Interobserver agreement issues in radiology.Diagn Interv Imaging. 2020;101:639-641. [PMID: 32958434 DOI: 10.1016/j.diii.2020.09.001]

Inter-reader agreement of pancreatic adenocarcinoma resectability assessment with photon counting versus energy integrating detector CT

PURPOSE

To compare the inter-reader agreement of pancreatic adenocarcinoma resectability assessment at pancreatic protocol photon-counting CT (PCCT) with conventional energy-integrating detector CT (EID-CT).

METHODS

A retrospective single institution database search identified all contrast-enhanced pancreatic mass protocol abdominal CT performed at an outpatient facility with both a PCCT and EID-CT from 4/11/2022 to 10/30/2022. Patients without pancreatic adenocarcinoma were excluded. Four fellowship-trained abdominal radiologists, blinded to CT type, independently assessed vascular tumor involvement (uninvolved, abuts ≤ 180°, encases > 180°; celiac, superior mesenteric artery (SMA), common hepatic artery (CHA), superior mesenteric vein (SMV), main portal vein), the presence/absence of metastases, overall tumor resectability (resectable, borderline resectable, locally advanced, metastatic), and diagnostic confidence. Fleiss's kappa was used to calculate inter-reader agreement. CTDIvol was recorded. Radiation dose metrics were compared with a two-sample t-test. A p < .05 indicated statistical significance.

RESULTS

145 patients (71 men, mean[SD] age: 66[9] years) were included. There was substantial inter-reader agreement, for celiac artery, SMA, and SMV involvement at PCCT (kappa = 0.61-0.69) versus moderate agreement at EID-CT (kappa = 0.56-0.59). CHA had substantial inter-reader agreement at both PCCT (kappa = 0.67) and EIDCT (kappa = 0.70). For metastasis identification, radiologists had substantial inter-reader agreement at PCCT (kappa = 0.78) versus moderate agreement at EID-CT (kappa = 0.56). CTDIvol for PCCT and EID-CT were 16.9[7.4]mGy and 29.8[26.6]mGy, respectively (p < .001).

CONCLUSION

There was substantial inter-reader agreement for involvement of 4/5 major peripancreatic vessels (celiac artery, SMA, CHA, and SMV) at PCCT compared with 2/5 for EID-CT. PCCT also afforded substantial inter-reader agreement for metastasis detection versus moderate agreement at EID-CT with statistically significant radiation dose reduction.

LI-RADS v2018 category and imaging features: inter-modality agreement between contrast-enhanced CT, gadoxetate disodium-enhanced MRI, and extracellular contrast-enhanced MRI

PURPOSE

To perform an intra-individual comparison of LI-RADS category and imaging features in patients at high risk of hepatocellular carcinoma (HCC) on contrast-enhanced CT, gadoxetate disodium-enhanced MRI (EOB-MRI), and extracellular agent-enhanced MRI (ECA-MRI) and to analyze the diagnostic performance of each imaging modality.

METHOD

This retrospective study included cirrhotic patients with at least one LR-3, LR-4, LR-5, LR-M or LR-TIV observation imaged with at least two imaging modalities among CT, EOB-MRI, or ECA-MRI. Two radiologists evaluated the observations using the LI-RADS v2018 diagnostic algorithm. Reference standard included pathologic confirmation and imaging criteria according to LI-RADS v2018. Imaging features were compared between different exams using the McNemar test. Inter-modality agreement was calculated by using the weighted Cohen's kappa (k) test.

RESULTS

A total of 144 observations (mean size 34.0 ± 32.4 mm) in 96 patients were included. There were no significant differences in the detection of major and ancillary imaging features between the three imaging modalities. When considering all the observations, inter-modality agreement for category assignment was substantial between CT and EOB-MRI (k 0.60; 95%CI 0.44, 0.75), moderate between CT and ECA-MRI (k 0.46; 95%CI 0.22, 0.69) and substantial between EOB-MRI and ECA-MRI (k 0.72; 95%CI 0.59, 0.85). In observations smaller than 20 mm, inter-modality agreement was fair between CT and EOB-MRI (k 0.26; 95%CI 0.05, 0.47), moderate between CT and ECA-MRI (k 0.42; 95%CI -0.02, 0.88), and substantial between EOB-MRI and ECA-MRI (k 0.65; 95%CI 0.47, 0.82). ECA-MRI demonstrated the highest sensitivity (70%) and specificity (100%) when considering LR-5 as predictor of HCC.

CONCLUSIONS

Inter-modality agreement between CT, ECA-MRI, and EOB-MRI decreases in observations smaller than 20 mm. ECA-MRI has the provided higher sensitivity for the diagnosis of HCC.

Assessing the inter-observer and intra-observer reliability of radiographic measurements for size-specific dose estimates

BACKGROUND

Calculating size-specific dose estimates (SSDEs) requires measurement of the patient's anteroposterior (AP) and lateral thickness based on computed tomography (CT) images. However, these measurements can be subject to variation due to inter-observer and intra-observer differences. This study aimed to investigate the impact of these variations on the accuracy of the calculated SSDE.

METHODS

Four radiographers with 1-10 years of experience were invited to measure the AP and lateral thickness on 30 chest, abdomen, and pelvic CT images. The images were sourced from an internet-based database and anonymized for analysis. The observers were trained to perform the measurements using MicroDicom software and asked to repeat the measurements 1 week later. The study was approved by the institutional review board at Taibah University, and written informed consent was obtained from the observers. Statistical analyses were performed using Python libraries Pingouin (version 0.5.3), Seaborn (version 0.12.2), and Matplotlib (version 3.7.1).

RESULTS

The study revealed excellent inter-observer agreement for the calculated effective diameter and AP thickness measurements, with Intraclass correlation coefficients (ICC) values of 0.95 and 0.96, respectively. The agreement for lateral thickness measurements was lower, with an ICC value of 0.89. The second round of measurements yielded nearly the same levels of inter-observer agreement, with ICC values of 0.97 for the effective diameter, 1.0 for AP thickness, and 0.88 for lateral thickness. When the consistency of the observer was examined, excellent consistency was found for the calculated effective diameter, with ICC values ranging from 0.91 to 1.0 for all observers. This was observed despite the lower consistency in the lateral thickness measurements, which had ICC values ranging from 0.78 to 1.0.

CONCLUSIONS

The study's findings suggest that the measurements required for calculating SSDEs are robust to inter-observer and intra-observer differences. This is important for the clinical use of SSDEs to set diagnostic reference levels for CT scans.

Automated Detection of Steno-Occlusive Lesion on Time-of-Flight MR Angiography: An Observer Performance Study

BACKGROUND AND PURPOSE

Intracranial steno-occlusive lesions are responsible for acute ischemic stroke. However, the clinical benefits of artificial intelligence (AI)-based methods for detecting pathologic lesions in intracranial arteries have not been evaluated. We aimed to validate the clinical utility of an AI model for detecting steno-occlusive lesions in the intracranial arteries.

MATERIALS AND METHODS

Overall, 138 TOF-MRA images were collected from 2 institutions, which served as internal (n = 62) and external (n = 76) test sets, respectively. Each study was reviewed by 5 radiologists (2 neuroradiologists and 3 radiology residents) to compare the usage and nonusage of our proposed AI model for TOF-MRA interpretation. They identified the steno-occlusive lesions and recorded their reading time. Observer performance was assessed by using the area under the jackknife free-response receiver operating characteristic curve (AUFROC) and reading time for comparison.

RESULTS

The average AUFROC for the 5 radiologists demonstrated an improvement from 0.70 without AI to 0.76 with AI (P = .027). Notably, this improvement was most pronounced among the 3 radiology residents, whose performance metrics increased from 0.68 to 0.76 (P = .002). Despite an increased reading time by using AI, there was no significant change among the readings by radiology residents. Moreover, the use of AI resulted in improved interobserver agreement among the reviewers (the intraclass correlation coefficient increased from 0.734 to 0.752).

CONCLUSIONS

Our proposed AI model offers a supportive tool for radiologists, potentially enhancing the accuracy of detecting intracranial steno-occlusion lesions on TOF-MRA. Less experienced readers may benefit the most from this model.

Effect of Matrix Size and Acquisition Mode on Image Quality and Radiation Dose of Ultra-High-Resolution CT of the Temporal Bone: An Anatomical Study

Purpose: To compare image quality and radiation exposure between super- and ultra-high-resolution helical and super-high-resolution volumetric CT of the temporal bone. Methods: Six cadaveric temporal bone specimens were used to evaluate key temporal bone structures using the following CT reconstruction and acquisition modes: helical and single-volume acquisition modes in super-high resolution (0.25-mm slice thickness, 10242 matrix), and helical mode in ultra-high resolution (0.25-mm slice thickness, 20482 matrix). Two observers performed 5 previously described preoperative measurements, measured noise and signal-to-noise ratios for air, and noise for bone, and rated the visualization of 5 anatomical structures on a 4-point scale, for each reconstruction mode. Radiation dose exposure was recorded for each examination. Results: There was no significant difference between any of the quantitative or qualitative measurements in any of the reconstruction and acquisition modes. There was a slight increase in noise and a decrease in signal-to-noise ratio in the air using the single-volume mode (115 ± 13.1 HU and 8.37 ± 0.91, respectively) compared to the helicoidal super-high-resolution (92.4 ± 11.8 HU and 10.8 ± 1.26, respectively) and helicoidal ultra-high-resolution (91.1 ± 10.7 HU and 10.9 ± 1.39, respectively) modes (P < .002). The volumic CT dose index was 50.9 mGy with helical acquisition and 29.8 mGy with single-volume acquisition mode (P < .0001). Conclusion: The single-volume super-high-resolution acquisition mode allows a reduction in radiation dose exposure without compromising image quality compared to helical scanning, but with a slightly lower signal-to-noise ratio in air with the single-volume mode, while there was no difference in image quality between the helical super- and ultra-high-resolution modes.

Olfactory cleft stenosis and obstruction on paranasal sinus CT scan in pre-septo-rhinoplasty patients: normal variants or pathologic findings?

OBJECTIVE(S)

To determine the frequency of olfactory cleft (OC) stenosis and obstruction on paranasal sinus CT scans in pre-septorhinoplasty of patients who had septal deviation, septopyramidal deformation or nasal obstruction without other sinonasal conditions.

METHODS

This retrospective study included patients referred to our institution between December 2013 and December 2021 for septorhinoplasty due to nasal obstruction without other sinonasal or neurological conditions. All patients underwent preoperative paranasal sinus CT scan and olfactory testing. OC stenosis was quoted as none, partial, or total (less than 1/3 contact between nasal septum and ethmoid turbinates, 1/3-2/3, more than 2/3, respectively), as well as OC obstruction as none, partial, or complete (obstruction of less than 1/3 of OC, 1/3-2/3, more than 2/3, respectively). Radiologic evaluation was validated by near perfect interobserver agreement.

RESULTS

A total of 75 patients (32 women, 43 men) with a mean age of 44.2 ± 15.64 (23-74) years were included, of which 36 were normosmic and 39 hyposmic. OC stenosis was partial in 58.7% (n = 44) of the patients, absent in 28% (n = 21), and total in 13.3% (n = 10), without difference between normosmic and hyposmic patients (p = .66). OC obstruction was absent in 52% (n = 39) and partial in 46.7% (n = 35), without difference between normosmic and hyposmic patients (p = .51). Only one normosmic patient had complete OC obstruction.

CONCLUSION

OC partial stenosis and partial obstruction were frequent findings in pre-septorhinoplasty patients without respiratory mucosa disease and did not influence their olfactory status. Total stenosis and complete obstruction were rarer and require further investigation.

CLINICAL RELEVANCE STATEMENT

Isolated partial olfactory cleft stenosis and obstruction should be considered normal variants, whereas the impact of complete olfactory cleft stenosis and obstruction on patient's olfactory status remains to be determined.

KEY POINTS

• The incidence of olfactory cleft stenosis and obstruction in asymptomatic patients remains unknown, even though it is encountered in clinical practice. • Partial and total olfactory cleft stenosis occurred in 58.7% and 13.3% of the patients; partial obstruction occurred in half of the cases, but complete obstruction was extremely rare. • There are frequent findings of partial olfactory cleft obstruction and stenosis, but complete obstruction and total stenosis should be further investigated.

Comparing the Double-Echo Steady State with Water Excitation and Constructive Interference in Steady State Sequence Techniques for Identifying Extracranial Facial Nerve and Tumor Positions in Patients with Parotid Tumors

BACKGROUND AND PURPOSE

Reliable preoperative visualization of facial nerve morphology and understanding the spatial relationship between the facial nerve and tumors in the parotid gland can help clinicians perform safe and effective surgeries. Hence, this study aimed to compare the image quality of extracranial facial nerves obtained by using double-echo steady state with water excitation (DESS-WE) and CISS sequences and evaluate their diagnostic efficacy in the localization of parotid tumors.

MATERIALS AND METHODS

In total, 32 facial nerves of 16 healthy volunteers and 25 facial nerves of 25 patients with parotid tumors were included in this retrospective study. All participants underwent noncontrast-enhanced extracranial facial nerve MR imaging with DESS-WE and CISS with a 3T MR scanner equipped with a 64-channel head and neck coil. Image quality was subjectively evaluated by using a 5-point Likert scale by 2 radiologists. Inter- and intrarater agreements were assessed by using the Cohen κ coefficient. Receiver operating characteristic analysis was performed, and the diagnostic efficacies of DESS-WE and CISS images in localizing parotid tumors were calculated.

RESULTS

For healthy volunteers (11 men and 5 women; median age, 26 years), image quality scores for CISS were significantly higher than those for DESS-WE for the discrimination of the temporofacial and cervicofacial trunks (both, P < .001). In patients with parotid tumors (12 men and 13 women; median age, 58 years), CISS performed better than DESS-WE in terms of visualizing the spatial relationship of the facial nerve to the tumor and diagnostic confidence (both, P < .001). Regarding the localization of parotid tumors, CISS showed excellent performance, comparable to that of DESS-WE (area under the curve, 0.981 versus 0.942, P = .1489).

CONCLUSIONS

CISS achieved diagnostic performance comparable to DESS-WE in parotid tumor localization, with favorable image quality and more reliable morphologic visualization of the facial nerve.

Reliability of impedance spectroscopy versus digital radiograph and ICDAS-II in occlusal caries detection: a prospective clinical trial

The traditional methods in early caries detection had many limitations. So, this study aimed to evaluate the clinical performance of alternating current impedance spectroscopy ACIST in comparison with digital radiograph and ICDAS-II in detection of occlusal carious lesions. Occlusal surfaces of molar and premolar teeth from 40 adult participants were examined by two observers using three diagnostic methods: (1) international caries detection and assessment system (ICDAS-II) (2) digital radiograph (DR) and (3) Cariescan Pro device (ACIST). Agreement analysis and the difference in sensitivities and specificities were evaluated. The results showed an excellent agreement in the different groups. The difference from the visual tactile against ACIST scoring for enamel caries detection, was statistically significant (p = 0.012) and the agreement was moderate (k = 0.509). For dentinal caries the difference was not statistically significant (p > 0.05) and the agreement was similarly moderate (k < 0.6). The difference from the digital radiograph against ACIST scoring, for enamel caries, digital radiography had significantly higher sensitivity and specificity than ACIST (p < 0.001) while for dentinal caries detection and overall, ACIST had higher sensitivity and digital radiography had higher specificity and the difference was statistically significant (p < 0.001). Visual-tactile examination is a considered as feasible and valid technique for occlusal caries detection, digital radiography is superior to ACIST in diagnosing enamel caries, but it could underestimate the caries depth, ACIST is a reliable tool for detecting occlusal caries in dentin.

Reducing Manual Annotation Costs for Cell Segmentation by Upgrading Low-Quality Annotations

Deep-learning algorithms for cell segmentation typically require large data sets with high-quality annotations to be trained with. However, the annotation cost for obtaining such sets may prove to be prohibitively expensive. Our work aims to reduce the time necessary to create high-quality annotations of cell images by using a relatively small well-annotated data set for training a convolutional neural network to upgrade lower-quality annotations, produced at lower annotation costs. We investigate the performance of our solution when upgrading the annotation quality for labels affected by three types of annotation error: omission, inclusion, and bias. We observe that our method can upgrade annotations affected by high error levels from 0.3 to 0.9 Dice similarity with the ground-truth annotations. We also show that a relatively small well-annotated set enlarged with samples with upgraded annotations can be used to train better-performing cell segmentation networks compared to training only on the well-annotated set. Moreover, we present a use case where our solution can be successfully employed to increase the quality of the predictions of a segmentation network trained on just 10 annotated samples.

Comparison of a Whole-Brain Contrast-Enhanced 3D TSE T1WI versus Orbits Contrast-Enhanced 2D Coronal T1WI at 3T MRI for the Detection of Optic Nerve Enhancement in Patients with Acute Loss of Visual Acuity

BACKGROUND AND PURPOSE

MR imaging is the technique of choice for patients presenting with acute loss of visual acuity with no obvious ophthalmologic cause. The goal of our study was to compare orbits contrast-enhanced 2D coronal T1WI with a whole-brain contrast-enhanced 3D (WBCE-3D) TSE T1WI at 3T for the detection of optic nerve enhancement.

MATERIALS AND METHODS

This institutional review board-approved retrospective single-center study included patients presenting with acute loss of vision who underwent 3T MR imaging from November 2014 to February 2020. Two radiologists, blinded to all data, individually assessed the presence of enhancement of the optic nerve on orbits contrast-enhanced 2D T1WI and WBCE-3D T1WI separately and in random order. A McNemar test and a Cohen κ method were used for comparing the 2 MR imaging sequences.

RESULTS

One thousand twenty-three patients (638 women and 385 men; mean age, 42 [SD, 18.3] years) were included. There was a strong concordance between WBCE-3D T1WI and orbits contrast-enhanced 2D T1WI when detecting enhancement of the optic nerve: κ = 0.87 (95% CI, 0.84-0.90). WBCE-3D T1WI was significantly more likely to detect canalicular enhancement compared with orbits contrast-enhanced 2D T1WI: 178/1023 (17.4%) versus 138/1023 (13.5%) (P < .001) and 108/1023 (10.6%) versus 90/1023 (8.8%) (P = .04), respectively. The WBCE-3D T1WI sequence detected 27/1023 (3%) instances of optic disc enhancement versus 0/1023 (0%) on orbits contrast-enhanced 2D T1WI. There were significantly fewer severe artifacts on WBCE-3D T1WI compared with orbits contrast-enhanced 2D T1WI: 68/1023 (6.6%) versus 101/1023 (9.8%) (P < .001). The median reader-reported confidence was significantly higher with coronal T1WI compared with 3D TSE T1WI: 5 (95% CI, 4-5) versus 3 (95% CI, 1-4; P < .001).

CONCLUSIONS

Our study showed that there was a strong concordance between WBCE-3D T1WI and orbits contrast-enhanced 2D T1WI when detecting enhancement of the optic nerve in patients with acute loss of visual acuity with no obvious ophthalmologic cause. WBCE-3D T1WI demonstrated higher sensitivity and specificity in diagnosing optic neuritis, particularly in cases involving the canalicular segments.

4D flow cardiac MRI to assess pulmonary blood flow in patients with pulmonary arterial hypertension associated with congenital heart disease

PURPOSE

The purpose of this study was to evaluate the accuracy of four-dimensional flow cardiac magnetic resonance imaging (4D flow MRI) compared to right heart catheterization in measuring pulmonary flow (Qp), systemic flow (Qs) and pulmonary-to-systemic flow ratio (Qp/Qs) in patients with pulmonary arterial hypertension associated with congenital heart disease (PAH-CHD).

MATERIALS AND METHODS

The study was registered on Clinical-trial.gov (NCT03928002). Sixty-four patients with PAH-CHD who underwent 4D flow MRI were included. There were 16 men and 48 women with a mean age of 45.3 ± 13.7 (standard deviation [SD]) years (age range: 21-77 years). Fifty patients (50/64; 78%) presented with pre-tricuspid shunt. Qp (L/min), Qs (L/min) and Qp/Qs were measured invasively using direct Fick method during right heart catheterization and compared with measurements assessed by 4D flow MRI within a 24-48-hour window.

RESULTS

The average mean pulmonary artery pressure was 51 ± 17 (SD) mm Hg with median pulmonary vascular resistance of 8.8 Wood units (Q1, Q3: 5.3, 11.7). A strong linear correlation was found between Qp measurements obtained with 4D flow MRI and those obtained with the Fick method (r = 0.96; P < 0.001). Bland Altman analysis indicated a mean difference of 0.15 ± 0.48 (SD) L/min between Qp estimated by 4D flow MRI and by right heart catheterization. A strong correlation was found between Qs and Qp/Qs measured by 4D flow MRI and those obtained with the direct Fick method (r = 0.85 and r = 0.92; P < 0.001 for both).

CONCLUSION

Qp as measured by 4D flow MRI shows a strong correlation with measurements derived from the direct Fick method. Further investigation is needed to develop less complex and standardized methods for measuring essential PAH parameters, such as pulmonary arterial pressures and pulmonary vascular resistance.

Assessment of whole-body muscle MRI for the early diagnosis of Amyotrophic Lateral Sclerosis

OBJECTIVES

To evaluate muscle signal abnormalities on whole-body muscle MRI with T2 and diffusion-weighted imaging in early ALS stages.

METHODS

101 muscles were analyzed in newly diagnosed ALS patients and healthy controls on a whole-body MRI protocol including four-point T2-Dixon imaging and diffusion-weighted imaging (b0 and b800). Sensitivity and inter-observer agreement were assessed.

RESULTS

15 patients (mean age, 64 +/- 12 [SD], 9 men) who met the Awaji-Shima criteria for definite, probable or possible ALS and 9 healthy controls were assessed (mean age, 53 +/- 13 [SD], 2 men). 61 % of the muscles assessed in ALS patients (62/101) showed signal hyperintensities on T2-weighted imaging, mainly in the upper and lower extremities (legs, hands and feet). ALS patients had a significantly higher number of involved muscles compared to healthy controls (p = 0,006). Diffusion-weighted imaging allowed for the detection of additional involvement in 22 muscles, thus improving the sensitivity of whole-body MRI from 60 % (using T2-weighted imaging only) up to 80 % (with the combination of T2-weighted and diffusion-weighted imaging).

CONCLUSIONS

ALS patients exhibited significant muscle signal abnormalities on T2-weighted and diffusion-weighted imaging in early disease stages. Whole-body MRI could be used for pre-EMG mapping of muscle involvement in order to choose suitable targets, thus improving early diagnosis.

Bi-regional dynamic contrast-enhanced MRI for prediction of microvascular invasion in solitary BCLC stage A hepatocellular carcinoma

OBJECTIVES

To construct a combined model based on bi-regional quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), as well as clinical-radiological (CR) features for predicting microvascular invasion (MVI) in solitary Barcelona Clinic Liver Cancer (BCLC) stage A hepatocellular carcinoma (HCC), and to assess its ability for stratifying the risk of recurrence after hepatectomy.

METHODS

Patients with solitary BCLC stage A HCC were prospective collected and randomly divided into training and validation sets. DCE perfusion parameters were obtained both in intra-tumoral region (ITR) and peritumoral region (PTR). Combined DCE perfusion parameters (CDCE) were constructed to predict MVI. The combined model incorporating CDCE and CR features was developed and evaluated. Kaplan-Meier method was used to investigate the prognostic significance of the model and the survival benefits of different hepatectomy approaches.

RESULTS

A total of 133 patients were included. Total blood flow in ITR and arterial fraction in PTR exhibited the best predictive performance for MVI with areas under the curve (AUCs) of 0.790 and 0.792, respectively. CDCE achieved AUCs of 0.868 (training set) and 0.857 (validation set). A combined model integrated with the α-fetoprotein, corona enhancement, two-trait predictor of venous invasion, and CDCE could improve the discrimination ability to AUCs of 0.966 (training set) and 0.937 (validation set). The combined model could stratify the prognosis of HCC patients. Anatomical resection was associated with a better prognosis in the high-risk group (p < 0.05).

CONCLUSION

The combined model integrating DCE perfusion parameters and CR features could be used for MVI prediction in HCC patients and assist clinical decision-making.

CRITICAL RELEVANCE STATEMENT

The combined model incorporating bi-regional DCE-MRI perfusion parameters and CR features predicted MVI preoperatively, which could stratify the risk of recurrence and aid in optimizing treatment strategies.

KEY POINTS

Microvascular invasion (MVI) is a significant predictor of prognosis for hepatocellular carcinoma (HCC). Quantitative DCE-MRI could predict MVI in solitary BCLC stage A HCC; the combined model improved performance. The combined model could help stratify the risk of recurrence and aid treatment planning.

Automated weight-bearing foot measurements using an artificial intelligence-based software

OBJECTIVE

To assess the accuracy of an artificial intelligence (AI) software (BoneMetrics, Gleamer) in performing automated measurements on weight-bearing forefoot and lateral foot radiographs.

METHODS

Consecutive forefoot and lateral foot radiographs were retrospectively collected from three imaging institutions. Two senior musculoskeletal radiologists independently annotated key points to measure the hallux valgus, first-second metatarsal, and first-fifth metatarsal angles on forefoot radiographs and the talus-first metatarsal, medial arch, and calcaneus inclination angles on lateral foot radiographs. The ground truth was defined as the mean of their measurements. Statistical analysis included mean absolute error (MAE), bias assessed with Bland-Altman analysis between the ground truth and AI prediction, and intraclass coefficient (ICC) between the manual ratings.

RESULTS

Eighty forefoot radiographs were included (53 ± 17 years, 50 women), and 26 were excluded. Ninety-seven lateral foot radiographs were included (51 ± 20 years, 46 women), and 21 were excluded. MAE for the hallux valgus, first-second metatarsal, and first-fifth metatarsal angles on forefoot radiographs were respectively 1.2° (95% CI [1; 1.4], bias =  - 0.04°, ICC = 0.98), 0.7° (95% CI [0.6; 0.9], bias =  - 0.19°, ICC = 0.91) and 0.9° (95% CI [0.7; 1.1], bias = 0.44°, ICC = 0.96). MAE for the talus-first, medial arch, and calcaneal inclination angles on the lateral foot radiographs were respectively 3.9° (95% CI [3.4; 4.5], bias = 0.61° ICC = 0.88), 1.5° (95% CI [1.2; 1.8], bias =  - 0.18°, ICC = 0.95) and 1° (95% CI [0.8; 1.2], bias = 0.74°, ICC = 0.99). Bias and MAE between the ground truth and the AI prediction were low across all measurements. ICC between the two manual ratings was excellent, except for the talus-first metatarsal angle.

CONCLUSION

AI demonstrated potential for accurate and automated measurements on weight-bearing forefoot and lateral foot radiographs.

Temporal bone remodeling is an indicator of transverse sinus stenosis on computed tomography

PURPOSE

The purpose of this study was to identify potential association between transverse sinus stenosis (TSS) and temporal bone thinning downstream of TSS on computed tomography (CT).

MATERIALS AND METHODS

Clinical and radiological data of patients with venous pulsatile tinnitus due to TSS (TSS group) and treated with stenting from 2019 to 2022 were retrospectively collected. An age-matched control group of patients with venous or neutral pulsatile tinnitus (control group) was built. CT measurements of temporal bone thickness were performed at the level of transverse-sigmoid sinus junction (E1) and the occipitomastoid suture (E2). E1; E2 and E1/E2 ratios obtained in TSS and control groups were compared.

RESULTS

A total of 122 patients with venous pulsatile tinnitus were included. There were 56 patients with TSS (TSS group; 56 women; mean age, 35.5 ± 11.3 [standard deviation] years) and 66 patients without TSS (control group; 54 women; mean age, 37.7 ± 10.5 [standard deviation] years). E1 measurements and E1/E2 ratios on the symptomatic and dominant sides were significantly lower in the TSS group by comparison with the contralateral side of the same group (P < 0.05) and the ipsilateral side of the control group (P < 0.05). There were no differences in median E2 values between the TSS group (6.8 mm; range: 3.5-10.8 mm) and the control group (7.1 mm; range: 2.9-11.2 mm) (P = 0.098). E1 = 0 mm was found only in the TSS group. At receiver operating characteristic (ROC) analysis, an E1/E2 ratio threshold of 0.562 maximized the ability to predict presence of TSS. An E1/E2 ratio < 0.562 was predictive of symptomatic TSS with an accuracy of 74% (95% confidence interval: 65-82%). The AUC for the diagnosis of TSS was 0.807 (95% CI: 0.729-0.885).

CONCLUSION

Temporal bone thickness is significantly reduced downstream of the stenosis on the pulsatile tinnitus side and may be a good indicator of symptomatic TSS.

Computed tomography-based device-sizing in Amplatzer Amulet left atrial appendage occlusion

BACKGROUND

Amplatzer Amulet is a frequently used device for left atrial appendage occlusion (LAAO). The current sizing protocol is based on the maximum diameter of the left atrial appendage (LAA) landing zone. However, mean, perimeter-, or area-derived diameter might be more accurate measures for device sizing.

METHODS

Retrospective analysis of 150 consecutive patients undergoing LAAO is guided by pre-procedural cardiac CT. A total of 117 patients were included; 7 were excluded due to renal failure and 26 due to closure with the sandwich technique. The maximum, mean, area-, and perimeter-derived diameters of the landing zone were derived from pre-procedural cardiac CT scans, and their accuracy to predict the implanted device size was investigated. The predicted device size was determined based on the currently recommended sizing algorithm. Peri-device leak (PDL) was assessed (grade 1-3) along with the underlying mechanism.

RESULTS

Device-sizing accuracy was superior for mean, area-, and perimeter derived diameters compared with the maximal diameter, especially for eccentric landing zones. Mean difference between predicted and actually implanted device size was 0.08 mm (± 2.77), 0.30 mm (± 2.40), - 0.39 mm (± 2.43), and - 2.55 mm (± 2.57) across mean, area-derived, perimeter-derived, and maximal diameter, respectively. Grade 3 peri-device leak was seen in 8.5% of implants without a significant association to the eccentricity of the landing zone. The leading mechanism for PDL was device malalignment.

CONCLUSION

Our results indicate mean, area-, and perimeter-derived diameters of the device landing zone to perform similar and superior in device-sizing accuracy compared with the maximum diameter.

Dose optimization in newborn abdominal radiography: Assessing the added value of additional filtration on radiation dose and image quality using an anthropomorphic phantom

Background

Abdominal radiographs remain useful in newborns. Given the high radiation sensitivity of this population, it is necessary to optimize acquisition techniques to minimize radiation exposure.

Objective

Evaluate the effects of three additional filtrations on radiation dose and image quality in abdominal X-rays of newborns using an anthropomorphic phantom.

Material and method

Abdominal radiographs of an anthropomorphic newborn phantom were performed using acquisition parameters ranging from 55 to 70 kV and from 0.4 to 2.5 mAs, without and with three different additional filtrations: 0.1 mm copper (Cu) + 1 mm aluminum (Al), 0.2 mm copper + 1 mm aluminum, and 2 mm aluminum. For each X-ray the dose area product (DAP) was measured, the signal-to-noise ratio (SNR) was calculated, and image quality (IQ) was evaluated by two blinded radiologists using the absolute visual grading analysis (VGA) method.

Results

Adding an additional filtration resulted in a significant reduction in DAP, with a decrease of 42% using 2 mm Al filtration, 65% with 0.1 mm Cu + 1 mm Al filtration, and 78% with 0.2 mm Cu + 1 mm Al filtration (p < 0.01). The addition of 2 mm aluminum filtration does not significantly decrease the SNR (p = 0.31), CNR (p = 0.52) or the IQ (p = 0.12 and 0.401 for reader 1 and 2, respectively). However, adding copper-containing filtration leads to a significant decrease in, SNR, CNR and IQ.

Conclusion

Adding a 2 mm Al additional filtration for abdominal radiographs in newborns can significantly reduce the radiation dose without causing a significant decrease in image quality.

Prostate Magnetic Resonance Imaging Using the Prostate Imaging for Recurrence Reporting (PI-RR) Scoring System to Detect Recurrent Prostate Cancer: A Systematic Review and Meta-analysis

BACKGROUND AND OBJECTIVE

Prostate Imaging for Recurrence Reporting (PI-RR) was introduced in 2021 to standardize the interpretation and reporting of multiparametric magnetic resonance imaging (MRI) for prostate cancer following whole-gland treatment. The system scores image on a scale from 1 to 5 and has shown promising results in single-center studies. The aim of our systematic review and meta-analysis was to assess the diagnostic performance of the PI-RR system in predicting the likelihood of local recurrence after whole-gland treatment.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for diagnostic test accuracy were followed. Relevant databases were searched up to December 2023. Primary studies met the eligibility criteria if they reported MRI diagnostic performance in prostate cancer recurrence using PI-RR. Diagnostic performance for MRI was assessed using two different cutoff points (≥3 or ≥4 for positivity according to the PI-RR system). A meta-analysis with a random-effects model was used to estimate pooled sensitivity and specificity values.

KEY FINDINGS AND LIMITATIONS

Sixteen articles were identified for full-text reading, of which six were considered eligible, involving a total of 467 patients. Using a cutoff of PI-RR ≥3 (4 studies) for recurrent disease, the sensitivity was 77.8% (95% confidence interval [CI] 69.9-84.1%) and the specificity was 80.2% (95% CI 58.2-92.2%). Using a cutoff of PI-RR ≥4 (4 studies), the sensitivity was 61.9% (95% CI 35.6-82.7%) and the specificity was 86.6% (95% CI 75.1-93.3%). Overall, the inter-rater agreement varied from fair to excellent.

CONCLUSIONS AND CLINICAL IMPLICATIONS

PI-RR is accurate in detecting local recurrence after whole-gland treatment for prostate cancer and shows fair-to-good to excellent inter-reader agreement. Overall, a PI-RR cutoff of ≥3 showed high sensitivity and specificity.

PATIENT SUMMARY

We reviewed studies that reported on how good MRI scans using a scoring system called PI-RR were in detecting recurrence of prostate cancer. We found that this system shows good performance, with fair to excellent agreement between different radiologists.

Improving assessment of lesions in longitudinal CT scans: a bi-institutional reader study on an AI-assisted registration and volumetric segmentation workflow

PURPOSE

AI-assisted techniques for lesion registration and segmentation have the potential to make CT-based tumor follow-up assessment faster and less reader-dependent. However, empirical evidence on the advantages of AI-assisted volumetric segmentation for lymph node and soft tissue metastases in follow-up CT scans is lacking. The aim of this study was to assess the efficiency, quality, and inter-reader variability of an AI-assisted workflow for volumetric segmentation of lymph node and soft tissue metastases in follow-up CT scans. Three hypotheses were tested: (H1) Assessment time for follow-up lesion segmentation is reduced using an AI-assisted workflow. (H2) The quality of the AI-assisted segmentation is non-inferior to the quality of fully manual segmentation. (H3) The inter-reader variability of the resulting segmentations is reduced with AI assistance.

MATERIALS AND METHODS

The study retrospectively analyzed 126 lymph nodes and 135 soft tissue metastases from 55 patients with stage IV melanoma. Three radiologists from two institutions performed both AI-assisted and manual segmentation, and the results were statistically analyzed and compared to a manual segmentation reference standard.

RESULTS

AI-assisted segmentation reduced user interaction time significantly by 33% (222 s vs. 336 s), achieved similar Dice scores (0.80-0.84 vs. 0.81-0.82) and decreased inter-reader variability (median Dice 0.85-1.0 vs. 0.80-0.82; ICC 0.84 vs. 0.80), compared to manual segmentation.

CONCLUSION

The findings of this study support the use of AI-assisted registration and volumetric segmentation for lymph node and soft tissue metastases in follow-up CT scans. The AI-assisted workflow achieved significant time savings, similar segmentation quality, and reduced inter-reader variability compared to manual segmentation.

Thin-slice 2D MR Imaging of the Shoulder Joint Using Denoising Deep Learning Reconstruction Provides Higher Image Quality Than 3D MR Imaging

PURPOSE

This study was conducted to evaluate whether thin-slice 2D fat-saturated proton density-weighted images of the shoulder joint in three imaging planes combined with parallel imaging, partial Fourier technique, and denoising approach with deep learning-based reconstruction (dDLR) are more useful than 3D fat-saturated proton density multi-planar voxel images.

METHODS

Eighteen patients who underwent MRI of the shoulder joint at 3T were enrolled. The denoising effect of dDLR in 2D was evaluated using coefficient of variation (CV). Qualitative evaluation of anatomical structures, noise, and artifacts in 2D after dDLR and 3D was performed by two radiologists using a five-point Likert scale. All were analyzed statistically. Gwet's agreement coefficients were also calculated.

RESULTS

The CV of 2D after dDLR was significantly lower than that before dDLR (P < 0.05). Both radiologists rated 2D higher than 3D for all anatomical structures and noise (P < 0.05), except for artifacts. Both Gwet's agreement coefficients of anatomical structures, noise, and artifacts in 2D and 3D produced nearly perfect agreement between the two radiologists. The evaluation of 2D tended to be more reproducible than 3D.

CONCLUSION

2D with parallel imaging, partial Fourier technique, and dDLR was proved to be superior to 3D for depicting shoulder joint structures with lower noise.

Combination of clinical and spectral-CT iodine concentration for predicting liver metastasis in gastric cancer: a preliminary study

PURPOSE

This study aimed to determine the diagnostic efficacy of various indicators and models for the prediction of gastric cancer with liver metastasis.

METHODS

Clinical and spectral computed tomography (CT) data from 80 patients with gastric adenocarcinoma who underwent surgical resection were retrospectively analyzed. Patients were divided into metastatic and non-metastatic groups based on whether or not to occur liver metastasis, and the region of interest (ROI) was measured manually on each phase iodine map at the largest level of the tumor. Iodine concentration (IC), normalized iodine concentration (nIC), and clinical data of the primary gastric lesions were analyzed. Logistic regression analysis was used to construct the clinical indicator (CI) and clinical indicator-spectral CT iodine concentration (CI-Spectral CT-IC) Models, which contained all of the parameters with statistically significant differences between the groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the accuracy of the models.

RESULTS

The metastatic group showed significantly higher levels of Cancer antigen125 (CA125), carcinoembryonic antigen (CEA), IC, and nIC in the arterial phase, venous phase, and delayed phase than the non-metastatic group (all p < 0.05). Normalized iodine concentration Venous Phase (nICVP) exhibited a favorable performance among all IC and nIC parameters for forecasting gastric cancer with liver metastasis (area under the curve (AUC), 0.846). The combination model of clinical data with significant differences and nICVP showed the best diagnostic accuracy for predicting liver metastasis from gastric cancer, with an AUC of 0.897.

CONCLUSION

nICVP showed the best diagnostic efficacy for predicting gastric cancer with liver metastasis. Clinical Indicators-normalized ICVP model can improve the prediction accuracy for this condition.

Radiation dose reduction and image quality improvement with ultra-high resolution temporal bone CT using deep learning-based reconstruction: An anatomical study

PURPOSE

The purpose of this study was to evaluate the achievable radiation dose reduction of an ultra-high resolution computed tomography (UHR-CT) scanner using deep learning reconstruction (DLR) while maintaining temporal bone image quality equal to or better than high-resolution CT (HR-CT).

MATERIALS AND METHODS

UHR-CT acquisitions were performed with variable tube voltages and currents at eight different dose levels (volumic CT dose index [CTDIvol] range: 4.6-79 mGy), 10242 matrix, and 0.25 mm slice thickness and reconstructed using DLR and hybrid iterative reconstruction (HIR) algorithms. HR-CT images were acquired using a standard protocol (120 kV/220 mAs; CTDI vol, 54.2 mGy, 5122 matrix, and 0.5 mm slice thickness). Two radiologists rated the image quality of seven structures using a five point confidence scale on six cadaveric temporal bone CTs. A global image quality score was obtained for each CT protocol by summing the image quality scores of all structures.

RESULTS

With DLR, UHR-CT at 120 kV/220 mAs (CTDIvol, 50.9 mGy) and 140 kV/220 mAs (CTDIvol, 79 mGy) received the highest global image quality scores (4.88 ± 0.32 [standard deviation (SD)] [range: 4-5] and 4.85 ± 0.35 [range: 4-5], respectively; P = 0.31), while HR-CT at 120 kV/220 mAs and UHR-CT at 120 kV/20 mAs received the lowest (i.e., 3.14 ± 0.75 [SD] [range: 2-5] and 2.97 ± 0.86 [SD] [range: 1-5], respectively; P = 0.14). All the DLR protocols had better image quality scores than HR-CT with HIR.

CONCLUSION

UHR-CT with DLR can be performed with up to a tenfold reduction in radiation dose compared to HR-CT with HIR while maintaining or improving image quality.

The impacts of venous outflow profiles on outcomes among large vessel occlusion patients receiving endovascular treatment in the late window

OBJECTIVES

To investigate the association between venous outflow (VO) profiles and outcomes among acute ischemic stroke caused by anterior circulation large vessel occlusion (AIS-LVO) patients who had undergone endovascular treatment (EVT) in the late window of 6-24 h from stroke onset.

METHODS

This was a post-hoc analysis of our preceding RESCUE-BT trial, with findings validated in an external cohort. Baseline computed tomographic angiography (CTA) was performed to assess VO using the Cortical Vein Opacification Score (COVES). The primary clinical outcome was functional independence at 90 days (modified Rankin Scale score of 0-2). The adjusted odd ratio (aOR) and confidence interval (CI) were obtained from multivariable logistic regressions.

RESULTS

A total of 440 patients were included in the present study. After identifying the cutoff of COVES by marginal effects approach, enrolled patients were divided into the favorable VO group (COVES 4-6) and the poor VO (COVES 0-3) group. Multivariable logistic regression analysis showed that favorable VO (aOR 2.25; 95% CI 1.31-3.86; p = 0.003) was associated with functional independence. Similar results were detected in the external validation cohort. Among those with poor arterial collateralization, favorable VO was still an independent predictor of functional independence (aOR 2.09; 95% CI 1.06-4.10; p = 0.032).

CONCLUSION

The robust VO profile indicated by COVES 4-6 could promote the frequency of functional independence among AIS-LVO patients receiving EVT in the late window, and the prognostic value of VO was independent of the arterial collateral status.

CLINICAL RELEVANCE STATEMENT

The robust venous outflow profile was a valid predictor for functional independence among AIS-LVO patients receiving EVT in the late window (6-24 h) and the predictive role of venous outflow did not rely on the status of arterial collateral circulation.

Patellar osteochondritis dissecans: maturation-dependent patellofemoral joint characteristics

BACKGROUND

The likelihood of healing of osteochondritis dissecans decreases with skeletal maturity and there are theories that abnormal biomechanical forces contribute to the development and progression of these lesions.

OBJECTIVE

To characterize, according to regional skeletal maturity, the morphology and alignment indices of the patellofemoral joint on MRI in patients with patellar osteochondritis dissecans.

MATERIALS AND METHODS

MRI examinations of patients with patellar osteochondritis dissecans obtained between January 2008 and May 2023 were retrospectively reviewed to determine regional skeletal maturity, osteochondritis dissecans lesion size and location, patellar and trochlear morphology (Wiberg/Dejour classifications), and to calculate trochlear sulcus angles, trochlear depth index, lateral trochlear inclination, Insall-Salvati index, Caton-Deschamps index, patellar tendon-lateral trochlear ridge, and tibial tubercle-trochlear groove distances. Values were compared between skeletally immature and mature groups.

RESULTS

Sixty-eight children (22 girls, 46 boys, age: 14.0 ± 1.7 years) yielded 74 knees with patellar osteochondritis dissecans lesions, 14 (19%) of which were skeletally mature. The most common anatomic location was over the central patella [median ridge (34/74 - 46%) on the axial images and over the middle third (45/74 - 61%) on the sagittal images]. Overall, mean trochlear sulcus angle (high, 151 ± 11°), trochlear depth index (low, 2.8 ± 1.4 mm), and Insall-Salvati index (borderline, 1.3 ± 0.1) were abnormal for the entire sample. Skeletally mature knees were significantly more likely to have higher (more dysplastic) Dejour types when compared to skeletally immature knees (p < 0.01). Knees in the mature group, compared to immature, had significantly more abnormal mean lateral trochlear inclination (15 ± 8° vs. 19 ± 6°, p = 0.03) and patellar tendon-lateral trochlear ridge distance (5.55 ± 4.31 mm vs. 2.89 ± 4.69 mm, p = 0.04). Half of the knees had ≥ 4 abnormal features that predispose to patellofemoral maltracking; mature knees were significantly (p = 0.02) more likely to have a higher number of abnormal features (> 6 features, 7/14, 50.0%) versus immature knees (0-3 features, 33/60, 55.0%).

CONCLUSION

In children with patellar osteochondritis dissecans, abnormal patellofemoral morphology and alignment indices were common in all patients and more severe in mature knees.

Deep Learning in Breast Cancer Imaging: State of the Art and Recent Advancements in Early 2024

The rapid advancement of artificial intelligence (AI) has significantly impacted various aspects of healthcare, particularly in the medical imaging field. This review focuses on recent developments in the application of deep learning (DL) techniques to breast cancer imaging. DL models, a subset of AI algorithms inspired by human brain architecture, have demonstrated remarkable success in analyzing complex medical images, enhancing diagnostic precision, and streamlining workflows. DL models have been applied to breast cancer diagnosis via mammography, ultrasonography, and magnetic resonance imaging. Furthermore, DL-based radiomic approaches may play a role in breast cancer risk assessment, prognosis prediction, and therapeutic response monitoring. Nevertheless, several challenges have limited the widespread adoption of AI techniques in clinical practice, emphasizing the importance of rigorous validation, interpretability, and technical considerations when implementing DL solutions. By examining fundamental concepts in DL techniques applied to medical imaging and synthesizing the latest advancements and trends, this narrative review aims to provide valuable and up-to-date insights for radiologists seeking to harness the power of AI in breast cancer care.

Ultra-high-resolution CT of the temporal bone: The end of stapes prosthesis dimensional error and correlation with patient symptoms

PURPOSE

To describe the reliability of ultra-high-resolution computed tomography (UHR-CT) in the measurement of titanium stapes prostheses using manufacturer data as a reference.

MATERIALS AND METHODS

This retrospective study included patients treated by stapedectomy with titanium prostheses who underwent UHR-CT between January 2020 and October 2023. Images were acquired using an ultra-high-resolution mode (slice thickness: 0.25 mm; matrix, 1024 × 1024). Two radiologists independently evaluated the length, diameter, and intra-vestibular protrusion of the prosthesis. Post-operative air-bone gaps (ABGs) were recorded.

RESULTS

Fourteen patients were enrolled (mean age, 44.3 ± 13.8 [SD] years, 9 females), resulting in 16 temporal bone UHR-CTs. The exact length was obtained in 81.3 % (n = 13/16) and underestimated by 0.1 to 0.3 mm in the remaining 18.7 % (n = 3/16) CT scans for both readers (mean misestimation: -0.02 ± 0.06 [SD] mm, overall underestimation of 0.43 %). The exact diameter was reported in 75 % (n = 12/16) and 87.5 % (n = 14/16) of the CT scans for readers 1 and 2, respectively, and was off by 0.1 mm in all discrepancies (mean misestimation: 0.01 ± 0.04 [SD] mm, overall overestimation of 2.43 %). Intravestibular prosthesis protrusion was of 0.5 ± 0.43 [SD] mm (range: 0-1) and 0.49 ± 0.44 [SD] mm (range: 0-1.1) for readers 1 and 2, respectively, and did not correlate with ABGs (r = 0.25 and 0.22; P = 0.39 and 0.47 for readers 1 and 2, respectively). Intra and interobserver agreements were excellent.

CONCLUSION

UHR-CT provides 99.6 % and 97.6 % accuracy for prosthesis length and diameter measurements, respectively.

Reduced Intravenous Contrast Dose Portal Venous Phase Photon-Counting Computed Tomography Compared With Conventional Energy-Integrating Detector Portal Venous Phase Computed Tomography

OBJECTIVE

The aim of this study was to compare portal venous phase photon-counting CT (PCCT) using 20 cc less than weight-based contrast dosing with energy-integrating detector CT (EID-CT) using weight-based dosing by quantitative and qualitative analysis.

METHODS

Fifty adult patients who underwent a reduced intravenous contrast dose portal venous phase PCCT from May 1, 2023, to August 10, 2023, and a prior portal-venous EID-CT with weight-based contrast dosing were retrospectively identified. Hounsfield units (HU) and noise (SD of HU) were obtained from region-of-interest measurements on 70-keV PCCT and EID-CT in 4 hepatic segments, the main and right portal vein, and both paraspinal muscles. Signal-to-noise and contrast-to-noise ratios were computed. Three abdominal radiologists qualitatively assessed overall image quality, hepatic enhancement, and confidence for metastasis identification on 5-point Likert scales. Readers also recorded the presence/absence of hepatic metastases. Quantitative variables were compared with paired t tests, and multiple comparisons were accounted for with a Bonferroni-adjusted α level of .0016. Ordinal logistic regression was used to evaluate qualitative assessments. Interreader agreement for hepatic metastases was calculated using Fleiss' κ.

RESULTS

Fifty patients (32 women; mean [SD] age, 64 [13] years) were included. There was no significant difference in hepatic HU, portal vein HU, noise, and signal-to-noise or contrast-to-noise ratio between reduced contrast dose portal venous phase PCCT versus EID-CT (all Ps > 0.0016). Image quality, degree of hepatic enhancement, and confidence for metastasis identification were not different for reduced dose PCCT 70-keV images and EID-CT (P = 0.06-0.69). κ Value for metastasis identification was 0.86 (95% confidence interval, 0.70-1.00) with PCCT and 0.78 (95% confidence interval, 0.59-0.98) with EID-CT.

CONCLUSION

Reduced intravenous contrast portal venous phase PCCT 70-keV images had similar attenuation and image quality as EID-CT with weight-based dosing. Metastases were identified with near-perfect agreement in reduced dose PCCT 70-keV images.

Differentiation between adrenocortical carcinoma and lipid-poor adrenal adenoma using a multiparametric MRI-based diagnostic algorithm

PURPOSE

The purpose of this study was to evaluate the capabilities of multiparametric magnetic resonance imaging (MRI) in differentiating between lipid-poor adrenal adenoma (LPAA) and adrenocortical carcinoma (ACC).

MATERIALS AND METHODS

Patients of two centers who underwent surgical resection of LPAA or ACC after multiparametric MRI were retrospectively included. A training cohort was used to build a diagnostic algorithm obtained through recursive partitioning based on multiparametric MRI variables, including apparent diffusion coefficient and chemical shift signal ratio (i.e., tumor signal intensity index). The diagnostic performances of the multiparametric MRI-based algorithm were evaluated using a validation cohort, alone first and then in association with adrenal tumor size using a cut-off of 4 cm. Performances of the diagnostic algorithm for the diagnosis of ACC vs. LPAA were calculated using pathology as the reference standard.

RESULTS

Fifty-four patients (27 with LPAA and 27 with ACC; 37 women; mean age, 48.5 ± 13.3 [standard deviation (SD)] years) were used as the training cohort and 61 patients (24 with LPAA and 37 with ACC; 47 women; mean age, 49 ± 11.7 [SD] years) were used as the validation cohort. In the validation cohort, the diagnostic algorithm yielded best accuracy for the diagnosis of ACC vs. LPAA (75%; 46/61; 95% CI: 55-88) when used without lesion size. Best sensitivity was obtained with the association of the diagnostic algorithm with tumor size (96%; 23/24; 95% CI: 80-99). Best specificity was obtained with the diagnostic algorithm used alone (76%; 28/37; 95% CI: 60-87).

CONCLUSION

A multiparametric MRI-based diagnostic algorithm that includes apparent diffusion coefficient and tumor signal intensity index helps discriminate between ACC and LPAA with high degrees of specificity and accuracy. The association of the multiparametric MRI-based diagnostic algorithm with adrenal lesion size helps maximize the sensitivity of multiparametric MRI for the diagnosis of ACC.

Association of Radiographic Soft Tissue Thickness With Revision Total Ankle Arthroplasty Following Primary Total Ankle Arthroplasty: A Minimum of 5-year Follow-up

Background

The incidence of primary total ankle arthroplasty (TAA) is rising, with a corresponding increase in revision surgeries. Despite this, research on risk factors for revision TAA following primary TAA remains limited. Radiographic soft tissue thickness has been explored as a potential predictor for outcomes in hip, knee, and shoulder arthroplasty, but its role in TAA has not been assessed. This study aimed to assess the predictive value of radiographic soft tissue thickness for identifying patients at risk of requiring revision surgery following primary TAA.

Methods

A retrospective study was conducted on 323 patients who underwent primary TAA between 2003 and 2019. Radiographic measurements of soft tissue thickness were obtained from preoperative radiographs. Two novel radiographic measures of soft tissue thickness were developed and assessed (tibial tissue thickness and talus tissue thickness). Clinical variables including age, gender, body mass index (BMI), American Society of Anesthesiologists (ASA) classification, diabetes, smoking status, primary diagnosis, and implant type were recorded. Logistic regression analysis was used to assess the predictive value of soft tissue thickness and BMI for revision TAA.

Results

The rate of revision surgery was 4.3% (14 of 323 patients). Patients requiring revision had significantly greater tibial tissue (3.54 vs 2.48 cm; P = .02) and talus tissue (2.79 vs 2.42 cm; P = .02) thickness compared with those not requiring revision. Both the tibial tissue thickness (odds ratio 1.16 [1.12-1.20]; P < .01) and the talus tissue thickness (odds ratio: 1.10 [1.05-1.15]; P < .01) measurements were significant predictors of revision TAA in multivariable logistic regression models. However, BMI was not a significant predictor of revision TAA. The two metrics demonstrated excellent interrater reliability.

Conclusion

Greater soft tissue thickness was a better predictor of revision TAA compared with BMI. These findings suggest that radiographic soft tissue thickness may be a valuable tool for assessing the risk of the need for revision TAA following primary TAA. Further research is needed to validate and explore the potential impact on clinical practice.

Level of Evidence

Level III, comparative study.

Correlation of CT parameters and PD-L1 expression status in gastric cancer

OBJECTIVE

We aimed to explore the correlation between routine computed tomography (CT) imaging features and programmed cell death ligand-1(PD-L1) expression status in gastric cancer and evaluate the predictive value of imaging parameters for this immunotherapy biomarker.

MATERIALS AND METHODS

Patients with gastric adenocarcinoma who underwent abdominal CT three-stage enhanced scan and PD-L1 immunohistochemical testing before treatment were retrospectively examined. All diagnoses were confirmed through pathology. According to the expression status of PD-L1, they were divided into the positive (CPS ≥ 5) or negative group (CPS < 5). Baseline CT imaging features were collected. Diagnostic performances of the different variables were evaluated using receiver operating characteristic (ROC) curve.

RESULTS

In total, 67 patients (17 women and 50 men; mean age: 59.55 ± 10.22 years) with gastric adenocarcinoma were included in the study. The overall stages, probability of maximum lymph node short diameter > 1 cm and peak of lesion enhancement occurring in the arterial phase were statistically significant between the two groups (p < 0.05). Moreover, the arterial enhancement fraction (AEF) was significantly higher in the positive group than that in the negative group (p < 0.05), and ROC curve analysis showed that the AEF exhibited a high evaluation efficacy (area under the curve [AUC] = 0.724 [95% confidence interval (CI): 0.602-0.826]). The combined parameters had the best diagnostic efficacy (AUC = 0.825 [95%CI: 0.716-0.933]), sensitivity (75.00%), and specificity (81.40%).

CONCLUSIONS

These findings confirm a correlation between CT imaging features and PD-L1 expression status in gastric cancer, and AEF may help evaluate high PD-L1 expression and select patients suitable for immunotherapy.

Nomogram combining pre-operative clinical characteristics and spectral CT parameters for predicting the WHO/ISUP pathological grading in clear cell renal cell carcinoma

PURPOSE

To develop a novel clinical-spectral-computed tomography (CT) nomogram incorporating clinical characteristics and spectral CT parameters for the preoperative prediction of the WHO/ISUP pathological grade in clear cell renal cell carcinoma (ccRCC).

METHODS

Seventy-three ccRCC patients who underwent spectral CT were included in this retrospective analysis from December 2020 to June 2023. The subjects were pathologically divided into low- and high-grade groups (WHO/ISUP 1/2, n = 52 and WHO/ISUP 3/4, n = 21, respectively). Information on clinical characteristics, conventional CT imaging features, and spectral CT parameters was collected. Multivariate logistic regression analyses were conducted to create a nomogram combing clinical data and image data for preoperatively predicting the pathological grade of ccRCC, and the area under the curve (AUC) was utilized to assess the predictive performance of the model.

RESULTS

Multivariate logistic regression analyses revealed that age, systemic immune-inflammation index (SII), and the slope of the spectrum curve in the cortex phase (CP-K) were independent predictors for predicting high-grade ccRCC. The clinical-spectral-CT model exhibited high evaluation efficacy, with an AUC of 0.933 (95% confidence interval [CI]: 0.878-0.998; sensitivity: 0.810; specificity: 0.923). The calibration curve revealed that the predicted probability of the clinical-spectral-CT nomogram could better fit the actual probability, with high calibration. The Hosmer-Lemeshow test showed that the model had a good fitness (χ2 = 5.574, p = 0.695).

CONCLUSION

The clinical-spectral-CT nomogram has the potential to predict WHO/ISUP grading of ccRCC preoperatively.

Diagnostic Performance of Dynamic Contrast-Enhanced 3T MR Imaging for Characterization of Orbital Lesions: Validation in a Large Prospective Study

BACKGROUND AND PURPOSE

Orbital lesions are rare but serious. Their characterization remains challenging. Diagnosis is based on biopsy or surgery, which implies functional risks. It is necessary to develop noninvasive diagnostic tools. The goal of this study was to evaluate the diagnostic performance of dynamic contrast-enhanced MR imaging at 3T when distinguishing malignant from benign orbital tumors on a large prospective cohort.

MATERIALS AND METHODS

This institutional review board-approved prospective single-center study enrolled participants presenting with an orbital lesion undergoing a 3T MR imaging before surgery from December 2015 to May 2021. Morphologic, diffusion-weighted, and dynamic contrast-enhanced MR images were assessed by 2 readers blinded to all data. Univariable and multivariable analyses were performed. To assess diagnostic performance, we used the following metrics: area under the curve, sensitivity, and specificity. Histologic analysis, obtained through biopsy or surgery, served as the criterion standard for determining the benign or malignant status of the tumor.

RESULTS

One hundred thirty-one subjects (66/131 [50%] women and 65/131 [50%] men; mean age, 52 [SD, 17.1] years; range, 19-88 years) were enrolled. Ninety of 131 (69%) had a benign lesion, and 41/131 (31%) had a malignant lesion. Univariable analysis showed a higher median of transfer constant from blood plasma to the interstitial environment (K trans) and of transfer constant from the interstitial environment to the blood plasma (minute-1) (Kep) and a higher interquartile range of K trans in malignant-versus-benign lesions (1.1 minute-1 versus 0.65 minute-1, P = .03; 2.1 minute-1 versus 1.1 minute-1, P = .01; 0.81 minute-1 versus 0.65 minute-1, P = .009, respectively). The best-performing multivariable model in distinguishing malignant-versus-benign lesions included parameters from dynamic contrast-enhanced imaging, ADC, and morphology and reached an area under the curve of 0.81 (95% CI, 0.67-0.96), a sensitivity of 0.82 (95% CI, 0.55-1), and a specificity of 0.81 (95% CI, 0.65-0.96).

CONCLUSIONS

Dynamic contrast-enhanced MR imaging at 3T appears valuable when characterizing orbital lesions and provides complementary information to morphologic imaging and DWI.

Automatic measurement of fetal anterior neck lower jaw angle in nuchal translucency scans

This study aims at suggesting an end-to-end algorithm based on a U-net-optimized generative adversarial network to predict anterior neck lower jaw angles (ANLJA), which are employed to define fetal head posture (FHP) during nuchal translucency (NT) measurement. We prospectively collected 720 FHP images (half hyperextension and half normal posture) and regarded manual measurement as the gold standard. Seventy percent of the FHP images (half hyperextension and half normal posture) were used to fit models, and the rest to evaluate them in the hyperextension group, normal posture group (NPG), and total group. The root mean square error, explained variation, and mean absolute percentage error (MAPE) were utilized for the validity assessment; the two-sample t test, Mann-Whitney U test, Wilcoxon signed-rank test, Bland-Altman plot, and intraclass correlation coefficient (ICC) for the reliability evaluation. Our suggested algorithm outperformed all the competitors in all groups and indices regarding validity, except for the MAPE, where the Inception-v3 surpassed ours in the NPG. The two-sample t test and Mann-Whitney U test indicated no significant difference between the suggested method and the gold standard in group-level comparison. The Wilcoxon signed-rank test revealed significant differences between our new approach and the gold standard in personal-level comparison. All points in Bland-Altman plots fell between the upper and lower limits of agreement. The inter-ICCs of ultrasonographers, our proposed algorithm, and its opponents were graded good reliability, good or moderate reliability, and moderate or poor reliability, respectively. Our proposed approach surpasses the competition and is as reliable as manual measurement.

High diagnostic accuracy of T2FLAIR at 3 T in the detection of optic nerve head edema in acute optic neuritis

OBJECTIVES

Optic nerve head edema (ONHE) detected by fundoscopy is observed in one-third of patients presenting optic neuritis (ON). While ONHE is an important semiological feature, the correlation between ONHE and optic nerve head MRI abnormalities (ONHMA), sometimes called "optic nerve head swelling," remains unknown. Our study aimed to assess the diagnostic accuracy of T2 fluid-attenuated inversion recovery (FLAIR) MRI sequence in detecting ONHE in patients with acute ON.

METHODS

In the present single-center study, data were extracted from two prospective cohort studies that consecutively included adults with a first episode of acute ON treated between 2015 and 2020. Two experienced readers blinded to study data independently analyzed imaging. A senior neuroradiologist resolved any discrepancies. The primary judgment criterion of ONHMA was assessed as optic nerve head high signal intensity on gadolinium-enhanced T2FLAIR MRI sequence. Its diagnostic accuracy was evaluated with both the gold standard of ONHE on fundus photography (FP) and peripapillary retinal nerve fiber layer thickening on optic coherence tomography (OCT).

RESULTS

A total of 102 patients were included, providing 110 affected and 94 unaffected optic nerves. Agreement was high between the different modalities: 92% between MRI and FP (k = 0.77, 95% CI: 0.67-0.88) and 93% between MRI and OCT (k = 0.77, 95% CI: 0.67-0.87). MRI sensitivity was 0.84 (95% CI: 0.70-0.93) and specificity was 0.94 (95% CI: 0.89-0.97) when compared with the FP.

CONCLUSION

Optic nerve head high T2FLAIR signal intensity corresponds indeed to the optic nerve head edema diagnosed by the ophthalmologists. MRI is a sensitive tool for detecting ONHE in patients presenting acute ON.

CLINICAL RELEVANCE STATEMENT

In patients with optic neuritis the high T2FLAIR (fluid-attenuated inversion recovery) signal intensity of the optic nerve head corresponds indeed to optic nerve head edema, which is a useful feature in optic neuritis etiological evaluation and treatment.

KEY POINTS

Optic nerve head edema is a prominent clinical feature of acute optic neuritis and is usually diagnosed during dilated or non-dilated eye fundus examination. Agreement was high between magnetic resonance imaging, fundus photography, and optical coherence tomography. Optic nerve head high T2 fluid attenuation inversion recovery signal intensity is a promising detection tool for optic nerve head edema in patients presenting acute optic neuritis.

MRI for Hepatitis B-Associated Intrahepatic Cholangiocarcinoma: A Multicenter Comparative Study

BACKGROUND

The diagnosis of intrahepatic cholangiocarcinoma (iCCA) is challenging in hepatitis B virus (HBV)-infected patients, due to the overlapping clinical manifestations and atypical imaging patterns compared to patients without HBV.

PURPOSE

To investigate the preoperative imaging characteristics of iCCA in patients with HBV in comparison to those without HBV.

STUDY TYPE

Retrospective.

SUBJECTS

431 patients with histopathologically confirmed iCCA (143 HBV-positive and 288 HBV-negative patients) were retrospectively enrolled from three institutes, and patients were allocated to the training (n = 302) and validation (n = 129) cohorts from different institutes or time period; 100 matching HBV-positive hepatocellular carcinoma (HCC) patients were also enrolled.

FIELD STRENGTH/SEQUENCE

1.5-T and 3-T, including T1- and T2-weighted, diffusion-weighted and dynamic gadopentetate dimeglumine-enhanced imaging.

ASSESSMENT

Clinical and MRI features were analyzed and compared between HBV-positive and HBV-negative patients with iCCA, and between HBV-positive patients with iCCA and HCC.

STATISTICAL TESTS

Univariate and multivariate logistic regression analyses with odds ratio (OR) to identify independent features for discriminating HBV-associated iCCA. Diagnostic model generation by incorporating independent features, and the performance for discrimination was evaluated by receiver operating characteristics with the area under the curve (AUC) and 95% confidence interval (CI). AUCs were compared by the DeLong's method. A P-value <0.05 was considered statistically significant.

RESULTS

Compared to patients without HBV, washout or degressive enhancement pattern (OR = 51.837), well-defined tumor margin (OR = 8.758) and no peritumoral bile duct dilation (OR = 4.651) were independent significant features for discriminating HBV-associated iCCAs. All these features were also the predominant MRI manifestations for HBV-associated HCC. The combined index showed an AUC of 0.798 (95% CI 0.748-0.842) in the training cohort and an AUC of 0.789 (95% CI 0.708-0.856) in the validation cohort for discrimination. The sensitivity, specificity, and accuracy were all >70%, which was superior to each single feature alone in both cohorts. [Correction added after first online publication on 29 June 2023. The Field Strength/Sequence has been updated from 5-T to 1.5-T.] DATA CONCLUSION: Preoperative MRI may help to discriminate HBV-associated iCCA.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY STAGE: 2.

Broken-fat pad sign: a characteristic radiographic finding to distinguish between knee rheumatoid arthritis and osteoarthritis

OBJECTIVES

Diagnostic imaging plays an important role in the pre-treatment workup of knee osteoarthritis (OA) and rheumatoid arthritis (RA). Herein, we identified a useful MRI sign of infrapatellar fat pad (IPFP) to improve diagnosis.

METHODS

Eighty-one age- and sex-matched RA and OA patients each, with pathological diagnosis and pre-treatment MRI were retrospectively evaluated. All randomized MR images were blinded and independently reviewed by two radiologists. The assessment process included initial diagnosis, sign evaluation, and final diagnosis, with a 3-week interval between each assessment. Broken-fat pad (BFP) sign was assessed on sagittal T2-weighted-imaging in routine MRI. The area under the curve and Cohen's kappa (κ) were used to assess the classification performance. Two shape features were extracted from IPFP for quantitative interpretation.

RESULTS

The median age of the study population was 57.6 years (range: 31.0-78.0 years). The BFP sign was detected more frequently in patients with RA (72.8%) than those with OA (21.0%). Both radiologists achieved better performance by referring to the BFP sign, with accuracies increasing from 58.0 to 75.9% and 72.8 to 79.6%, respectively. The inter-reader correlation coefficient showed an increase from fair (κ = 0.30) to substantial (κ = 0.75) upon the consideration of the BFP sign. For quantitative analysis, the IPFP of RA had significantly lower sphericity (0.54 ± 0.04 vs. 0.59 ± 0.03, p < 0.01). Despite larger surface-volume-ratio of RA (0.38 ± 0.05 vs. 0.37 ± 0.04, p = 0.25) than that of OA, there was no statistical difference.

CONCLUSIONS

The BFP sign is a potentially important diagnostic clue for differentiating RA from OA with routine MRI and reducing misdiagnosis.

CRITICAL RELEVANCE STATEMENT

With the simple and feasible broken-fat pad sign, clinicians can help more patients with early accurate diagnosis and proper treatment, which may be a valuable addition to the diagnostic workup of knee MRI assessment.

KEY POINTS

• Detailed identification of infrapatellar fat pad alterations of patients may be currently ignored in routine evaluation. • Broken-fat pad sign is helpful for differentiating rheumatoid arthritis and osteoarthritis. • The quantitative shape features of the infrapatellar fat pad may provide a possible explanation of the signs. • This sign has good inter-reader agreements and is feasible for clinical application.

Diagnostic performance and interreader agreement of individual and combined non-enhanced and contrast-enhanced MR imaging parameters in adhesive capsulitis of the shoulder

OBJECTIVE

The aims of our study were to analyze agreement among readers with different levels of expertise and diagnostic performance of individual and combined imaging signs for the diagnosis of adhesive capsulitis of the shoulder.

METHODS

In a retrospective study, contrast-enhanced shoulder MRIs of 60 patients with and 120 without clinically diagnosed adhesive capsulitis were evaluated by three readers independently. As non-enhanced imaging signs, readers evaluated signal intensity and thickness of the axillary recess capsule, thickness of the rotator interval capsule and the coracohumeral ligament as well as obliteration of subcoracoid fat. Furthermore, contrast enhancement of axillary recess and rotator interval capsule were evaluated. Data analysis included interreader reliability, ROC analysis, and logistic regression (p < 0.05).

RESULTS

Contrast-enhanced parameters showed substantially higher agreement among readers (ICC 0.79-0.80) than non-enhanced parameters (0.37-0.45). AUCs of contrast-enhanced signs (95.1-96.6%) were significantly higher (p < 0.01) than of non-enhanced imaging signs (61.5-85.9%) when considered individually. Combined evaluation of axillary recess signal intensity and thicknesses of axillary recess or rotator interval-when at least one of two signs was rated positive-increased accuracy compared to individual imaging signs, however not statistically significant.

CONCLUSION

Contrast-enhanced imaging signs show both distinctly higher agreement among readers and distinctly higher diagnostic performance compared to non-enhanced imaging signs based on the imaging protocol used in this study. Combined evaluation of parameters showed a tendency to increase discrimination; however, the effect on diagnosis of ACS was not statistically significant.

Endoscopic Rectal Ultrasound-Based Radiomics Analysis for the Prediction of Synchronous Liver Metastasis in Patients With Primary Rectal Cancer

OBJECTIVES

To develop and validate an ultrasound-based radiomics model to predict synchronous liver metastases (SLM) in rectal cancer (RC) patients preoperatively.

METHODS

Two hundred and thirty-nine RC patients were included in this study and randomly divided into training and validation cohorts. A total of 5936 radiomics features were calculated on the basis of ultrasound images to build a radiomic model and obtain a radiomics score (Rad-score) using logistic regression. Meanwhile, clinical characteristics were collected to construct a clinical model. The radiomics-clinical model was developed and validated by integrating the radiomics features with the selected clinical characteristics. The performances of three models were evaluated and compared through their discrimination, calibration, and clinical usefulness.

RESULTS

The radiomics model was developed based on 13 radiomic features. The radiomics-clinical model, which incorporated Rad-score, CEA, and CA199, exhibited favorable discrimination and calibration with areas under the receiver operating characteristic curve (AUC) of 0.920 (95% CI: 0.874-0.965) in the training cohorts and 0.855 (95% CI: 0.759-0.951) in the validation cohorts. And the AUC of the radiomics-clinical model was 0.849 (95% CI: 0.771-0.927) for the training cohorts and 0.780 (95% CI: 0.655-0.905) for the validation cohorts, the clinical model was 0.811 (95% CI: 0.718-0.905) for the training cohorts and 0.805 (95% CI: 0.645-0.965) for the validation cohorts. Moreover, decision curve analysis (DCA) further confirmed the clinical utility of the radiomics-clinical model.

CONCLUSIONS

The radiomics-clinical model performed satisfactory predictive performance, which can help improve clinical diagnosis performance and outcome prediction for SLM in RC patients.

Intraprocedural assessment of ablation margins using computed tomography co-registration in hepatocellular carcinoma treatment with percutaneous ablation: IAMCOMPLETE study

PURPOSE

The primary objective of this study was to determine the feasibility of ablation margin quantification using a standardized scanning protocol during thermal ablation (TA) of hepatocellular carcinoma (HCC), and a rigid registration algorithm. Secondary objectives were to determine the inter- and intra-observer variability of tumor segmentation and quantification of the minimal ablation margin (MAM).

MATERIALS AND METHODS

Twenty patients who underwent thermal ablation for HCC were included. There were thirteen men and seven women with a mean age of 67.1 ± 10.8 (standard deviation [SD]) years (age range: 49.1-81.1 years). All patients underwent contrast-enhanced computed tomography examination under general anesthesia directly before and after TA, with preoxygenated breath hold. Contrast-enhanced computed tomography examinations were analyzed by radiologists using rigid registration software. Registration was deemed feasible when accurate rigid co-registration could be obtained. Inter- and intra-observer rates of tumor segmentation and MAM quantification were calculated. MAM values were correlated with local tumor progression (LTP) after one year of follow-up.

RESULTS

Co-registration of pre- and post-ablation images was feasible in 16 out of 20 patients (80%) and 26 out of 31 tumors (84%). Mean Dice similarity coefficient for inter- and intra-observer variability of tumor segmentation were 0.815 and 0.830, respectively. Mean MAM was 0.63 ± 3.589 (SD) mm (range: -6.26-6.65 mm). LTP occurred in four out of 20 patients (20%). The mean MAM value for patients who developed LTP was -4.00 mm, as compared to 0.727 mm for patients who did not develop LTP.

CONCLUSION

Ablation margin quantification is feasible using a standardized contrast-enhanced computed tomography protocol. Interpretation of MAM was hampered by the occurrence of tissue shrinkage during TA. Further validation in a larger cohort should lead to meaningful cut-off values for technical success of TA.

Association of LI-RADS and Histopathologic Features with Survival in Patients with Solitary Resected Hepatocellular Carcinoma

Background Both Liver Imaging Reporting and Data System (LI-RADS) and histopathologic features provide prognostic information in patients with hepatocellular carcinoma (HCC), but whether LI-RADS is independently associated with survival is uncertain. Purpose To assess the association of LI-RADS categories and features with survival outcomes in patients with solitary resected HCC. Materials and Methods This retrospective study included patients with solitary resected HCC from three institutions examined with preoperative contrast-enhanced CT and/or MRI between January 2008 and December 2019. Three independent readers evaluated the LI-RADS version 2018 categories and features. Histopathologic features including World Health Organization tumor grade, microvascular and macrovascular invasion, satellite nodules, and tumor capsule were recorded. Overall survival and disease-free survival were assessed with Cox regression models. Marginal effects of nontargetoid features on survival were estimated using propensity score matching. Results A total of 360 patients (median age, 64 years [IQR, 56-70 years]; 280 male patients) were included. At CT and MRI, the LI-RADS LR-M category was associated with increased risk of recurrence (CT: hazard ratio [HR] = 1.83 [95% CI: 1.26, 2.66], P = .001; MRI: HR = 2.22 [95% CI: 1.56, 3.16], P < .001) and death (CT: HR = 2.47 [95% CI: 1.72, 3.55], P < .001; MRI: HR = 1.80 [95% CI: 1.32, 2.46], P < .001) independently of histopathologic features. The presence of at least one nontargetoid feature was associated with an increased risk of recurrence (CT: HR = 1.80 [95% CI: 1.36, 2.38], P < .001; MRI: HR = 1.93 [95% CI: 1.81, 2.06], P < .001) and death (CT: HR = 1.51 [95% CI: 1.10, 2.07], P < .010) independently of histopathologic features. In matched samples, recurrence was associated with the presence of at least one nontargetoid feature at CT (HR = 2.06 [95% CI: 1.15, 3.66]; P = .02) or MRI (HR = 1.79 [95% CI: 1.01, 3.20]; P = .048). Conclusion In patients with solitary resected HCC, LR-M category and nontargetoid features were negatively associated with survival independently of histopathologic characteristics. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kartalis and Grigoriadis in this issue.

Feasibility study on the clinical application of CT-based synthetic brain T1-weighted MRI: comparison with conventional T1-weighted MRI

OBJECTIVES

This study aimed to examine the equivalence of computed tomography (CT)-based synthetic T1-weighted imaging (T1WI) to conventional T1WI for the quantitative assessment of brain morphology.

MATERIALS AND METHODS

This prospective study examined 35 adult patients undergoing brain magnetic resonance imaging (MRI) and CT scans. An image synthesis method based on a deep learning model was used to generate synthetic T1WI (sT1WI) from CT data. Two senior radiologists used sT1WI and conventional T1WI on separate occasions to independently measure clinically relevant brain morphological parameters. The reliability and consistency between conventional and synthetic T1WI were assessed using statistical consistency checks, comprising intra-reader, inter-reader, and inter-method agreement.

RESULTS

The intra-reader, inter-reader, and inter-method reliability and variability mostly exhibited the desired performance, except for several poor agreements due to measurement differences between the radiologists. All the measurements of sT1WI were equivalent to that of T1WI at 5% equivalent intervals.

CONCLUSION

This study demonstrated the equivalence of CT-based sT1WI to conventional T1WI for quantitatively assessing brain morphology, thereby providing more information on imaging diagnosis with a single CT scan.

CLINICAL RELEVANCE STATEMENT

Real-time synthesis of MR images from CT scans reduces the time required to acquire MR signals, improving the efficiency of the treatment planning system and providing benefits in the clinical diagnosis of patients with contraindications such as presence of metal implants or claustrophobia.

KEY POINTS

• Deep learning-based image synthesis methods generate synthetic T1-weighted imaging from CT scans. • The equivalence of synthetic T1-weighted imaging and conventional MRI for quantitative brain assessment was investigated. • Synthetic T1-weighted imaging can provide more information per scan and be used in preoperative diagnosis and radiotherapy.

Discrepancies in MR- and CT-Based Femoral Version Measurements Despite Strong Correlations

PURPOSE

To determine the correlation and classification consistency of femoral version measurements between magnetic resonance (MR) and computed tomography (CT) using 4 commonly used measurement methods.

METHODS

A retrospective study was performed on patients with femoroacetabular impingement (FAI) who received preoperative CT and MR imaging assessment of the surgical hip and ipsilateral distal femur. Femoral version was measured using the Murphy method, the oblique method, the Reikerås method, and the Lee method. Intra- and inter-rater agreements were calculated. Linear regression and Bland-Altman analysis were performed for measurements using different imaging modalities and measurement methods. Femoral version measurements within the lower quartile, the middle 2 quartiles, and the upper quartile were classified into different groups based on their percentile within the sample population. Classification consistency rates between modalities and methods were calculated and compared.

RESULTS

Fifty-three patients (39.4 ± 9.1 years; 32 female) were included for analysis. Intra- and inter-rater reliability were high for all modalities and methods (intrarater intraclass correlation coefficient [ICC] range, 0.963-0.993; inter-rater ICC range, 0.871-0.960). MR- and CT-based femoral version measurements showed strong correlations for all methods, with the Lee method demonstrating the strongest association (r = 0.904), while the oblique method exhibited the lowest correlation (r = 0.684) (all P < .001). MR-based measurements were smaller than CT-based measurements, with mean differences ranging from 4.5° to 10.3°. Classification consistency between MR and CT ranged from 51% to 74%, whereas the consistency between different measurement methods ranged from 68% to 85%.

CONCLUSIONS

While strong correlations were observed between MR- and CT-based femoral version measurements, MR-based measurements were significantly smaller than their CT counterparts. Classification consistency between the modalities was moderate to high. Measurements between different methods showed strong correlations with high consistency rates.

LEVEL OF EVIDENCE

Level III, retrospective case series.

In vivo depiction of cortical bone vascularization with ultra-high resolution-CT and deep learning algorithm reconstruction using osteoid osteoma as a model

PURPOSE

The purpose of this study was to evaluate the ability to depict in vivo bone vascularization using ultra-high-resolution (UHR) computed tomography (CT) with deep learning reconstruction (DLR) and hybrid iterative reconstruction algorithm, compared to simulated conventional CT, using osteoid osteoma as a model.

MATERIALS AND METHODS

Patients with histopathologically proven cortical osteoid osteoma who underwent UHR-CT between October 2019 and October 2022 were retrospectively included. Images were acquired with a 1024 × 1024 matrix and reconstructed with DLR and hybrid iterative reconstruction algorithm. To simulate conventional CT, images with a 512 × 512 matrix were also reconstructed. Two radiologists (R1, R2) independently evaluated the number of blood vessels entering the nidus and crossing the bone cortex, as well as vessel identification and image quality with a 5-point scale. Standard deviation (SD) of attenuation in the adjacent muscle and that of air were used as image noise and recorded.

RESULTS

Thirteen patients with 13 osteoid osteomas were included. There were 11 men and two women with a mean age of 21.8 ± 9.1 (SD) years. For both readers, UHR-CT with DLR depicted more nidus vessels (11.5 ± 4.3 [SD] (R1) and 11.9 ± 4.6 [SD] (R2)) and cortical vessels (4 ± 3.8 [SD] and 4.3 ± 4.1 [SD], respectively) than UHR-CT with hybrid iterative reconstruction (10.5 ± 4.3 [SD] and 10.4 ± 4.6 [SD], and 4.1 ± 3.8 [SD] and 4.3 ± 3.8 [SD], respectively) and simulated conventional CT (5.3 ± 2.2 [SD] and 6.4 ± 2.5 [SD], 2 ± 1.2 [SD] and 2.4 ± 1.6 [SD], respectively) (P < 0.05). UHR-CT with DLR provided less image noise than simulated conventional CT and UHR-CT with hybrid iterative reconstruction (P < 0.05). UHR-CT with DLR received the greatest score and simulated conventional CT the lowest score for vessel identification and image quality.

CONCLUSION

UHR-CT with DLR shows less noise than UHR-CT with hybrid iterative reconstruction and significantly improves cortical bone vascularization depiction compared to simulated conventional CT.

Enhanced CT imaging artificial neural network coronary artery calcification score assisted diagnosis

BACKGROUND

The study of coronary artery calcification (CAC) may assist in identifying additional coronary artery problem protective factors. On the contrary side, due to the wide variety of CAC as individuals, CAC research is difficult. Due to this, evaluating data for investigation is becoming complicated.

OBJECTIVE

To use a multi-layer perceptron, we investigated the accuracy and reliability of synthetic CAC coursework or hazard classification in pre or alors chest computerized tomography (CT) of arrangements resolutions in this analysis.

method

Photographs of the chest from similar individuals as well as calcium-just and non-gated pictures were incorporated. This cut thickness ordered CT pictures (bunch A: 1 mm; bunch B: 3 mm). The CAC rating was determined utilizing calcification score picture information, and became standard for tests. While the control treatment's machine learning program was created using 170 computed tomography pictures and evaluated using 144 scans, group A's machine learning algorithm was created using 150 chest CT diagnostic tests.

RESULTS

334 external related pictures (100 μm: 117; 0.5 mm x: 117) of 117 individuals and 612 inside design organizing (1 mm: 294; mm3: 314) of 406 patients were surveyed. Pack B had 0.94, however, tests An and b had 0.90 (95% CI: 0.85-0.93) ICCs between significant learning and gold expenses (0.92-0.96). Dull Altman plots agreed well. A machine teaching approach successfully identified 71% of cases in category A is 81% of patients in section B again for cardiac risk class.

CONCLUSION

Regression risk evaluation algorithms could assist in categorizing cardiorespiratory individuals into distinct risk groups and conveniently personalize the treatments to the patient's circumstances. The models would be based on information gathered through CAC. On both 1 and 3-mm scanners, the automatic determination of a CAC value and cardiovascular events categorization that used a depth teaching approach was reliable and precise. The layer thickness of 0.5 mm on chest CT was slightly less accurate in CAC detection and risk evaluation.

Predicting tumor deposits in rectal cancer: a combined deep learning model using T2-MR imaging and clinical features

BACKGROUND

Tumor deposits (TDs) are associated with poor prognosis in rectal cancer (RC). This study aims to develop and validate a deep learning (DL) model incorporating T2-MR image and clinical factors for the preoperative prediction of TDs in RC patients.

METHODS AND METHODS

A total of 327 RC patients with pathologically confirmed TDs status from January 2016 to December 2019 were retrospectively recruited, and the T2-MR images and clinical variables were collected. Patients were randomly split into a development dataset (n = 246) and an independent testing dataset (n = 81). A single-channel DL model, a multi-channel DL model, a hybrid DL model, and a clinical model were constructed. The performance of these predictive models was assessed by using receiver operating characteristics (ROC) analysis and decision curve analysis (DCA).

RESULTS

The areas under the curves (AUCs) of the clinical, single-DL, multi-DL, and hybrid-DL models were 0.734 (95% CI, 0.674-0.788), 0.710 (95% CI, 0.649-0.766), 0.767 (95% CI, 0.710-0.819), and 0.857 (95% CI, 0.807-0.898) in the development dataset. The AUC of the hybrid-DL model was significantly higher than the single-DL and multi-DL models (both p < 0.001) in the development dataset, and the single-DL model (p = 0.028) in the testing dataset. Decision curve analysis demonstrated the hybrid-DL model had higher net benefit than other models across the majority range of threshold probabilities.

CONCLUSIONS

The proposed hybrid-DL model achieved good predictive efficacy and could be used to predict tumor deposits in rectal cancer.

CRITICAL RELEVANCE STATEMENT

The proposed hybrid-DL model achieved good predictive efficacy and could be used to predict tumor deposits in rectal cancer.

KEY POINTS

• Preoperative non-invasive identification of TDs is of great clinical significance. • The combined hybrid-DL model achieved good predictive efficacy and could be used to predict tumor deposits in rectal cancer. • A preoperative nomogram provides gastroenterologist with an accurate and effective tool.

Quantifying iodine concentration in the normal bowel wall using dual-energy CT: influence of patient and contrast characteristics

This study aimed to establish quantitative references of the normal bowel wall iodine concentration (BWIC) using dual energy CT (DECT). This single-center retrospective study included 248 patients with no history of gastrointestinal disease who underwent abdominal contrast-enhanced DECT between January and April 2022. The BWIC was normalized by the iodine concentration of upper abdominal organs (BWICorgan,) and the iodine concentration (IC) of the aorta (BWICaorta). BWIC decreased from the stomach to the rectum (mean 2.16 ± 0.63 vs. 2.19 ± 0.63 vs. 2.1 ± 0.58 vs. 1.67 ± 0.47 vs. 1.31 ± 0.4 vs. 1.18 ± 0.34 vs. 0.94 ± 0.26 mgI/mL for the stomach, duodenum, jejunum, ileum, right colon, left colon and rectum, respectively; P < 0.001). By multivariate analysis, BWIC was associated with a higher BMI (OR:1.01, 95% CI 1.00-1.02, P < 0.001) and with a higher injected contrast dose (OR: 1.51; 95% CI 1.36-1.66, P < 0.001 and 2.06; 95% CI 1.88-2.26, P < 0.001 for 500 mgI/kg and 600 mgI/kg doses taking 400 mgI/kg dose as reference). The BWICorgan was shown independent from patients and contrast-related variables while the BWICaorta was not. BWIC varies according to bowel segments and is dependent on the total iodine dose injected. It shall be normalized with the IC of the upper abdominal organs.

Agreement between Optoelectronic System and Wearable Sensors for the Evaluation of Gait Spatiotemporal Parameters in Progressive Supranuclear Palsy

The use of wearable sensors for calculating gait parameters has become increasingly popular as an alternative to optoelectronic systems, currently recognized as the gold standard. The objective of the study was to evaluate the agreement between the wearable Opal system and the optoelectronic BTS SMART DX system for assessing spatiotemporal gait parameters. Fifteen subjects with progressive supranuclear palsy walked at their self-selected speed on a straight path, and six spatiotemporal parameters were compared between the two measurement systems. The agreement was carried out through paired data test, Passing Bablok regression, and Bland-Altman Analysis. The results showed a perfect agreement for speed, a very close agreement for cadence and cycle duration, while, in the other cases, Opal system either under- or over-estimated the measurement of the BTS system. Some suggestions about these misalignments are proposed in the paper, considering that Opal system is widely used in the clinical context.

Tomosynthesis performance compared to radiography and computed tomography for sacroiliac joint structural damage detection in patients with suspected axial spondyloarthritis

Purpose

To compare tomosynthesis performance to radiography for the differentiation of sacroiliitis versus normal or degenerative changes in sacroiliac joints in patients with suspected axial spondyloarthritis (SpA).

Materials and methods

Radiography, tomosynthesis and CT of sacroiliac joints (29 patients) were performed on the same day in consecutive patients with suspected SpA. The examinations were retrospectively read independently, blinded by two radiologists (one junior and one senior, and twice by one junior). Interobserver and intraobserver agreement was evaluated using the kappa coefficient. Effective doses for each imaging sensitivity, specificity and accuracy were assessed and compared with CT as gold standard.

Results

CT detected 15/58 joints with sacroiliitis. The imaging sensitivity, specificity and accuracy were 60%, 84% and 44%, respectively, for radiography and 87%, 91% and 77% for tomosynthesis. The mean effective dose for tomosynthesis was significantly lower than that of CT (5-fold less) and significantly higher than that of radiography (8-fold more).

Conclusion

Tomosynthesis is superior to radiography for sacroiliitis detection in patients with suspected SpA, with 5-fold less radiation exposure than CT.