BACKGROUND: The current clinical staging of pleural mesothelioma (PM) is often discordant with the pathologic staging. This study aimed to identify clinical and radiological features that could help predict unresectability in PM.
METHODS: Twenty-two descriptive radiologic features were retrospectively evaluated on preoperative computed tomography (CT) and/or positron emission tomography/CT (PET/CT) performed in patients with presumably resectable PM who underwent surgery. Measurements of maximum and sum pleural thickness at three levels of the thorax (upper, middle, and lower) were taken and stratified based on the cutpoints provided by the International Association for the Study of Lung Cancer (IASLC). Clinical and radiological features, including clinical-stage, were compared between resectable and unresectable tumors by univariate analysis and logistic regression modeling.
RESULTS: Of 133 patients, 69/133 (52%) had resectable and 64/133 (48%) had unresectable PM. Asbestos exposure (p = 0.005), neoadjuvant treatment (p = 0.001), clinical T-stage (p < 0.0001), all pleural thickness measurements (p < 0.05), pleural thickness pattern (p < 0.0001) and degree (p = 0.033), lung invasion (p = 0.004), extrapleural space obliteration (p < 0.0001), extension to subphrenic space (p = 0.0004), and two combination variables representing extensive diaphragmatic contact and/or chest wall involvement (p = 0.002) and mediastinal invasion (p < 0.0001) were significant predictors at univariate analysis. At multivariable analysis, all models achieved a strong diagnostic performance (area under the curve (AUC) > 0.8). The two best-performing models were one that included the upper-level maximum pleural thickness, extrapleural space obliteration, and mediastinal infiltration (AUC = 0.876), and another that integrated clinical variables and radiological assessment through the clinical T-stage (AUC = 0.879).
CONCLUSIONS: Selected clinical and radiologic features, including pleural thickness measurements, appear to be strong predictors of unresectability in PM.
CONCLUSIONS: A more accurate prediction of unresectability in the preoperative assessment of patients with pleural mesothelioma may avoid unnecessary surgery and prompt initiation of nonsurgical treatments.
CONCLUSIONS: About half of pleural mesothelioma patients are reported to receive an incorrect disease stage preoperatively. Eleven features identified as predictors of unresectability were included in strongly performing predictive models. More accurate preoperative staging will help clinicians and patients choose the most appropriate treatments.

ANCA-associated vasculitides (AAV) comprise granulomatosis with polyangiitis (GPA), microscopic polyangiitis (MPA) and eosinophilic granulomatosis with polyangiitis. All forms may involve different organ systems, yet kidney and lung involvement are common and fatal in many cases. Here, we aimed to determine the predictive value of pulmonary disease manifestation and individual CT findings in AAV patients. Available CT scans and clinical information on mortality, renal outcomes, occurrence of relapses and damage scores were analysed retrospectively from a tertiary rheumatology center in Germany. We included a total of 94 AAV patients (49 with GPA, 41 with MPA). Forty-four patients had lung involvement with available CT scans, 70.5% of which with GPA and 72.7% with renal involvement. Nodule formation and cavities were more frequent among GPA patients, whereas ground-glass opacities (GGO), ILD and pleural effusion were observed predominantly in MPA patients. Over a median follow-up of 37 months, GPA patients had a slightly higher overall mortality, whereas end-stage kidney failure rates were significantly increased in MPA patients. Relapse frequencies were comparable between both entities. The presence of GGO and pleural effusion were associated with higher relapse rates, whereas nodules were negatively correlated with relapses. Notably, RTX-treated patients had less infections as compared to individuals under different therapies. Our data demonstrate the outstanding importance of characteristic CT patterns in AAV diagnosis assessment. Especially certain CT patterns including GGO and pleura effusion may help to identify patients who are at higher risk for relapsing disease.

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.

Bottom-up growth offers precise control over the structure and geometry of semiconductor nanowires (NWs), enabling a wide range of possible shapes and seamless heterostructures for applications in nanophotonics and electronics. The most common vapor-liquid-solid (VLS) growth method features a complex interaction between the liquid metal catalyst droplet and the anisotropic structure of the crystalline NW, and the growth is mainly orchestrated by the triple-phase line (TPL). Despite the intrinsic mismatch between the droplet and the NW symmetries, its discussion has been largely avoided because of its complexity, which has led to the situation when multiple observed phenomena such as NW axial asymmetry or the oscillating truncation at the TPL still lack detailed explanation. The introduction of an electric field control of the droplet has opened even more questions, which cannot be answered without properly addressing three-dimensional (3D) structure and morphology of the NW and the droplet. This work describes the details of electric-field-controlled VLS growth of germanium (Ge) NWs using environmental transmission electron microscopy (ETEM). We perform TEM tomography of the droplet-NW system during an unperturbed growth, then track its evolution while modulating the bias potential. Using 3D finite element method (FEM) modeling and crystallographic considerations, we provide a detailed and consistent mechanism for VLS growth, which naturally explains the observed asymmetries and features of a growing NW based on its crystal structure. Our findings provide a solid framework for the fabrication of complex 3D semiconductor nanostructures with ultimate control over their morphology.

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.

OBJECTIVE: To evaluate a deep learning-based pipeline using a Dense-UNet architecture for the assessment of acute intracranial hemorrhage (ICH) on non-contrast computed tomography (NCCT) head scans after traumatic brain injury (TBI).
METHODS: This retrospective study was conducted using a prototype algorithm that evaluated 502 NCCT head scans with ICH in context of TBI. Four board-certified radiologists evaluated in consensus the CT scans to establish the standard of reference for hemorrhage presence and type of ICH. Consequently, all CT scans were independently analyzed by the algorithm and a board-certified radiologist to assess the presence and type of ICH. Additionally, the time to diagnosis was measured for both methods.
RESULTS: A total of 405/502 patients presented ICH classified in the following types: intraparenchymal (n = 172); intraventricular (n = 26); subarachnoid (n = 163); subdural (n = 178); and epidural (n = 15). The algorithm showed high diagnostic accuracy (91.24%) for the assessment of ICH with a sensitivity of 90.37% and specificity of 94.85%. To distinguish the different ICH types, the algorithm had a sensitivity of 93.47% and a specificity of 99.79%, with an accuracy of 98.54%. To detect midline shift, the algorithm had a sensitivity of 100%. In terms of processing time, the algorithm was significantly faster compared to the radiologist\'s time to first diagnosis (15.37 ± 1.85 vs 277 ± 14 s, p < 0.001).
CONCLUSIONS: A novel deep learning algorithm can provide high diagnostic accuracy for the identification and classification of ICH from unenhanced CT scans, combined with short processing times. This has the potential to assist and improve radiologists\' ICH assessment in NCCT scans, especially in emergency scenarios, when time efficiency is needed.

OBJECTIVE: To develop and validate imaging-based models for predicting the malignancy risk of intraductal papillary mucinous neoplasm (IPMN).
METHODS: We retrospectively analyzed data from 241 IPMN patients who underwent preoperative CT and MRI for model development. Cyst size, presence and size of the enhancing mural nodule (EMN), main pancreatic duct (MPD) diameter, thickened/enhancing cyst wall, abrupt MPD caliber change with distal atrophy, and lymphadenopathy were assessed. Multiple logistic regression models predicting malignancy risk were created using either continuous (Model C) or dichotomized variables (Model D) using these imaging features. Validation included internal (n = 55) and external (n = 43) datasets. Model performance was assessed using the area under the receiver operating characteristic curve (AUC) and compared with that of the international guideline-based model (Model F).
RESULTS: Model C identified age, EMN size, MPD diameter, and lymphadenopathy as independent predictors on CT, and age and presence and size of EMN on MRI. Model D identified age ≥ 68, cyst size ≥ 31 mm, EMN ≥ 6 mm, MPD ≥ 7 mm, and lymphadenopathy as independent predictors on CT, and age ≥ 68, EMN ≥ 4.5 mm, and lymphadenopathy on MRI. Model C (AUC, 0.763-0.899) performed slightly better than Model D (AUC, 0.753-0.912) without statistical significance. No significant difference was observed between Models C and F (AUC, 0.729-0.952). Combining Model C with obstructive jaundice improved performance (AUC, 0.802-0.941) without statistical significance.
CONCLUSIONS: Our imaging-based models effectively predicted the malignancy risk of IPMNs, comparable to international consensus guidelines.
CONCLUSIONS: Imaging features are important for predicting the malignant potential of IPMNs. Our imaging-based model may help determine surgical candidacy for patients with IPMNs.
CONCLUSIONS: Non-invasively determining the malignant potential of intraductal papillary mucinous neoplasms (IPMNs) allows for appropriate treatment decision-making We identified multiple imaging features that are associated with malignant transformation and developed models for this prediction. Our model performs comparably with international consensus guidelines in predicting the malignant potential of IPMNs.

UNASSIGNED: To demonstrate the feasibility of using a ring array ultrasound (US) transducer, guided by ultrasound tomography (UST), for generating and monitoring mild hyperthermia (MHTh).
UNASSIGNED: In silico and in vitro experiments were designed to evaluate the efficacy of a ring array US transducer for generating MHTh and monitoring changes in temperature. In a series of in silico studies, we compared the acoustic focal profiles produced by a ring array US transducer transmitting at different frequencies and further investigated the effectiveness of UST-guidance in implementing aberration correction to enhance the focal profile. In vitro experiments evaluated the capability of using a ring array US transducer to generate and maintain MHTh and the accuracy of using UST to monitor temperature changes.
UNASSIGNED: The simulations demonstrated that a ring array US transducer achieves symmetrical and localized acoustic focusing. In a heterogenous tissue model, a ring array US transducer achieved a superior acoustic focus by implementing aberration correction with guidance from UST. In vitro experiments demonstrated the capability of a ring array US transducer to generate MHTh in a tissue-mimicking phantom in an average of 117 ± 18 s and subsequently maintain MHTh. Lastly, a ring array US transducer utilized UST to track temperature changes in a preheated water-filled inclusion while it passively cooled from 45 °C to 25 °C, with a maximum error of 0.58 °C.
UNASSIGNED: A ring array US transducer can noninvasively generate and monitor MHTh, overcoming many limitations of current clinical systems. The closed geometry of the transducer is optimal for acoustic focusing and UST-guidance allows for improved aberration correction in a heterogenous medium. Utilizing UST thermometry with the same ring array US transducer will allow for implementing an image-guided, temperature-controlled, all-acoustic MHTh system.

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.