Liver Tumor Enhancement at Hybrid Angio-CT and Comparison With Tumor and Hepatic Parenchymal Distribution of Yttrium-90 Microspheres by Positron Emission Tomography.

This single-center retrospective study evaluated patients who underwent treatment of a primary or secondary hepatic malignancy with injection of glass or resin yttrium-90 (90Y) microspheres with a corresponding hybrid angiography-computed tomography (angio-CT) and 90Y positron emission tomography (PET). Volumetric contours were defined by three independent observers and were used to calculate relative tumoral enhancement at angio-CT. This parameter was compared with the tumor-to-normal (T/N) activity ratio predicted by technetium-99m macro-aggregated albumin (99mTc-MAA) single photon emission computed tomography (SPECT) and microsphere activity distribution by 90Y PET. A similar correlation was observed for the enhancement ratio at angio-CT with observed microsphere distribution at 90Y PET (r=0.34) to that predicted by 99mTc-MAA SPECT (r=0.32). The enhancement ratio on angio-CT performed as well as 99mTc-MAA in the prediction of 90Y PET activity distribution. The technique could not be readily applied to tumors with large areas of hypoattenuation (necrosis) on angio-CT. With refinement and further study, this technique could be used as a quantitative adjunct to standard-of-care 99mTc-MAA SPECT for dosimetry calculations and prediction of microsphere distribution to maximize tumor response and minimize hepatotoxicity.

The Influence of Patient and System Factors on the Radiotherapy Treatment Time in the Treatment of Non-metastatic Cervical Cancer Patients in a Rural and Resource-Lean State's Safety-Net Hospital: Benefits of Strategic Planning.

Objective To decrease radiotherapy treatment time (RTT), measured from the day of initiation of radiotherapy to the day of its completion, specific strategies were initiated in early 2020 in the only academic safety-net medical center in a rural, resource-lean state. The factors that can succeed and those that need further improvements were analyzed in this initial assessment phase of our efforts to shorten the RTT. Methods This is an analysis of 28 cervix cancer patients treated with magnetic resonance imaging (MRI)-guided brachytherapy (February 2020-November 2021). The relationship between independent and dependent variable were analyzed by simple linear regression, and p-values ≤ 0.05 were considered statistically significant. SPSS software version 28.0 (IBM, Armonk, NY, USA) was used for statistical analysis. Results Two RTT groups (≤ 60 (32.1%) vs. > 60 days {67.9%}) with median RTT of 68 days (range, 51 to 106 days) were analyzed. Caucasians represented 66.7% of the RTT ≤ 60 days group. Four 'issues' were identified that increased the RTT: non-compliance, learning curve (early days of implementation of MRI-guided brachytherapy in the department), stage IV comorbidities, and with more than one issue mentioned; 77.8% with no issues had ≤ 60 days RTT vs. 26.3% for the > 60 days group. The breakdown of the no-issues factor by calendar year showed the RTT of ≤ 60 days was achieved higher in 2021 (85.7% vs. 20.0%; p=0.023) compared to 2020. For this entire cohort, the RTT of ≤ 60 days was achieved higher in 2021 (50.0% vs. 8.3%; p=0.019) compared to 2020. Data also showed improvement in RTT of ≤ 60 days for every sequential six months. 'Non-compliance' and 'learning curve' were the most important factors among patients having the longest RTTs. Conclusion The RTT can be further decreased. As a result of this preliminary analysis of the our strategic planning approach of 'circular' "See it," "Own it," "Solve it," and "Do it" and go back to the first step again, we plan to implement the following strategies in the immediate future to shorten the RTTs further and, in turn, improve our overall outcomes (local/regional control, disease-free survival, and overall survival): (a) Interdigitate MRI-guided brachytherapy during external beam radiotherapy (EBRT); patients who can not get the interdigitated brachytherapy procedures performed during the course of EBRT for any reason will receive two brachytherapy procedures per week; (c) attempt to add a cervix cancer care navigator to our staff to help patients having social issues, thus leading to compliance problems; (d) finally, in a year or two after these new strategic implementations, the RTT data will be reanalyzed.

Multiparametric Magnetic Resonance Imaging in the Assessment of Primary Brain Tumors Through Radiomic Features: A Metric for Guided Radiation Treatment Planning.

Purpose The definition of radiotherapy target volume is a critical step in treatment planning for all tumor sites. Conventional magnetic resonance imaging (MRI) pulse sequences are used for the definition of the gross target volume (GTV) and the contouring of glioblastoma multiforme (GBM) and meningioma. We propose the use of multiparametric MRI combined with radiomic features to improve the texture-based differentiation of tumor from edema for GTV definition and to differentiate vasogenic from tumor cell infiltration edema. Methods Twenty-five patients with brain tumor and peritumoral edema (PTE) were assessed. Of the enrolled patients, 17 (63 ± 10 years old, six female and 11 male patients) were diagnosed with GBM and eight (64 ± 14 years old, five female and three male patients) with meningioma. A 3 Tesla (3T) MRI scanner was used to scan patients using a 3D multi-echo Gradient Echo (GRE) sequence. After the acquisition process, two experienced neuroradiologists independently used an in-house semiautomatic algorithm to conduct a segmentation of two regions of interest (ROI; edema and tumor) in all patients using functional MRI sequences, apparent diffusion coefficient (ADC), and dynamic contrast-enhanced MRI (DCE-MRI), as well as anatomical MRI sequences-T1-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR). Radiomic (computer-extracted texture) features were extracted from all ROIs through different approaches, including first-, second-, and higher-order statistics, both with and without normalization, leading to the calculation of around 300 different texture parameters for each ROI. Based on the extracted parameters, a least absolute shrinkage and selection operator (LASSO) analysis was used to isolate the parameters that best differentiated edema from tumors while irrelevant parameters were discarded. Results and conclusions The parameters chosen by LASSO were used to perform statistical analyses which allowed identification of the variables with the best discriminant ability in all scenarios. Receiver operating characteristic results showcase both the best single discriminator and the discriminant capacity of the model using all variables selected by LASSO. Excellent results were obtained for patients with GBM with all MRI sequences, with and without normalization; a T1-weighted sequence postcontrast (T1W+C) with normalization offered the best tumor classification (area under the curve, AUC > 0.97). For patients with meningioma, a good model of tumor classification was obtained through the T1-weighted sequence (T1W) without normalization (AUC > 0.71). However, there was no agreement between the results of both radiologists for some MRI sequences analyzed for patients with GBM and meningioma. In conclusion, a small subset of radiomic features showed an excellent ability to distinguish edema from tumor tissue through its most discriminating features.