Low-dose ultrahigh-resolution PCCT enhances subsolid nodule characterization

High resolution CT in differentiating minimally invasive component in early lung adenocarcinoma

BackgroundWith the emergence of photon-counting CT, ultrahigh-resolution (UHR) imaging can be performed without dose penalty. This study aims to directly compare the image quality of UHR and standard resolution (SR) scan mode in femoral artery angiographies.MethodsAfter establishing continuous extracorporeal perfusion in four fresh-frozen cadaveric specimens, photon-counting CT angiographies were performed with a radiation dose of 5 mGy and tube voltage of 120 kV in both SR and UHR mode. Images were reconstructed with dedicated convolution kernels (soft: Body-vascular (Bv)48; sharp: Bv60; ultrasharp: Bv76). Six radiologists evaluated the image quality by means of a pairwise forced-choice comparison tool. Kendall’s concordance coefficient (W) was calculated to quantify interrater agreement. Image quality was further assessed by measuring intraluminal attenuation and image noise as well as by calculating signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNR).ResultsUHR yielded lower noise than SR for identical reconstructions with kernels ≥ Bv60 (p < 0.001). UHR scans exhibited lower intraluminal attenuation compared to SR (Bv60: 406.4 ± 25.1 versus 418.1 ± 30.1 HU; p < 0.001). Irrespective of scan mode, SNR and CNR decreased while noise increased with sharper kernels but UHR scans were objectively superior to SR nonetheless (Bv60: SNR 25.9 ± 6.4 versus 20.9 ± 5.3; CNR 22.7 ± 5.8 versus 18.4 ± 4.8; p < 0.001). Notably, UHR scans were preferred in subjective assessment when images were reconstructed with the ultrasharp Bv76 kernel, whereas SR was rated superior for Bv60. Interrater agreement was high (W = 0.935).ConclusionsCombinations of UHR scan mode and ultrasharp convolution kernel are able to exploit the full image quality potential in photon-counting CT angiography of the femoral arteries.Relevance statementThe UHR scan mode offers improved image quality and may increase diagnostic accuracy in CT angiography of the peripheral arterial runoff when optimized reconstruction parameters are chosen.Key points• UHR photon-counting CT improves image quality in combination with ultrasharp convolution kernels.• UHR datasets display lower image noise compared with identically reconstructed standard resolution scans.• Scans in UHR mode show decreased intraluminal attenuation compared with standard resolution imaging.Graphical

A Subsolid Nodules Imaging Reporting System (SSN-IRS) for Classifying 3 Subtypes of Pulmonary Adenocarcinoma

Pulmonary nodules present a unique challenge for radiologists which includes the detection of malignancy and identification of benign disease, recommending the appropriate procedures to avoid unnecessary thoracotomy, and ensuring that excessive radiation from follow-up computed tomography (CT) examinations is kept to a minimum. Although seasoned radiologists can use an approach based on their extensive experience, in this era of evidence-based medicine, guidelines have been established that include both radiologic and clinical factors in an integrated fashion. Such guidelines have been developed by the Fleischner Society, first in 2005, for the management of small pulmonary nodules detected on CT scans, and then, in 2013, for the management of sub-solid nodules [1]. For incidentally detected solitary nodules, these guidelines integrate elements as individual risk factors (via pre-test probability), with lesion size, growth rate, and morphology, based on imaging characteristics. Relevant risk factors to consider in the evaluation of pulmonary nodules are smoking history and patient age. Patients with a substantial smoking history and over 40 years of age are defined as high-risk patients, whereas low-risk patients are those with a negligible smoking history and no other known risk factors, and who are below 40 years of age. Based on the Fleischner Society recommendation [1], lesions less than 4 mm do not require any further invasive or non-invasive measures or evaluations. However, lesions with a diameter of more than 8mm should be evaluated with either follow-up CT scans, including dynamic, contrast-enhanced scans, positron emission tomography (PET)-CT, and biopsy. For lesions that fall between the 4 mm and 8 mm size, CT follow-up with a limited number of scans is recommended. Sub-solid nodules are often found during screening studies or incidentally on CT scans. They are characterized by their appearance as rounded areas of increased attenuation, and a homogeneous or heterogeneous texture. Sub-solid nodules can be subdivided according to their composition: non-solid lesions that consist of ground-glass opacity only; and part solid lesions that contain both ground-glass and soft tissue elements. Sub-solid nodules can regress, persist, or grow. Small persistent non-solid nodules are often atypical adenomatous hypoplasia (AAH) and focal fibrosis, whereas non-solid and part-solid nodules that increase in size typically indicate malignancy, which can include adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma, as well as lympho-proliferative disease. How these lesions develop has not been entirely elucidated as yet, but it seems that a small percentage of ground-glass opacities (AAH) develop into larger lesions that can eventually comprise solid components due to invasion and alveolar collapse [2]. In any case, radiologically, an increase in lesion density, growth, or the development of solid portions are all indicative of malignancy. CT analysis and surveillance of sub-solid nodules is the modality of choice for the identification of malignant lesions. The primary factor is nodule size. While lesions less than 5 mm in diameter are usually AAHs, lesions greater than 15 mm is size are malignant, and are typically MIAs and invasive adenocarcinomas. Generally, a diameter of more than 8 mm is indicative of malignancy. Another important indicator of malignancy is lesion growth. The growth of the lesion may affect either the ground-glass or the solid components, or both. Volume doubling times of AIS and MIAs are much longer, compared to invasive adenocarcinomas and squamous cell lesions. Morphologically, the presence of lobulated borders, air bronchograms and bubble-like lucencies, and the development of solid portions in pure ground-glass abnormalities are all indicative of malignancy. Lesion morphology is closely related to prognosis. Nodules with an increasing percentage of solid components represent a poorer prognosis, but, for patients with pure ground-glass abnormalities or those with only a small area of a solid component, the survival rate after lesion resection is 100%. The Fleischner Society management guidelines [2] for sub-solid lesions recommend that part solid nodules, especially those that persist or grow in size, mandate further evaluation and monitoring, and typically, require surgical resection. Smaller lesions, with a negligible area of solid components, can be managed with follow-up CT scans.

The aim of this study was to investigate potential benefits of ultra-high resolution (UHR) over standard resolution scan mode in ultra-low dose photon-counting detector CT (PCD-CT) of the lung. Six cadaveric specimens were examined with 5 dose settings using tin prefiltration, each in UHR (120 × 0.2 mm) and standard mode (144 × 0.4 mm), on a first-generation PCD-CT scanner. Image quality was evaluated quantitatively by noise comparisons in the trachea and both main bronchi. In addition, 16 readers (14 radiologists and 2 internal medicine physicians) independently completed a browser-based pairwise forced-choice comparison task for assessment of subjective image quality. The Kendall rank coefficient ( W ) was calculated to assess interrater agreement, and Pearson's correlation coefficient ( r ) was used to analyze the relationship between noise measurements and image quality rankings. Across all dose levels, image noise in UHR mode was lower than in standard mode for scan protocols matched by CTDI vol ( P < 0.001). UHR examinations exhibited noise levels comparable to the next higher dose setting in standard mode ( P ≥ 0.275). Subjective ranking of protocols based on 5760 pairwise tests showed high interrater agreement ( W = 0.99; P ≤ 0.001) with UHR images being preferred by readers in the majority of comparisons. Irrespective of scan mode, a substantial indirect correlation was observed between image noise and subjective image quality ranking ( r = -0.97; P ≤ 0.001). In PCD-CT of the lung, UHR scan mode reduces image noise considerably over standard resolution acquisition. Originating from the smaller detector element size in fan direction, the small pixel effect allows for superior image quality in ultra-low dose examinations with considerable potential for radiation dose reduction.

Flow diverters are a crucial element in the treatment of intracranial aneurysms. However, the optimal non-invasive follow-up imaging modality, particularly for the detection of in-stent stenosis, remains uncertain. This study aims to compare the performance of photon-counting detector CT (PCD-CT) in ultra-high-resolution (UHR) mode with flat-panel CT (FP-CT) for the evaluation of intracranial flow diverters. A phantom model for intracranial vessels was used to evaluate 15 flow diverters of various sizes and designs. Imaging was performed using both PCD-CT and FP-CT. Qualitative assessment of the stent lumen was conducted by three experienced neuroradiologists using a 5-point Likert scale. Quantitative analysis included measurements of lumen area, contrast to noise ratio and signal to noise ratio. FP-CT provided a significantly larger assessable stent lumen than PCD-CT at all dose levels (p < 0.05), with no significant differences between PCD-CT dose levels (p = 0.999). Increasing PCD-CT dose did not improve lumen visualization. SNR and CNR increased with PCD-CT dose (p < 0.001), peaking at CTDI 20, but showed diminishing returns beyond CTDI 10. Flow diverter diameter correlated positively with SNR and CNR (p < 0.05). Subjective image quality improved with PCD-CT dose (p < 0.001) but showed no significant difference beyond 10 mGy (p > 0.05). FRED devices had the lowest ratings, independent of imaging modality (p = 0.80). Our study demonstrated that while FP-CT provided superior visualization of the flow diverter lumen in a head phantom vessel model, subjective assessability ratings were comparable between FP-CT and PCD-CT when evaluated by experienced readers. PCD-CT at a CTDIvol of 10 mGy offered the best balance between image quality and radiation dose, making it a viable alternative for post-interventional assessment of flow diverters.

A CT-based deep learning model for subsolid pulmonary nodules to distinguish minimally invasive adenocarcinoma and invasive adenocarcinoma

Pancreatic cancer remains highly lethal, with a 5-year survival below 15%. While surgical resection is the only potentially curative approach, conventional imaging often fails to clearly delineate tumor boundaries and adjacent anatomy, compromising preoperative planning and surgical precision. This review summarizes recent advancements in photon-counting computed tomography (PCCT) for pancreatic cancer imaging and surgical planning. A literature search was conducted to identify relevant studies published between 2018 and 2025, focusing on PCCT’s role in tumor visualization, comprehensive vascular mapping including invasion and anatomical variants, lymph node detection, and surgical navigation. PCCT provides ultra-high spatial resolution and intrinsic spectral imaging capabilities, significantly improving the visualization of low-contrast pancreatic tumors and subtle anatomical details. Emerging preliminary clinical evidence highlights PCCT’s potential to enhance diagnostic accuracy, precisely assess tumor resectability, and guide surgical interventions. As clinical adoption expands, PCCT may become a key imaging tool for precision management of pancreatic cancer.

To explore the natural history of pulmonary subsolid nodules (SSNs) with different pathological types by deep learning-assisted nodule segmentation. Between June 2012 and June 2019, 95 resected SSNs with preoperative long-term follow-up were enrolled in this retrospective study. SSN detection and segmentation were performed on preoperative follow-up CTs using the deep learning-based Dr. Wise system. SSNs were categorized into invasive adenocarcinoma (IAC, n = 47) and non-IAC (n = 48) groups; according to the interval change during the preoperative follow-up, SSNs were divided into growth (n = 68), nongrowth (n = 22), and new emergence (n = 5) groups. We analyzed the cumulative percentages and pattern of SSN growth and identified significant factors for IAC diagnosis and SSN growth. The mean preoperative follow-up was 42.1 ± 17.0 months. More SSNs showed growth or new emergence in the IAC than in the non-IAC group (89.4% vs. 64.6%, p = 0.009). Volume doubling time was non-significantly shorter for IACs than for non-IACs (1436.0 ± 1188.2 vs. 2087.5 ± 1799.7 days, p = 0.077). Median mass doubling time was significantly shorter for IACs than for non-IACs (821.7 vs. 1944.1 days, p = 0.001). Lobulated sign (p = 0.002) and SSN mass (p = 0.004) were significant factors for differentiating IACs. IACs showed significantly higher cumulative growth percentages than non-IACs in the first 70 months of follow-up. The growth pattern of SSNs may conform to the exponential model. The initial volume (p = 0.042) was a predictor for SSN growth. IACs appearing as SSNs showed an indolent course. The mean growth rate was larger for IACs than for non-IACs. SSNs with larger initial volume are more likely to grow. • Invasive adenocarcinomas (IACs) appearing as subsolid nodules (SSNs), with a mean volume doubling time (VDT) of 1436.0 ± 1188.2 days and median mass doubling time (MDT) of 821.7 days, showed an indolent course. • The VDT was shorter for IACs than for non-IACs (1436.0 ± 1188.2 vs. 2087.5 ± 1799.7 days), but the difference was not significant (p = 0.077). The median MDT was significantly shorter for IACs than for non-IACs (821.7 vs. 1944.1 days, p = 0.001). • SSNs with lobulated sign and larger mass (> 390.5 mg) may very likely be IACs. SSNs with larger initial volume are more likely to grow.

Photon counting CT versus multi-slice CT for radiographic evaluation of postoperative cochlear implantation: Electrode characteristics and image-quality analysis.

ObjectiveTo investigative the diagnostic performance of the morphological model, radiomics model, and combined model in differentiating invasive adenocarcinomas (IACs) from minimally invasive adenocarcinomas (MIAs).MethodsThis study retrospectively involved 307 patients who underwent chest computed tomography (CT) examination and presented as subsolid pulmonary nodules whose pathological findings were MIAs or IACs from January 2010 to May 2018. These patients were randomly assigned to training and validation groups in a ratio of 4:1 for 10 times. Eighteen categories of morphological features of pulmonary nodules including internal and surrounding structure were labeled. The following radiomics features are extracted: first-order features, shape-based features, gray-level co-occurrence matrix (GLCM) features, gray-level size zone matrix (GLSZM) features, gray-level run length matrix (GLRLM) features, and gray-level dependence matrix (GLDM) features. The chi-square test and F1 test selected morphology features, and LASSO selected radiomics features. Logistic regression was used to establish models. Receiver operating characteristic (ROC) curves evaluated the effectiveness, and Delong analysis compared ROC statistic difference among three models.ResultsIn validation cohorts, areas under the curve (AUC) of the morphological model, radiomics model, and combined model of distinguishing MIAs from IACs were 0.88, 0.87, and 0.89; the sensitivity (SE) was 0.68, 0.81, and 0.83; and the specificity (SP) was 0.93, 0.79, and 0.87. There was no statistically significant difference in AUC between three models (p > 0.05).ConclusionThe morphological model, radiomics model, and combined model all have a high efficiency in the differentiation between MIAs and IACs and have potential to provide non-invasive assistant information for clinical decision-making.

Clinical photon-counting CT (PCCT) offers a spatial resolution of about 200 µm and might allow for acquisitions close to conventional dental CBCTs. In this study, the capabilities of this new system in comparison to dental CBCTs shall be evaluated. All 8 apical osteolysis identified in CBCT were identified by both readers in all three PCCT scan protocols. Mean visibility scores showed statistical significant differences for root canals(p = 0.0001), periodontal space(p = 0.0090), cortical(p = 0.0003) and spongious bone(p = 0.0293) in favor of high and medium dose PCCT acquisitions. Overall, both devices showed excellent image quality of all structures assessed. Interrater-agreement showed high values for all protocols in all structures. Bland–Altman plots revealed a high concordance of both modalities with the reference measurements. In vitro, ultra-high resolution PCCT can reliably identify different diagnostic entities and structures relevant for dental diagnostics similar to conventional dental CBCT with similar radiation dose. Acquisitions of five cadaveric heads were performed in an experimental CT-system containing an ultra-high resolution PC detector (0.25 mm pixel size in isocenter) as well as in a dental CBCT scanner. Acquisitions were performed using dose levels of 8.5 mGy, 38.0 mGy and 66.5 mGy (CTDI16cm) in case of PCCT and of 8.94 mGy (CTDI16cm) in case of CBCT. The quality of delineation of hard tissues, root-canals, periodontal-space as well as apical osteolysis was assessed by two readers. Mean visibility scores and interrater-agreement (overall agreement (%)) were calculated. Vertical bone loss (bl) and thickness (bt) of the buccal bone lamina of 15 lower incisors were measured and compared to reference measurements by ore microscopy and clinical probing.

ObjectiveTo investigate the image quality of a low-dose dental imaging protocol in the first clinical photon-counting computed tomography (PCCT) system in comparison to a normal-dose acquisition in a digital volume tomography (DVT) system. Materials and methodsClinical PCCT systems offer an increased spatial resolution compared to previous generations of clinical systems. Their spatial resolution is in the order of dental DVT systems. Resolution-matched acquisitions of ten porcine jaws were performed in a PCCT (Naeotom Alpha, Siemens Healthineers) and in a DVT (Orthophos XL, Dentsply Sirona). PCCT images were acquired with 90 kV at a dose of 1 mGy CTDI16 cm. DVT used 85 kV at 4 mGy. Image reconstruction was performed using the standard algorithms of each system to a voxel size of 160 × 160 × 200 µm. The dose-normalized contrast-to-noise ratio (CNRD) was measured between dentine and enamel and dentine and bone. Two readers evaluated overall diagnostic quality of images and quality of relevant structures such as root channels and dentine. ResultsCNRD is higher in all PCCT acquisitions. CNRD is 37 % higher for the contrast dentine-enamel and 31 % higher for the dentine-bone contrast (p < 0.05). Overall diagnostic image quality was higher for PCCT over DVT (p < 0.02 and p < 0.04 for readers 1 and 2). Quality scores for anatomical structures were higher in PCCT compared to DVT (all p < 0.05). Inter- and intrareader reproducibility were acceptable (all ICC>0.64). ConclusionsPCCT provides an increased image quality over DVT even at a lower dose level and might enable complex dental imaging protocols in the future. Clinical significanceThe evolution of photon-counting technology and it's optimization will increasingly move dental imaging towards standardized 3D visualizations providing both minimal radiation exposure and high diagnostic accuracy.

Objectives:To evaluate the clinical performance of a cadmium-zinc-telluride- (CZT-) based photon-counting computed tomography (PCCT) system for low-dose lung cancer screening (LCS-LDCT) using patient-specific 3D-printed lung phantoms, and to compare its image quality and radiomics consistency with a conventional energy-integrating detector CT (EIDCT) system.Methods:Six 3D-printed lung phantoms, derived from patient CT datasets and representing various lesion types (solid, part-solid, and ground-glass), were imaged on PCCT and EIDCT scanners at matched dose levels (1.6 – 20.4 mGy). Quantitative image metrics, Hounsfield unit (HU) accuracy, image noise, and contrast-to-noise ratio (CNR), were assessed across dose levels. Radiomic features were extracted for each lesion and analyzed via principal component analysis to quantify feature consistency (within-cluster distance) and lesion type separability.Results:PCCT demonstrated significantly lower image noise and higher CNR compared with EIDCT, particularly at lower dose levels. HU values were consistent across doses for both systems, with reduced variability in PCCT (coefficient of variation < 0.004). Radiomics analysis revealed tighter clustering (reduced within-cluster distances) and comparable lesion type separability between PCCT and EIDCT, indicating enhanced feature stability and lesion differentiation. Qualitative review confirmed superior lesion conspicuity and margin delineation with PCCT.Conclusions:CZT-based PCCT outperforms conventional EIDCT in quantitative and qualitative imaging metrics for LCS-LDCT, enabling superior image quality and radiomics reproducibility at reduced radiation doses. These findings support the clinical translation of PCCT for lung cancer screening and radiomics-based lesion characterization.

ObjectivesThis study aimed to evaluate the feasibility of low-tube-potential ultra-high-resolution (UHR) coronary CT angiography (CCTA) using photon-counting detector CT (PCD-CT) in comparison to low-tube-potential CCTA using energy-integrating detector CT (EID-CT), with a specific focus on the evaluation of coronary stents.Materials and methodsThis retrospective study included 54 patients (88 stents) who underwent CCTA in UHR mode on PCD-CT at low tube potential (PCDUHR-low; 27 patients [45 stents]) or CCTA with EID-CT at low tube potential (EID-low; 27 patients [43 stents]). The EID-low cohort was selected by propensity score matching to the PCDUHR-low cohort. Image quality of in-stent lumen was assessed using a 4-point Likert scale, with a score of 4 indicating “excellent.” Quantitative assessment of stents included stent-induced blooming, edge sharpness, stent full width at half maximum (FWHM) and ΔHUin-stent which quantifies the increase in CT attenuation within the stent lumen. Radiation dose was evaluated using CT dose index volume (CTDIvol) and dose–length product (DLP).ResultsPCDUHR-low had higher image quality scores than EID-low (scores of 3 and 4, 82.2% vs. 53.5%; p = 0.02). PCDUHR-low showed reduced stent-induced blooming, superior edge sharpness, smaller stent FWHM and smaller ΔHUin-stent than EID-low (all, p < 0.01). CTDIvol and DLP in PCDUHR-low (9.3 ± 4.4 mGy and 107.1 ± 50.4 mGy・cm) were comparable to those of EID-low (10.5 ± 5.9 mGy and 118.2 ± 74.9 mGy・cm), respectively. (p = 0.26 and 0.47).ConclusionCCTA using UHR mode in PCD-CT at low tube potential achieved superior image quality for implanted stent visualization as compared to EID-CT at low tube potential, while maintaining comparable radiation doses.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11604-025-01846-x.