and TLG after the application of the deep learning tool were feasible in all patients. A significant positive correlation (p < 0.05) was observed between the results of the visual analysis of the PET/CT scans for the three patient groups and the MTV and TLG values after the employment of all six [18F]FDG uptake thresholds. In addition, there were significant differences between the three patient groups with regard to their MTV and TLG values for all applied thresholds of pathological tracer uptake. Furthermore, we could demonstrate a significant, moderate, positive correlation of BM plasma cell infiltration and plasma levels of ß2-microglobulin with the automated quantitative PET/CT parameters MTV and TLG after utilization of Approaches 1, 2, 4, and 5. CONCLUSIONS: The automated, volumetric, whole-body PET/CT assessment of the BM metabolic activity in MM is feasible with the herein applied method and correlates with clinically relevant parameters in the disease. This methodology offers a potentially reliable tool in the direction of optimization and standardization of PET/CT interpretation in MM. Based on the present promising findings, the deep learning-based approach will be further evaluated in future prospective studies with larger patient cohorts.

Long axial field of view (LAFOV) PET-CT: implementation in static and dynamic oncological studies.

Long axial field of view (LAFOV) PET-CT scanners have been recently developed and are already in clinical use in few centers worldwide. Although still limited, the hitherto acquired experience with these novel systems highlights an increased sensitivity as their main advantage, which results in an increased lesion detectability. This attribute, alternatively, allows a reduction in PET acquisition time and/or administered radiotracer dose, while it renders delayed scanning of satisfying diagnostic accuracy possible. Another potential advantage of the new generation scanners is CT-less approaches for attenuation correction with the impact of marked reduction of radiation exposure, which may in turn lead to greater acceptance of longitudinal PET studies in the oncological setting. Further, the possibility for the first time of whole-body dynamic imaging, improved compartment modeling, and whole-body parametric imaging represent unique characteristics of the LAFOV PET-CT scanners. On the other hand, the advent of the novel LAFOV scanners is linked to specific challenges, such as the high purchase price and issues related to logistics and their optimal operation in a nuclear medicine department. Moreover, with regard to its research applications in oncology, the full potential of the new scanners can only be reached if different radiopharmaceuticals, both short and long-lived ones, as well as novel tracers, are available for use, which would, in turn, require the appropriate infrastructure in the area of radiochemistry. Although the novel LAFOV scanners are not yet widely used, this development represents an important step in the evolution of molecular imaging. This review presents the advantages and challenges of LAFOV PET-CT imaging for oncological applications with respect to static and dynamic acquisition protocols as well as to new tracers, while it provides an overview of the literature in the field.

Application of the long axial field-of-view PET/CT with low-dose [18F]FDG in melanoma.

AIM: The recent introduction of long axial field-of-view (LAFOV) PET/CT scanners has yielded very promising results regarding image quality and sensitivity in oncological patients. We, herein, aim to determine an appropriate acquisition time range for the new long axial field of view Biograph Vision Quadra PET/CT (Siemens Healthcare) using low dose [18F]FDG activity in a group of melanoma patients. METHODOLOGY: Forty-nine melanoma patients were enrolled in the study. All patients underwent total body PET/CT from the top of the head through the feet in two bed positions (field-of-view 106 cm) after i.v. injection of 2.0 MBq/kg [18F]FDG. The PET images of the first bed position (head to upper thigh; PET-10) were reconstructed and further split into 8-min (PET-8), 6-min (PET-6), 5-min (PET-5), 4-min (PET-4), and 2-min (PET-2) duration groups. Comparisons were performed between the different reconstructed scan times with regard to the visual evaluation of the PET/CT scans using the PET-10 images as reference and by calculating the 95%-CI for the differences between different time acquisitions. Moreover, objective evaluation of PET/CT image quality was performed based on SUV calculations of tumor lesions and background, leading to calculation of liver signal-to-noise ratio (SNR), and tumor-to-background ratio (TBR). RESULTS: A total of 60 scans were evaluated. Concerning visual analysis, 49/60 (81.7%) PET-10 scans were pathological, while the respective frequencies were 49/60 (81.7%) for PET-8 (95%-CI: - 0.0602-0.0602), 49/60 (81.7%) for PET-6 (95%-CI: - 0.0602-0.0602), 48/60 (80%) for PET-5 (95%-CI: - 0.0445-0.0886), 46/60 (76.7%) for PET-4 (95%-CI: - 0.0132-0.1370), and 45/60 (75%) for PET-2 (95%-CI: 0.0025-0.1593). In 18 PET-10 scans, the extent of metastatic involvement was very large, rendering the accurate calculation of [18F]FDG-avid tumor lesions very complicated. In the remaining 42 PET-10 scans, for which the exact calculation of tumor lesions was feasible, a total of 119 tumor lesions were counted, and the respective lesion detection rates for shorter acquisitions were as follows: 97.5% (116/119) for PET-8 (95%-CI: 0-1), 95.0% (113/119) for PET-6 (95%-CI: 0-1), 89.9% (107/119) for PET-5 (95%-CI: 0-2), 83.2% (99/119) for PET-4 (95%-CI: 1-2), and 73.9% (88/119) for PET-2 (95%-CI: 2-4). With regard to objective image quality evaluations, as a general trend, the reduction of acquisition time was associated with a decrease of liver SNR and a decrease of TBR, although in lesion-based analysis the change in TBR and tumor SUVmean values was non-significant up to 6 and 5 min acquisitions, respectively. CONCLUSIONS: In melanoma, low-dose LAFOV PET/CT imaging is feasible and can reduce the total scan time from head to upper thigh up to 5 min providing comparable diagnostic data to standard lengths of acquisition. This may have significant implications for the diagnostic work-up of patients with melanoma, given the need for true whole-body imaging in this type of cancer.

A decision support system for the identification of metastases of Metastatic Melanoma using whole-body FDG PET/CT images.

Metastatic Melanoma (MM) is an aggressive type of cancer which produces metastases throughout the body with very poor survival rates. Recent advances in immunotherapy have shown promising results for controlling disease's progression. Due to the often rapid progression, fast and accurate diagnosis and treatment response assessment is vital for the whole patient management. These procedures prerequisite accurate, whole-body tumor identification. This can be offered by the imaging modality Positron Emission Tomography (PET)/Computed Tomography (CT) with the radiotracer F 18-Fluorodeoxyglucose (FDG). However, manual segmentation of PET/CT images is a very time-consuming and labor intensive procedure that requires expert knowledge. Most of the previously published segmentation techniques focus on a specific type of tumor or part of the body and require a great amount of manually labeled data, which is, however, difficult for MM. Multimodal analysis of PET/CT is also crucial because FDG-PET contains only the functional information of tumors which can be complemented by the anatomical information of CT. In this paper, we propose a whole-body segmentation framework capable of efficiently identifying the highly heterogeneous tumor lesions of MM from the whole-body 3D FDG-PET/CT images. The proposed decision support system begins with an Ensemble Unsupervised Segmentation of regions of high FDG-uptake based on Fuzzy C-means and a custom region growing algorithm. Then, a region classification model based on radiomics features and Neural Networks classifies these regions as tumors or not. Experimental results showed high performance in the identification of MM lesions with Sensitivity 83.68%, Specificity 91.82%, F1-score 75.42%, AUC 94.16% and Balanced accuracy 87.75% which were also supported by the public dataset evaluation.

Parametric Imaging With Dynamic PET for Oncological Applications: Protocols, Interpretation, Current Applications and Limitations for Clinical Use.

Nuclear medicine imaging modalities, and in particular positron emission tomography (PET), provide functional images that demonstrate the mean radioactivity distribution at a defined point in time. With the help of mathematical model's, it is possible to depict isolated parameters of the radiotracers' pharmacokinetics and to visualize them. These so called parametric images add a new dimension to the existing conventional PET images and provide more detailed information about the tracer distribution over time and space. Prerequisite for the calculation of parametric images, which reflect specific pharmacokinetic parameters, is the dynamic PET (dPET) data acquisition. Hitherto, PET parametric imaging has mainly found use for research purposes. However, it has not been yet implemented into clinical routine, since it is more time-consuming, it requires a complicated analysis and still lacks a clear benefit over conventional PET imaging. However, the recent introduction of new PET-CT scanners with an ultralong field of view, which allow a faster data acquisition and are associated with higher sensitivity, as well as the development of more sophisticated evaluation software packages will probably lead to a renaissance of dPET and parametric maps even of the whole body. The implementation of dPET imaging in daily routine with appropriate acquisition protocols, as well as the calculation, interpretation and potential clinical applications of parametric images will be discussed in this review article.

Fractal and Multifractal Analysis of PET-CT Images for Therapy Assessment of Metastatic Melanoma Patients under PD-1 Inhibitors: A Feasibility Study.

Longitudinal whole-body PET-CT scans with F-18-fluorodeoxyglucose (18F-FDG) in patients suffering from metastatic melanoma were analyzed and the tracer distribution in patients was compared with that of healthy controls. Nineteen patients with metastatic melanoma were scanned before, after two and after four cycles of treatment with PD-1 inhibitors (pembrolizumab, nivolumab) applied as monotherapy or as combination treatment with ipilimumab. For comparison eight healthy controls were analyzed. As quantitative measures for the comparison between controls and patients, the nonlinear fractal dimension (FD) and multifractal spectrum (MFS) were calculated from the digitized PET-CT scans. The FD and MFS measures, which capture the dispersion of the tracer in the body, decreased with disease progression, since the tracer particles tended to accumulate around metastatic sites in patients, while the measures increased when the patients' clinical condition ameliorate. The MFS measure gave better predictions and were consistent with the PET Response Evaluation Criteria for Immunotherapy (PERCIMT) in 81% of the cases, while FD agreed in 77% of all cases. These results agree, qualitatively, with a previous study of our group when treatment with ipilimumab monotherapy was considered.

Interim [18F]FDG PET/CT can predict response to anti-PD-1 treatment in metastatic melanoma.

PURPOSE: In an attempt to identify biomarkers that can reliably predict long-term outcomes to immunotherapy in metastatic melanoma, we investigated the prognostic role of [18F]FDG PET/CT, performed at baseline and early during the course of anti-PD-1 treatment. METHODS: Twenty-five patients with stage IV melanoma, scheduled for treatment with PD-1 inhibitors, were enrolled in the study (pembrolizumab, n = 8 patients; nivolumab, n = 4 patients; nivolumab/ipilimumab, 13 patients). [18F]FDG PET/CT was performed before the start of treatment (baseline PET/CT) and after the initial two cycles of PD-1 blockade administration (interim PET/CT). Seventeen patients underwent also a third PET/CT scan after administration of four cycles of treatment. Evaluation of patients' response by means of PET/CT was performed after application of the European Organization for Research and Treatment of Cancer (EORTC) 1999 criteria and the PET Response Evaluation Criteria for IMmunoTherapy (PERCIMT). Response to treatment was classified into 4 categories: complete metabolic response (CMR), partial metabolic response (PMR), stable metabolic disease (SMD), and progressive metabolic disease (PMD). Patients were further grouped into two groups: those demonstrating metabolic benefit (MB), including patients with SMD, PMR, and CMR, and those demonstrating no MB (no-MB), including patients with PMD. Moreover, patterns of [18F]FDG uptake suggestive of radiologic immune-related adverse events (irAEs) were documented. Progression-free survival (PFS) was measured from the date of interim PET/CT until disease progression or death from any cause. RESULTS: Median follow-up from interim PET/CT was 24.2 months (19.3-41.7 months). According to the EORTC criteria, 14 patients showed MB (1 CMR, 6 PMR, and 7 SMD), while 11 patients showed no-MB (PMD). Respectively, the application of the PERCIMT criteria revealed that 19 patients had MB (1 CMR, 6 PMR, and 12 SMD), and 6 of them had no-MB (PMD). With regard to PFS, no significant difference was observed between patients with MB and no-MB on interim PET/CT according to the EORTC criteria (p = 0.088). In contrary, according to the PERCIMT criteria, patients demonstrating MB had a significantly longer PFS than those showing no-MB (p = 0.045). The emergence of radiologic irAEs (n = 11 patients) was not associated with a significant survival benefit. Regarding the sub-cohort undergoing also a third PET/CT, 14/17 patients (82%) showed concordant responses and 3/17 (18%) had a mismatch of response assessment between interim and late PET/CT. CONCLUSION: PET/CT-based response of metastatic melanoma to PD-1 blockade after application of the recently proposed PERCIMT criteria is significantly correlated with PFS. This highlights the potential ability of [18F]FDG PET/CT for early stratification of response to anti-PD-1 agents, a finding with possible significant clinical and financial implications. Further studies including larger numbers of patients are necessary to validate these results.

Kinetic modeling and parametric imaging with dynamic PET for oncological applications: general considerations, current clinical applications, and future perspectives.

Dynamic PET (dPET) studies have been used until now primarily within research purposes. Although it is generally accepted that the information provided by dPET is superior to that of conventional static PET acquisitions acquired usually 60 min post injection of the radiotracer, the duration of dynamic protocols, the limited axial field of view (FOV) of current generation clinical PET systems covering a relatively small axial extent of the human body for a dynamic measurement, and the complexity of data evaluation have hampered its implementation into clinical routine. However, the development of new-generation PET/CT scanners with an extended FOV as well as of more sophisticated evaluation software packages that offer better segmentation algorithms, automatic retrieval of the arterial input function, and automatic calculation of parametric imaging, in combination with dedicated shorter dynamic protocols, will facilitate the wider use of dPET. This is expected to aid in oncological diagnostics and therapy assessment. The aim of this review is to present some general considerations about dPET analysis in oncology by means of kinetic modeling, based on compartmental and noncompartmental approaches, and parametric imaging. Moreover, the current clinical applications and future perspectives of the modality are outlined.

Multi-Path Dilated Residual Network for Nuclei Segmentation and Detection.

As a typical biomedical detection task, nuclei detection has been widely used in human health management, disease diagnosis and other fields. However, the task of cell detection in microscopic images is still challenging because the nuclei are commonly small and dense with many overlapping nuclei in the images. In order to detect nuclei, the most important key step is to segment the cell targets accurately. Based on Mask RCNN model, we designed a multi-path dilated residual network, and realized a network structure to segment and detect dense small objects, and effectively solved the problem of information loss of small objects in deep neural network. The experimental results on two typical nuclear segmentation data sets show that our model has better recognition and segmentation capability for dense small targets.

Discussion on operative skills in the embolization of hydrosalpinx by hysteroscopic placement of a microcoil.

This study aims to discuss the operative skills of hysteroscopic tubal embolization and reduce the occurrence of complications.Ninety-four patients were divided into group A and group B. The main surgical technique in group A: when the inner sleeve is sent to the fallopian tube and no longer accessible (but no >3 cm), remove the guide wire and put into the microcoil. But in group B, there are four major surgical techniques. First, the depth at which the guide wire enters the tube was controlled at 2 cm. Second, the inner diameter of the fallopian tube must be explored to determine the type and shape of the coils. Third, saline should be used to separate the catheter. Fourth, it is to control the release speed of the coils. The superiority of the improved operation method was confirmed by comparing the surgical failure rate, incidence of complications, and cost of surgery before and after the procedure.The reoperation rate of group A was 10% (3/30), while that of group B was 2.68% (3/112). The ectopic microcoils rate of group A was 6.67% (2/30), while that of group B was 0.89% (1/112). The microcoil damages rate of group 23.33% (7/30), while that of group B was 8.04% (9/112). All P values were <.01, and the difference was statistically significant.Hysteroscopic tubal embolization is currently a new surgical procedure to block the fallopian tubes and prevent the reverse flow of fluid in the fallopian tubes into the uterine cavity. After we improved surgical techniques, the surgical failure rate, complication rate, and operation cost of fallopian tube embolization were significantly lower than before the improved method was applied. The improved techniques led to a higher success rate.

Radiogenomic Analysis of F-18-Fluorodeoxyglucose Positron Emission Tomography and Gene Expression Data Elucidates the Epidemiological Complexity of Colorectal Cancer Landscape.

PURPOSE: Transcriptomic profiling has enabled the neater genomic characterization of several cancers, among them colorectal cancer (CRC), through the derivation of genes with enhanced causal role and informative gene sets. However, the identification of small-sized gene signatures, which can serve as potential biomarkers in CRC, remains challenging, mainly due to the great genetic heterogeneity of the disease. METHODS: We developed and exploited an analytical framework for the integrative analysis of CRC datasets, encompassing transcriptomic data and positron emission tomography (PET) measurements. Profiling data comprised two microarray datasets, pertaining biopsy specimen from 30 untreated patients with primary CRC, coupled by their F-18-Fluorodeoxyglucose (FDG) PET values, using tracer kinetic analysis measurements. The computational framework incorporates algorithms for semantic processing, multivariate analysis, data mining and dimensionality reduction. RESULTS: Transcriptomic and PET data feature sets, were evaluated for their discrimination performance between primary colorectal adenocarcinomas and adjacent normal mucosa. A composite signature was derived, pertaining 12 features: 7 genes and 5 PET variables. This compact signature manifests superior performance in classification accuracy, through the integration of gene expression and PET data. CONCLUSIONS: This work represents an effort for the integrative, multilayered, signature-oriented analysis of CRC, in the context of radio-genomics, inferring a composite signature with promising results for patient stratification.

68Ga-PSMA-11 PET/CT in prostate cancer local recurrence: impact of early images and parametric analysis.

68Ga-PSMA-11 PET/CT performed 60 min post tracer injection (p.i.) can underestimate prostate cancer (PC) local recurrence, due to high 68Ga-PSMA-11 urinary bladder accumulation. Aim of this analysis is to evaluate the complementary role of early dynamic and parametric PET imaging in patients with PC local recurrence. Sixteen patients with PC biochemical relapse attributed to local recurrence underwent dynamic 68Ga-PSMA-11 PET/CT scanning of the pelvis and whole-body PET/CT. Data analysis was based on visual analysis of the PET/CT scans, SUV calculations, quantitative analysis based on two-tissue compartment and Patlak models as well as parametric imaging based on Patlak analysis. 12/16 patients were PSMA-positive in the static 68Ga-PSMA-11 PET/CT scans (60 min p.i.). All 12 lesions corresponding to PC local recurrence were detected in the early dynamic images at a median time of 4.5 min p.i. (range = 1.5-11.5 min). Moreover, early dynamic PET imaging could detect local recurrence in 1/4 static PET/CT-negative patients. Tracer accumulation in the urinary bladder began at a median time of 10 min (range = 6.0-17.5 min). All PC local recurrences visible on late static PET/CT and the local recurrence, which was positive only in early dynamic but not in late PET images, could be delineated on Patlak images. The present findings indicate that early dynamic 68Ga-PSMA-11 PET/CT scan of the pelvis up to 12 min p.i. as well as Patlak analysis, performed in addition to the conventional PET/CT acquired at 60 min p.i., seem a practical approach to increase the detection rate of PC local recurrence.

Imaging therapy response of gastrointestinal stromal tumors (GIST) with FDG PET, CT and MRI: a systematic review.

PURPOSE: Improvement of the therapeutic approaches in gastrointestinal stromal tumors (GIST) by the introduction of targeted therapies requires appropriate diagnostic tools, which allow sufficient assessment of therapeutic response, including differentiation of true progression from pseudoprogression due to myxoid degeneration or intratumoral hemorrhage. In this literature review the impact and limitations of different imaging modalities used in GIST therapy monitoring are discussed. METHODS: PubMed and Cochrane library search were performed using appropriate keywords. Overall, 39 original papers fulfilled the defined criteria and were included in this systematic review. RESULTS: Morphological imaging modalities like computed tomography (CT) are primarily used for both diagnosis and therapy monitoring. However, therapy with tyrosine kinase inhibitors and other targeted therapies in GIST may lead only to a minor tumor volume reduction even in cases of response. Therefore, the use of Response Evaluation Criteria in Solid Tumors (RECIST) has limitations. To overcome those limitations, modified response criteria have been introduced for the CT-based therapy assessment, like the Choi criteria as well as criteria based on dual energy CT studies. Functional imaging techniques, mostly based on FDG PET-CT are in use, in particular for the assessment of early treatment response. CONCLUSIONS: The impact and the limitations of PET-based therapy monitoring, as well as its comparison with CT, MRI and survival data are discussed in this review. CT is still the standard method for the evaluation of therapy response despite its several limitations. FDG PET-CT is helpful for the assessment of early therapy response; however, more prospective data are needed to define its role as well as the appropriate time intervals for therapy monitoring. A multiparametric evaluation based on changes in both morphological and functional data has to be assessed in further prospective studies.

Machine learning-based kinetic modeling: a robust and reproducible solution for quantitative analysis of dynamic PET data.

A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated values over time, which may encounter some problems such as the overfitting of model parameters and a lack of reproducibility, especially when handling noisy data or error data. In this paper, a machine learning (ML) based kinetic modeling method is introduced, which can fully utilize a historical reference database to build a moderate kinetic model directly dealing with noisy data but not trying to smooth the noise in the image. Also, due to the database, the presented method is capable of automatically adjusting the models using a multi-thread grid parameter searching technique. Furthermore, a candidate competition concept is proposed to combine the advantages of the ML and IF modeling methods, which could find a balance between fitting to historical data and to the unseen target curve. The machine learning based method provides a robust and reproducible solution that is user-independent for VOI-based and pixel-wise quantitative analysis of dynamic PET data.

68Ga-PSMA-11 Dynamic PET/CT Imaging in Primary Prostate Cancer.

PURPOSE: The aim of our study is to assess the pharmacokinetics and biodistribution of Ga-PSMA-11 in patients suffering from primary prostate cancer (PC) by means of dynamic and whole-body PET/CT. MATERIALS AND METHODS: Twenty-four patients with primary, previously untreated PC were enrolled in the study. All patients underwent dynamic PET/CT (dPET/CT) scanning of the pelvis and whole-body PET/CT studies with Ga-PSMA-11. The evaluation of dPET/CT studies was based on qualitative evaluation, SUV calculation, and quantitative analysis based on two-tissue compartment modeling and a noncompartmental approach leading to the extraction of fractal dimension (FD). RESULTS: A total of 23/24 patients (95.8%) were Ga-PSMA-11 positive. In 9/24 patients (37.5%), metastatic lesions were detected. PC-associated lesions demonstrated the following mean values: SUVaverage = 14.3, SUVmax = 23.4, K1 = 0.24 (1/min), k3 = 0.34 (1/min), influx = 0.15 (1/min), and FD = 1.27. The parameters SUVaverage, SUVmax, k3, influx, and FD derived from PC-associated lesions were significantly higher than respective values derived from reference prostate tissue. Time-activity curves derived from PC-associated lesions revealed an increasing Ga-PSMA-11 accumulation during dynamic PET acquisition. Correlation analysis revealed a moderate but significant correlation between PSA levels and SUVaverage (r = 0.60) and SUVmax (r = 0.57), and a weak but significant correlation between Gleason score and SUVaverage (r = 0.33) and SUVmax (r = 0.28). CONCLUSION: Ga-PSMA-11 PET/CT confirmed its capacity in detecting primary PC with a detection rate of 95.8%. Dynamic PET/CT studies of the pelvis revealed an increase in tracer uptake in PC-associated lesions during the 60 minutes of dynamic PET acquisition, a finding with potential applications in anti-PSMA approaches.

Fractal and multifractal analysis of PET/CT images of metastatic melanoma before and after treatment with ipilimumab.

BACKGROUND: PET/CT with F-18-fluorodeoxyglucose (FDG) images of patients suffering from metastatic melanoma have been analysed using fractal and multifractal analysis to assess the impact of monoclonal antibody ipilimumab treatment with respect to therapy outcome. RESULTS: Thirty-one cases of patients suffering from metastatic melanoma have been scanned before and after two and after four cycles of treatment. For each patient, we calculated the fractal and multifractal dimensions using the box-counting method on the digitalised PET/CT images of all three studies to assess the therapeutic outcome. We modelled the spreading of malignant cells in the body via kinetic Monte Carlo simulations to address the dynamical evolution of the metastatic process and to predict the spatial distribution of malignant lesions. Our analysis shows that the fractal dimensions which describe the tracer dispersion in the body decrease consistently with the deterioration of the patient's therapeutic outcome condition. In 20 out of 24 cases, the fractal analysis results match those of the treatment outcome as defined by the oncologists, while 7 cases are considered as special cases because the patients had non-tumour-related findings or side effects which affect the results. The decrease in the fractal dimensions with the deterioration of the patient conditions (in terms of disease progression) is attributed to the hierarchical localisation of the tracer which accumulates in the affected lesions and does not spread homogeneously throughout the body. Fractality emerges as a result of the migration patterns which the malignant cells follow for propagating within the body (circulatory system, lymphatic system). Analysis of the multifractal spectrum complements and supports the results of the fractal analysis. In the kinetic Monte Carlo modelling of the metastatic process, a small number of malignant cells diffuse through a fractal medium representing the blood circulatory network. Along their way, the malignant cells engender random metastases (colonies) with a small probability and, as a result, fractal spatial distributions of the metastases are formed similar to the ones observed in the PET/CT images. CONCLUSIONS: The Monte Carlo-generated spatial distribution of metastases changes with time approaching values close to the ones recorded in the metastatic patients. Thus, we propose that fractal and multifractal analyses have potential applications in quantification of the evaluation of PET/CT images to monitor the disease evolution as well as the response to different medical treatments. The proposed approach, being operator independent, can offer new diagnostic tools in parallel to the visual location of the lesions and may improve multiparameter assessment of FDG PET/CT studies.

Comparison of (18)F-FDG PET/CT and PET/MRI in patients with multiple myeloma.

PET/MRI represents a promising hybrid imaging modality with several potential clinical applications. Although PET/MRI seems highly attractive in the diagnostic approach of multiple myeloma (MM), its role has not yet been evaluated. The aims of this prospective study are to evaluate the feasibility of (18)F-FDG PET/MRI in detection of MM lesions, and to investigate the reproducibility of bone marrow lesions detection and quantitative data of (18)F-FDG uptake between the functional (PET) component of PET/CT and PET/MRI in MM patients. The study includes 30 MM patients. All patients initially underwent (18)F-FDG PET/CT (60 min p.i.), followed by PET/MRI (120 min p.i.). PET/CT and PET/MRI data were assessed and compared based on qualitative (lesion detection) and quantitative (SUV) evaluation. The hybrid PET/MRI system provided good image quality in all cases without artefacts. PET/MRI identified 65 of the 69 lesions, which were detectable with PET/CT (94.2%). Quantitative PET evaluations showed the following mean values in MM lesions: SUVaverage=5.5 and SUVmax=7.9 for PET/CT; SUVaverage=3.9 and SUVmax=5.8 for PET/MRI. Both SUVaverage and SUVmax were significantly higher on PET/CT than on PET/MRI. Spearman correlation analysis demonstrated a strong correlation between both lesional SUVaverage (r=0.744) and lesional SUVmax (r=0.855) values derived from PET/CT and PET/MRI. Regarding detection of myeloma skeletal lesions, PET/MRI exhibited equivalent performance to PET/CT. In terms of tracer uptake quantitation, a significant correlation between the two techniques was demonstrated, despite the statistically significant differences in lesional SUVs between PET/CT and PET/MRI.