BACKGROUND: With the development of immune checkpoint inhibitors for the treatment of non-small cell lung cancer, the need for new functional imaging techniques and early response assessments has increased to account for new response patterns and the high cost of treatment. The present study was designed to assess the prognostic impact of dynamic contrast-enhanced computed tomography (DCE-CT) on survival outcomes in non-small cell lung cancer patients treated with immune checkpoint inhibitors.
METHODS: Thirty-three patients with inoperable non-small-cell lung cancer treated with immune checkpoint inhibitors were prospectively enrolled for DCE-CT as part of their follow-up. A single target lesion at baseline and subsequent follow-up examinations were enclosed in the DCE-CT. Blood volume deconvolution (BVdecon), blood flow deconvolution (BFdecon), blood flow maximum slope (BFMax slope) and permeability were assessed using overall survival (OS) and progression-free survival (PFS) as endpoints in Kaplan Meier and Cox regression analyses.
RESULTS: High baseline Blood Volume (BVdecon) (> 12.97 ml × 100 g-1) was associated with a favorable OS (26.7 vs 7.9 months; p = 0.050) and PFS (14.6 vs 2.5 months; p = 0.050). At early follow-up on day seven a higher relative increase in BFdecon (> 24.50% for OS and > 12.04% for PFS) was associated with an unfavorable OS (8.7 months vs 23.1 months; p < 0.025) and PFS (2.5 vs 13.7 months; p < 0.018). The relative change in BFdecon (categorical) on day seven was a predictor of OS (HR 0.26, CI95: 0.06 to 0.93 p = 0.039) and PFS (HR 0.27, CI95: 0.09 to 0.85 p = 0.026).
CONCLUSIONS: DCE-CT-identified parameters may serve as potential prognostic biomarkers at baseline and during early treatment in patients with NSCLC treated with immune checkpoint inhibitor therapy.

BACKGROUND: This study investigated and compared the efficacy, safety, radiation exposure, and financial compensation of two modalities for percutaneous radiologic gastrostomy (PRG): multislice computed tomography biopsy mode (MS-CT BM)-guided and fluoroscopy-guided (FPRG). The aim was to provide insights into optimizing radiologically assisted gastrostomy procedures.
METHODS: We conducted a retrospective analysis of PRG procedures performed at a single center from January 2018 to January 2024. The procedures were divided into two groups based on the imaging modality used. We compared patient demographics, intervention parameters, complication rates, and procedural times. Financial compensation was evaluated based on the tariff structure for outpatient medical services in Switzerland (TARMED). Statistical differences were determined using Fisher\'s exact test and the Mann-Whitney U test.
RESULTS: The study cohort included 133 patients: 55 with MS-CT BM-PRG and 78 with FPRG. The cohort comprised 35 women and 98 men, with a mean age of 64.59 years (±11.91). Significant differences were observed between the modalities in effective dose (MS-CT BM-PRG: 10.95 mSv ± 11.43 vs. FPRG: 0.169 mSv ± 0.21, p < 0.001) and procedural times (MS-CT BM-PRG: 41.15 min ± 16.14 vs. FPRG: 28.71 min ± 16.03, p < 0.001). Major complications were significantly more frequent with FPRG (10% vs. 0% in MS-CT BM-PRG, p = 0.039, φ = 0.214). A higher single-digit number of MS-CT BM-guided PRG was required initially to reduce procedure duration by 10 min. Financial comparison revealed that only 4% of MS-CT BM-guided PRGs achieved reimbursement equivalent to the most frequent comparable examination, according to TARMED.
CONCLUSIONS: Based on our experience from a retrospective, single-center study, the execution of a PRG using MS-CT BM, as opposed to FPRG, is currently justified in challenging cases despite a lower incidence of major complications. However, further well-designed prospective multicenter studies are needed to determine the efficacy, safety, and cost-effectiveness of these two modalities.

In this pilot study, we investigated the utility of handheld ultrasound-guided photoacoustic (US-PA) imaging probe for analyzing ex-vivo breast specimens obtained from female patients who underwent breast-conserving surgery (BCS). We aimed to assess the potential of US-PA in detecting biochemical markers such as collagen, lipids, and hemoglobin, and compare these findings with routine imaging modalities (mammography, ultrasound) and histopathology results, particularly across various breast densities. Twelve ex-vivo breast specimens were obtained from female patients with a mean age of 59.7 ± 9.5 years who underwent BCS. The tissues were illuminated using handheld US-PA probe between 700 and 1100 nm across all margins and analyzed for collagen, lipids, and hemoglobin distribution. The obtained results were compared with routine imaging and histopathological assessments. Our findings revealed that lipid intensity and distribution decreased with increasing breast density, while collagen exhibited an opposite trend. These observations were consistent with routine imaging and histopathological analyses. Moreover, collagen intensity significantly differed (P < 0.001) between cancerous and normal breast tissue, indicating its potential as an additional biomarker for risk stratification across various breast conditions. The study results suggest that a combined assessment of PA biochemical information, such as collagen and lipid content, superimposed on grey-scale ultrasound findings could aid in distinguishing between normal and malignant breast conditions, as well as assist in BCS margin assessment. This underscores the potential of US-PA imaging as a valuable tool for enhancing breast cancer diagnosis and management, offering complementary information to existing imaging modalities and histopathology.

Diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT) and electrodeless conductivity tensor imaging (CTI) are two emerging modalities that can quantify low-frequency tissue anisotropic conductivity properties by assuming similar properties underlie ionic mobility and water diffusion. While both methods have potential applications to estimating neuro-modulation fields or formulating forward models used for electrical source imaging, a direct comparison of the two modalities has not yet been performed in-vitro or in-vivo. Therefore, the aim of this study was to test the equivalence of these two modalities. We scanned a tissue phantom and the head of human subject using DT-MREIT and CTI protocols and reconstructed conductivity tensor and effective low frequency conductivities. We found both gray and white matter conductivities recovered by each technique were equivalent within 0.05 S/m. Both DT-MREIT and CTI require multiple processing steps, and we further assess the effects of each factor on reconstructions and evaluate the extent to which different measurement mechanisms potentially cause discrepancies between the two methods. Finally, we discuss the implications for spectral models of measuring conductivity using these techniques. The study further establishes the credibility of CTI as an electrodeless non-invasive method of measuring low frequency conductivity properties.

The development of non-destructive, tomographic imaging systems is a current topic of research in biomedical technologies. One of these technologies is Scanning Laser Optical Tomography (SLOT), which features a highly modular setup with various contrast mechanisms. Extending this technology with new acquisition mechanisms allows us to investigate untreated and non-stained biological samples, leaving their natural biological physiology intact. To enhance the development of SLOT, we aimed to extend the density of information with a significant increase of acquisition channels. This should allow us to investigate samples with unknown emission spectra and even allow for label-fee cell identification. We developed and integrated a hyperspectral module into an existing SLOT system. The adaptations allow for the acquisition of three-dimensional datasets containing a highly increased information density. For validation, artificial test objects were made from fluorescent acrylic and acquired with the new hyperspectral setup. In addition, measurements were made on two different human cell spheroids with an unknown spectra, to test the possibilities of label-free cell identification. The validation measurements of the artificial test target show the expected results. Furthermore, the measurements of the biological cell spheroids show small variations in their tomographic spectrum that allow for label-free cell type differentiation. The results of the biological sample demonstrate the potential of label-free cell identification of the newly developed setup.

Our objective was to develop and evaluate the clinical feasibility of deep-learning-based synthetic contrast-enhanced computed tomography (DL-SynCCT) in patients designated for nonenhanced CT (NECT). We proposed a weakly supervised learning with the utilization of virtual non-contrast CT (VNC) for the development of DL-SynCCT. Training and internal validations were performed with 2202 pairs of retrospectively collected contrast-enhanced CT (CECT) images with the corresponding VNC images acquired from dual-energy CT. Clinical validation was performed using an external validation set including 398 patients designated for true nonenhanced CT (NECT), from multiple vendors at three institutes. Detection of lesions was performed by three radiologists with only NECT in the first session and an additionally provided DL-SynCCT in the second session. The mean peak signal-to-noise ratio (PSNR) and structural similarity index map (SSIM) of the DL-SynCCT compared to CECT were 43.25 ± 0.41 and 0.92 ± 0.01, respectively. With DL-SynCCT, the pooled sensitivity for lesion detection (72.0% to 76.4%, P < 0.001) and level of diagnostic confidence (3.0 to 3.6, P < 0.001) significantly increased. In conclusion, DL-SynCCT generated by weakly supervised learning showed significant benefit in terms of sensitivity in detecting abnormal findings when added to NECT in patients designated for nonenhanced CT scans.

UNASSIGNED: To determine which combination of imaging modalities/contrast, radiomics models, and how many features provides the best diagnostic performance for the differentiation between low- and high-grade soft tissue sarcomas (STS) using a radiomics approach.
UNASSIGNED: MRI and CT from 39 patients with a histologically confirmed STS were prospectively analyzed. Images were evaluated both quantitatively by radiomics models and qualitatively by visual evaluation (used as reference) for grading (low-grade vs high-grade). In radiomics analysis, 120 radiomic features were extracted and contributed into three models: least absolute shrinkage and selection operator with logistic regression(LASSO-LR), recursive feature elimination and cross-validation (RFECV-SVC) and analysis of variance with SVC (ANOVA-SVC). Those were applied to different combinations of imaging modalities acquisition, with and without contrast medium administration, as well as selected number of features.
UNASSIGNED: Fat-saturated T2w (FS-T2w) MR images using RFECV-SVC radiomic models involving five features yielded the best results with mean sensitivity, specificity, and accuracy of 92% ± 10%, 78% ± 30%, and 89% ± 12%, respectively. The performance of radiomics was better than that of conventional analysis (67% accuracy) for STS grading. Combination of multiple contrast or imaging modalities did not increase the diagnostic performance.
UNASSIGNED: FS-T2w MR images alone with a five-feature radiomics analysis usingh REFCV-SVC model may be able to provide sufficient diagnositic performance compared to conventional visual evaluation with multiple MRI contrast and CT imaging.

Pulmonary monitoring is crucial for the diagnosis and management of respiratory conditions, especially after the epidemic of coronavirus disease. Electrical impedance tomography (EIT) is an alternative non-radioactive tomographic imaging tool for monitoring pulmonary conditions. This review proffers the current EIT technical principles and applications on pulmonary monitoring, which gives a comprehensive summary of EIT applied on the chest and encourages its extensive usage to clinical physicians. The technical principles involving EIT instrumentations and image reconstruction algorithms are explained in detail, and the conditional selection is recommended based on clinical application scenarios. For applications, specifically, the monitoring of ventilation/perfusion (V/Q) is one of the most developed EIT applications. The matching correlation of V/Q could indicate many pulmonary diseases, e.g., the acute respiratory distress syndrome, pneumothorax, pulmonary embolism, and pulmonary edema. Several recently emerging applications like lung transplantation are also briefly introduced as supplementary applications that have potential and are about to be developed in the future. In addition, the limitations, disadvantages, and developing trends of EIT are discussed, indicating that EIT will still be in a long-term development stage before large-scale clinical applications.

The radiomic analysis of the tissue surrounding colorectal liver metastases (CRLM) enhances the prediction accuracy of pathology data and survival. We explored the variation of the textural features in the peritumoural tissue as the distance from CRLM increases. We considered patients with hypodense CRLMs >10 mm and high-quality computed tomography (CT). In the portal phase, we segmented (1) the tumour, (2) a series of concentric rims at a progressively increasing distance from CRLM (from one to ten millimetres), and (3) a cylinder of normal parenchyma (Liver-VOI). Sixty-three CRLMs in 51 patients were analysed. Median peritumoural HU values were similar to Liver-VOI, except for the first millimetre around the CRLM. Entropy progressively decreased (from 3.11 of CRLM to 2.54 of Liver-VOI), while uniformity increased (from 0.135 to 0.199, p < 0.001). At 10 mm from CRLM, entropy was similar to the Liver-VOI in 62% of cases and uniformity in 46%. In small CRLMs (≤30 mm) and responders to chemotherapy, normalisation of entropy and uniformity values occurred in a higher proportion of cases and at a shorter distance. The radiomic analysis of the parenchyma surrounding CRLMs unveiled a wide halo of progressively decreasing entropy and increasing uniformity despite a normal radiological aspect. Underlying pathology data should be investigated.

The aim of this study is to compare the diagnostic performance of magnetic resonance imaging (MRI) against computed tomography (CT) in various aspects of local staging in colon cancer patients. This study was a prospective single arm diagnostic accuracy study. All consecutive adult patients with confirmed colon cancer that met the current criteria for surgical resection were considered as eligible. Diagnostic performance assessment included T (T1/T2 vs T3/T4 and < T3ab vs > T3cd) and N (N positive) staging, serosa and retroperitoneal surgical margin (RSM) involvement and extramural vascular invasion (EMVI). Imaging was based on a 3 Tesla MRI system and the evaluation of all sequences (T1, T2 and diffusion-weighted imaging-DWI series) by two independent readers. CT scan was performed in a 128 row multidetector (MD) CT scanner (slice thickness: 1 mm) with intravenous contrast. Pathology report was considered as the gold standard for local staging. Sensitivity (SE), specificity (SP), and area under the curve (AUC) were calculated for both observers. MRI displayed a higher diagnostic performance over CT in terms of T1/T2 vs T3/T4 (SE: 100% vs 83.9%, SP: 96.6% vs 81%, AUC: 0.825 vs 0.983, p < 0.001), N positive (p < 0.001) and EMVI (p = 0.023) assessment. An excellent performance of MRI was noted in the T3ab vs T3cd (CT AUCReader1: 0.636, AUCReader2: 0.55 vs MRI AUCReader1: 0.829 AUCReader2 0.846, p = 0.01) and RSM invasion diagnosis. In contrast to these, MRI did not perform well in the identification of serosa invasion. MRI had a higher diagnostic yield than CT in several local staging parameters.