Surgical Treatment and Clinical Outcomes of Petroclival Meningiomas: A Single-Center Experience of 107 Patients.

OBJECTIVE: This study aimed to establish optimal surgical strategies via reviewing the clinical outcomes of various surgical approaches for the pertroclival meningiomas (PCMs). METHODS: This retrospective study enrolled 107 patients with PCMs at the authors' institution from year 2010 to 2020. Patient demographics, the clinical characteristics, various operative approaches, major morbidity, post-operative cranial nerve deficits and tumor progression or recurrence were analyzed. RESULTS: The subtemporal transtentorial approach (STA), the Kawase approach (KA), the retrosigmoid approach (RSA) and the anterior sigmoid approach (ASA), namely the posterior petrosal approach (PPA) were adopted for 17 cases, 22 cases, 31 cases and 34 cases respectively. Total or subtotal resection was achieved in 96 cases (89.7%). The incidence of new-onset and aggravated cranial nerve dysfunction were 13.1% (14/107) and 10.4% (15/144), respectively. Furthermore, 14 cases suffered from intracranial infection, 9 cases had cerebrospinal fluid leakage, and 3 cases sustained intracranial hematoma (1 case underwent second operation). The mean preoperative and postoperative Karnofsky Performance Status (KPS) score was 80 (range 60-100) and 78.6 (range 0-100), but this was not statistically significant (P>0.05). After a mean follow-up of 5.1 years (range 0.3- 10.6 years), tumor progression or recurrence was confirmed in 23 cases. Two cases died from postoperative complications. CONCLUSIONS: For the treatment of PCMs, it is still a challenge to achieve total resection. With elaborate surgical plans and advanced microsurgical skills, most patients with PCMs can be rendered tumor resection with satisfactory extent and functional preservation, despite transient neurological deterioration during early postoperative periods.

Quantitative PET in the 2020s: a roadmap.

Positron emission tomography (PET) plays an increasingly important role in research and clinical applications, catalysed by remarkable technical advances and a growing appreciation of the need for reliable, sensitive biomarkers of human function in health and disease. Over the last 30 years, a large amount of the physics and engineering effort in PET has been motivated by the dominant clinical application during that period, oncology. This has led to important developments such as PET/CT, whole-body PET, 3D PET, accelerated statistical image reconstruction, and time-of-flight PET. Despite impressive improvements in image quality as a result of these advances, the emphasis on static, semi-quantitative 'hot spot' imaging for oncologic applications has meant that the capability of PET to quantify biologically relevant parameters based on tracer kinetics has not been fully exploited. More recent advances, such as PET/MR and total-body PET, have opened up the ability to address a vast range of new research questions, from which a future expansion of applications and radiotracers appears highly likely. Many of these new applications and tracers will, at least initially, require quantitative analyses that more fully exploit the exquisite sensitivity of PET and the tracer principle on which it is based. It is also expected that they will require more sophisticated quantitative analysis methods than those that are currently available. At the same time, artificial intelligence is revolutionizing data analysis and impacting the relationship between the statistical quality of the acquired data and the information we can extract from the data. In this roadmap, leaders of the key sub-disciplines of the field identify the challenges and opportunities to be addressed over the next ten years that will enable PET to realise its full quantitative potential, initially in research laboratories and, ultimately, in clinical practice.

Dependence of fluorodeoxyglucose (FDG) uptake on cell cycle and dry mass: a single-cell study using a multi-modal radiography platform.

High glucose uptake by cancer compared to normal tissues has long been utilized in fluorodeoxyglucose-based positron emission tomography (FDG-PET) as a contrast mechanism. The FDG uptake rate has been further related to the proliferative potential of cancer, specifically the proliferation index (PI) - the proportion of cells in S, G2 or M phases. The underlying hypothesis was that the cells preparing for cell division would consume more energy and metabolites as building blocks for biosynthesis. Despite the wide clinical use, mixed reports exist in the literature on the relationship between FDG uptake and PI. This may be due to the large variation in cancer types or methods adopted for the measurements. Of note, the existing methods can only measure the average properties of a tumor mass or cell population with highly-heterogeneous constituents. In this study, we have built a multi-modal live-cell radiography system and measured the [18F]FDG uptake by single HeLa cells together with their dry mass and cell cycle phase. The results show that HeLa cells take up twice more [18F]FDG in S, G2 or M phases than in G1 phase, which confirms the association between FDG uptake and PI at a single-cell level. Importantly, we show that [18F]FDG uptake and cell dry mass have a positive correlation in HeLa cells, which suggests that high [18F]FDG uptake in S, G2 or M phases can be largely attributed to increased dry mass, rather than the activities preparing for cell division. This interpretation is consistent with recent observations that the energy required for the preparation of cell division is much smaller than that for maintaining house-keeping proteins.

Investigation of cone-beam CT image quality trade-off for image-guided radiation therapy.

It is well-known that projections acquired over an angular range slightly over 180° (so-called short scan) are sufficient for fan-beam reconstruction. However, due to practical imaging conditions (projection data and reconstruction image discretization, physical factors, and data noise), the short-scan reconstructions may have different appearances and properties from the full-scan (scans over 360°) reconstructions. Nevertheless, short-scan configurations have been used in applications such as cone-beam CT (CBCT) for head-neck-cancer image-guided radiation therapy (IGRT) that only requires a small field of view due to the potential reduced imaging time and dose. In this work, we studied the image quality trade-off for full, short, and full/short scan configurations with both conventional filtered-backprojection (FBP) reconstruction and iterative reconstruction algorithms based on total-variation (TV) minimization for head-neck-cancer IGRT. Anthropomorphic and Catphan phantoms were scanned at different exposure levels with a clinical scanner used in IGRT. Both visualization- and numerical-metric-based evaluation studies were performed. The results indicate that the optimal exposure level and number of views are in the middle range for both FBP and TV-based iterative algorithms and the optimization is object-dependent and task-dependent. The optimal view numbers decrease with the total exposure levels for both FBP and TV-based algorithms. The results also indicate there are slight differences between FBP and TV-based iterative algorithms for the image quality trade-off: FBP seems to be more in favor of larger number of views while the TV-based algorithm is more robust to different data conditions (number of views and exposure levels) than the FBP algorithm. The studies can provide a general guideline for image-quality optimization for CBCT used in IGRT and other applications.

4D numerical observer for lesion detection in respiratory-gated PET.

PURPOSE: Respiratory-gated positron emission tomography (PET)/computed tomography protocols reduce lesion smearing and improve lesion detection through a synchronized acquisition of emission data. However, an objective assessment of image quality of the improvement gained from respiratory-gated PET is mainly limited to a three-dimensional (3D) approach. This work proposes a 4D numerical observer that incorporates both spatial and temporal informations for detection tasks in pulmonary oncology. METHODS: The authors propose a 4D numerical observer constructed with a 3D channelized Hotelling observer for the spatial domain followed by a Hotelling observer for the temporal domain. Realistic (18)F-fluorodeoxyglucose activity distributions were simulated using a 4D extended cardiac torso anthropomorphic phantom including 12 spherical lesions at different anatomical locations (lower, upper, anterior, and posterior) within the lungs. Simulated data based on Monte Carlo simulation were obtained using geant4 application for tomographic emission (GATE). Fifty noise realizations of six respiratory-gated PET frames were simulated by GATE using a model of the Siemens Biograph mMR scanner geometry. PET sinograms of the thorax background and pulmonary lesions that were simulated separately were merged to generate different conditions of the lesions to the background (e.g., lesion contrast and motion). A conventional ordered subset expectation maximization (OSEM) reconstruction (5 iterations and 6 subsets) was used to obtain: (1) gated, (2) nongated, and (3) motion-corrected image volumes (a total of 3200 subimage volumes: 2400 gated, 400 nongated, and 400 motion-corrected). Lesion-detection signal-to-noise ratios (SNRs) were measured in different lesion-to-background contrast levels (3.5, 8.0, 9.0, and 20.0), lesion diameters (10.0, 13.0, and 16.0 mm), and respiratory motion displacements (17.6-31.3 mm). The proposed 4D numerical observer applied on multiple-gated images was compared to the conventional 3D approach applied on the nongated and motion-corrected images. RESULTS: On average, the proposed 4D numerical observer improved the detection SNR by 48.6% (p < 0.005), whereas the 3D methods on motion-corrected images improved by 31.0% (p < 0.005) as compared to the nongated method. For all different conditions of the lesions, the relative SNR measurement (Gain = SNRObserved/SNRNongated) of the 4D method was significantly higher than one from the motion-corrected 3D method by 13.8% (p < 0.02), where Gain4D was 1.49 ± 0.21 and Gain3D was 1.31 ± 0.15. For the lesion with the highest amplitude of motion, the 4D numerical observer yielded the highest observer-performance improvement (176%). For the lesion undergoing the smallest motion amplitude, the 4D method provided superior lesion detectability compared with the 3D method, which provided a detection SNR close to the nongated method. The investigation on a structure of the 4D numerical observer showed that a Laguerre-Gaussian channel matrix with a volumetric 3D function yielded higher lesion-detection performance than one with a 2D-stack-channelized function, whereas a different kind of channels that have the ability to mimic the human visual system, i.e., difference-of-Gaussian, showed similar performance in detecting uniform and spherical lesions. The investigation of the detection performance when increasing noise levels yielded decreasing detection SNR by 27.6% and 41.5% for the nongated and gated methods, respectively. The investigation of lesion contrast and diameter showed that the proposed 4D observer preserved the linearity property of an optimal-linear observer while the motion was present. Furthermore, the investigation of the iteration and subset numbers of the OSEM algorithm demonstrated that these parameters had impact on the lesion detectability and the selection of the optimal parameters could provide the maximum lesion-detection performance. The proposed 4D numerical observer outperformed the other observers for the lesion-detection task in various lesion conditions and motions. CONCLUSIONS: The 4D numerical observer shows substantial improvement in lesion detectability over the 3D observer method. The proposed 4D approach could potentially provide a more reliable objective assessment of the impact of respiratory-gated PET improvement for lesion-detection tasks. On the other hand, the 4D approach may be used as an upper bound to investigate the performance of the motion correction method. In future work, the authors will validate the proposed 4D approach on clinical data for detection tasks in pulmonary oncology.

Relative role of motion and PSF compensation in whole-body oncologic PET-MR imaging.

PURPOSE: Respiratory motion and partial-volume effects are the two main sources of image degradation in whole-body PET imaging. Simultaneous PET-MR allows measurement of respiratory motion using MRI while collecting PET events. Improved PET images may be obtained by modeling respiratory motion and point spread function (PSF) within the PET iterative reconstruction process. In this study, the authors assessed the relative impact of PSF modeling and MR-based respiratory motion correction in phantoms and patient studies using a whole-body PET-MR scanner. METHODS: An asymmetric exponential PSF model accounting for radially varying and axial detector blurring effects was obtained from point source acquisitions performed in the PET-MR scanner. A dedicated MRI acquisition protocol using single-slice steady state free-precession MR acquisitions interleaved with pencil-beam navigator echoes was developed to track respiratory motion during PET-MR studies. An iterative ordinary Poisson fully 3D OSEM PET reconstruction algorithm modeling all the physical effects of the acquisition (attenuation, scatters, random events, detectors efficiencies, PSF), as well as MR-based nonrigid respiratory deformations of tissues (in both emission and attenuation maps) was developed. Phantom and(18)F-FDG PET-MR patient studies were performed to evaluate the proposed quantitative PET-MR methods. RESULTS: The phantom experiment results showed that PSF modeling significantly improved contrast recovery while limiting noise propagation in the reconstruction process. In patients with soft-tissue static lesions, PSF modeling improved lesion contrast by 19.7%-109%, enhancing the detectability and assessment of small tumor foci. In a patient study with small moving hepatic lesions, the proposed reconstruction technique improved lesion contrast by 54.4%-98.1% and reduced apparent lesion size by 21.8%-34.2%. Improvements were particularly important for the smallest lesion undergoing large motion at the lung-liver interface. Heterogeneous tumor structures delineation was substantially improved. Enhancements offered by PSF modeling were more important when correcting for motion at the same time. CONCLUSIONS: The results suggest that the proposed quantitative PET-MR methods can significantly enhance the performance of tumor diagnosis and staging as compared to conventional methods. This approach may enable utilization of the full potential of the scanner in oncologic studies of both the lower abdomen, with moving lesions, as well as other parts of the body unaffected by motion.

Simultaneous 99mTc-MDP/123I-MIBG tumor imaging using SPECT-CT: phantom and constructed patient studies.

PURPOSE: Authors' goal is to evaluate the performance of simultaneous (99m)Tc-MDP/(123)I-MIBG tumor imaging with fast Monte-Carlo (MC) based joint iterative reconstruction as compared to sequential (99m)Tc-MDP and (123)I-MIBG tumor imaging. METHODS: Noise-free (99m)Tc and (123)I SPECT projections were acquired separately using an anthropomorphic torso phantom modified to include a fillable tube around the lungs to mimic ribs. Additionally, (99m)Tc and (123)I projections were acquired separately using a 1-cm spherical "tumor" placed at various distances from one detector. Tumor-present data were generated by adding tumor projections to the torso phantom data, which were scaled to the total counts in typical clinical studies. Twenty-five noise realizations were generated by adding Poisson noise to the projection data for each radionuclide. Dual-radionuclide data were synthesized by summing the (99m)Tc and (123)I projections. Image reconstruction was performed using: (1) SR-OSEM, ordered subset expectation maximization (OSEM) without scatter correction (SC) using single-radionuclide (SR) data; (2) SR-MC-OSEM, OSEM with a fast MC-based SC using SR data; (3) DR-OSEM, OSEM without SC using dual-radionuclide (DR) data; and (4) DR-MC-JOSEM, joint OSEM with a fast MC-based SC using DR data. Ten (99m)Tc-MDP and ten (123)I-MIBG data sets, which had tumors mathematically inserted, were also used to evaluate the performance of authors' approach. For the phantom study, relative bias and relative standard deviation of tumor uptake were computed for each tumor using the tumor uptake in the noise-free single-radionuclide images, which were reconstructed by SR-MC-OSEM, as the gold standard. For both the phantom and constructed patient studies, mean contrast and standard deviation of contrast were computed for each tumor for both the single- and dual-radionuclide images. Additionally, contrast recovery was computed as the ratio between mean contrast and the mean contrast for SR-MC-OSEM. RESULTS: For the phantom study, DR-MC-JOSEM yielded 2.7% on average relative bias of tumor uptake using the images, which were reconstructed from the noise-free SR data with SR-MC-OSEM, as the gold-standard. For both the phantom and constructed patient studies, DR-MC-JOSEM yielded 94.7% and 95.2% tumor contrast recovery on average using SR-MC-OSEM as the reference, in the phantom and constructed patient studies, respectively. DR-MC-JOSEM yielded comparable relative standard deviation of bias and standard deviation of contrast to SR-MC-OSEM. CONCLUSIONS: Simultaneous (99m)Tc-MDP/(123)I-MIBG tumor imaging using authors' dual-radionuclide reconstruction approach yielded comparable image quality to sequential (99m)Tc-MDP and (123)I-MIBG imaging. For patients who need to undergo both scans, authors' approach offers perfectly registered dual-tracer images under identical conditions without compromising image quality, and reduces the imaging cost while increasing patient throughput.

Monitoring proton radiation therapy with in-room PET imaging.

We used a mobile positron emission tomography (PET) scanner positioned within the proton therapy treatment room to study the feasibility of proton range verification with an in-room, stand-alone PET system, and compared with off-line equivalent studies. Two subjects with adenoid cystic carcinoma were enrolled into a pilot study in which in-room PET scans were acquired in list-mode after a routine fractionated treatment session. The list-mode PET data were reconstructed with different time schemes to generate in-room short, in-room long and off-line equivalent (by skipping coincidences from the first 15 min during the list-mode reconstruction) PET images for comparison in activity distribution patterns. A phantom study was followed to evaluate the accuracy of range verification for different reconstruction time schemes quantitatively. The in-room PET has a higher sensitivity compared to the off-line modality so that the PET acquisition time can be greatly reduced from 30 to <5 min. Features in deep-site, soft-tissue regions were better retained with in-room short PET acquisitions because of the collection of (15)O component and lower biological washout. For soft tissue-equivalent material, the distal fall-off edge of an in-room short acquisition is deeper compared to an off-line equivalent scan, indicating a better coverage of the high-dose end of the beam. In-room PET is a promising low cost, high sensitivity modality for the in vivo verification of proton therapy. Better accuracy in Monte Carlo predictions, especially for biological decay modeling, is necessary.

Improved activity estimation with MC-JOSEM versus TEW-JOSEM in 111In SPECT.

We have previously developed a fast Monte Carlo (MC)-based joint ordered-subset expectation maximization (JOSEM) iterative reconstruction algorithm, MC-JOSEM. A phantom study was performed to compare quantitative imaging performance of MC-JOSEM with that of a triple-energy-window approach (TEW) in which estimated scatter was also included additively within JOSEM, TEW-JOSEM. We acquired high-count projections of a 5.5 cm3 sphere of 111In at different locations in the water-filled torso phantom; high-count projections were then obtained with 111In only in the liver or only in the soft-tissue background compartment, so that we could generate synthetic projections for spheres surrounded by various activity distributions. MC scatter estimates used by MC-JOSEM were computed once after five iterations of TEW-JOSEM. Images of different combinations of liver/background and sphere/background activity concentration ratios were reconstructed by both TEW-JOSEM and MC-JOSEM for 40 iterations. For activity estimation in the sphere, MC-JOSEM always produced better relative bias and relative standard deviation than TEW-JOSEM for each sphere location, iteration number, and activity combination. The average relative bias of activity estimates in the sphere for MC-JOSEM after 40 iterations was -6.9%, versus -15.8% for TEW-JOSEM, while the average relative standard deviation of the sphere activity estimates was 16.1% for MC-JOSEM, versus 27.4% for TEW-JOSEM. Additionally, the average relative bias of activity concentration estimates in the liver and the background for MC-JOSEM after 40 iterations was -3.9%, versus -12.2% for TEW-JOSEM, while the average relative standard deviation of these estimates was 2.5% for MC-JOSEM, versus 3.4% for TEW-JOSEM. MC-JOSEM is a promising approach for quantitative activity estimation in 111In SPECT.