Journal of Clinical Imaging Science最新文献

We report a rare case of a 28-year-old African-American woman with chronic hidradenitis suppurativa (HS), in whom breast masses were initially misattributed to HS-related inflammation, delaying diagnosis of breast cancer. She presented with back pain and diagnostic work-up revealed thoracic vertebral metastasis. Dedicated breast imaging showed suspicious breast masses and biopsy confirmed invasive ductal carcinoma. This case highlights the importance of breast imaging when inflammatory skin conditions of the breast fail to respond to standard treatment.

Objectives: The objectives of the study are to compare the effect on image quality of a motion artifact correction algorithm (CAVAREC) alone versus in combination with an automated bone removal algorithm (ZIBOS) for motion-degraded intraprocedural liver cone-beam computed tomography (CBCT) images.

Material and methods: In this retrospective, two-center, Institutional Review Board (IRB)-approved study, 48 CBCTs from 41 patients were included. Inclusion criteria were (a) age ≥18; (b) liver CBCT with contrast injected at the main, right, or left hepatic artery; and (c) CBCT motion-degraded. Exclusion criteria were (a) no visible tumor and (b) CBCT not capturing the entire liver. The mean (standard deviation [SD]) age was 64 (7) years, 81% male. 65% had hepatocellular carcinoma and 35% metastatic cancer. 69% CBCTs were from transarterial radioembolization (TARE) mapping, 25% transarterial chemoembolization, and 6% TARE treatment. Mean (SD) maximum tumor diameter was 4.6 (2.7) cm. CBCT images were processed with CAVAREC (prototype, Siemens Healthineers AG, Forchheim, Germany) and CAVAREC + ZIBOS (work in progress, Comprehenso, Hannover, Germany). Using CoroEval, sharpness for two segmental arteries per case was obtained quantitatively. Three blinded interventional radiologists independently evaluated overall image quality on a 0-100 scale and large vessels, small vessels, vessel sharpness, tumor feeders, tumor blush, and streak artifacts on a -50 to +50 scale relative to uncorrected images. Results were analyzed with paired t-tests and Wilcoxon signed-rank tests, adjusting P-values with the Benjamini-Hochberg procedure.

Results: On quantitative assessment, mean (SD) sharpness for uncorrected, CAVAREC, and CAVAREC + ZIBOS (C+Z) images was 0.281 (0.04), 0.287 (0.04), and 0.284 (0.04), respectively, P = 0.02 for uncorrected versus CAVAREC and P > 0.05 for other comparisons. On qualitative assessment, mean (SD) overall quality for uncorrected, CAVAREC, and C+Z images was 45 (14), 53 (16), and 53 (17), respectively, P < 0.001 for both uncorrected versus CAVAREC and uncorrected versus C+Z and P = 0.06 for CAVAREC versus C+Z. The mean preference for both CAVAREC and C+Z compared to uncorrected images for all parameters ranged from +4.3 to +9.5, P < 0.001, except tumor blush which was +1.6 for CAVAREC and +0.9 for C+Z, P > 0.05. CAVAREC versus C+Z was not significant for any parameter.

Conclusion: Motion artifact correction of liver CBCT images using CAVAREC improves image quality significantly. According to observer studies, integrating the automated bone segmentation algorithm ZIBOS with CAVAREC does not degrade image quality.

Objectives: This study aims to evaluate the image quality of 55 keV virtual monoenergetic imaging (VMI) in carotid dual-energy computed tomography (CT) angiography (DE-CTA) reconstructed using deep learning image reconstruction (DLIR) algorithms and traditional iterative reconstruction algorithms.

Material and methods: This prospective study included 48 patients who underwent DE-CTA examinations at our institution between December 2024 and January 2025. Image reconstructions were performed using 50% strength adaptive statistical iterative reconstruction-Veo (ASIR-V 50%), low and high strengths DLIR (DLIR-L and DLIR-H) algorithms. Objective image quality was evaluated by measuring background noise (standard deviation), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) at key anatomical locations, including the aortic arch, common carotid artery, carotid bifurcation, and internal carotid artery. Two senior radiologists conducted subjective assessments of image quality, focusing on image noise, artifacts, and vessel continuity, and the clarity of vascular wall margin.

Results: Compared with ASIR-V 50% and DLIR-L, DLIR-H significantly improved image quality by reducing background noise and increasing SNR and CNR (P < 0.05). Subjectively, DLIR-H images demonstrated better suppression of noise and clearer vascular wall margin (P < 0.05). Subgroup analysis revealed that these improvements were more pronounced in patients with a body mass index (BMI) ≥24 kg/m². No significant differences were observed in CT attenuations among the three reconstruction methods (P > 0.05).

Conclusion: At 55 keV VMI in carotid DE-CTA, DLIR-H significantly enhanced image quality, particularly by reducing noise and preserving fine anatomical structures. Its efficacy was especially notable in patients with BMI ≥24 kg/m².

Neuronal migrational anomalies, cortical dysplasias, hemimegalencephaly, and microcephalies are collectively termed malformations of cortical development (MCD). MCDs have multifactorial etiologies including genetic, environmental, vascular, and infectious insults between the late 1^st trimester and late 2^nd trimester. Neonatal correlates of various neuronal migration anomalies detected on fetal magnetic resonance imaging are illustrated. Physiologic immaturity of sulci and certain mimics of migration anomalies can pose a challenge, and these are also outlined.

Computed tomography (CT) is often utilized for evaluation of patients presenting with traumatic injuries, and differentiating between traumatic and non-traumatic pathologies can be difficult, particularly for uncommon or atypically presenting disease. A 43-year-old male presented to the hospital as a restrained driver in a motor vehicle collision, and CT angiogram of the neck revealed a well-defined, mixed cystic and solid lesion, with enhancing components that were initially interpreted as a retropharyngeal hematoma with contained contrast extravasation. Serial laryngoscopes revealed stability of the lesion, and the mass was resected the following day without complication. Histopathology revealed this mass to be a cystic parathyroid adenoma. Diagnosis of a functional cystic parathyroid adenoma is difficult, and an atypical presentation like in our case is challenging to the radiologist when assessing trauma CTs. The typical findings of mixed solid and cystic component, intense enhancement of the solid component, and prominent inferior polar artery should increase suspicion for a cystic parathyroid adenoma. This case emphasizes the need for radiologists to maintain a broad differential diagnosis when reviewing trauma imaging, particularly in the head-and-neck region.

Magnetic resonance imaging (MRI) has proven its strengths in soft-tissue imaging, but advancements in imaging techniques have now enhanced bone visualization. This review evaluates the effectiveness and reliability of black bone MRI for detecting and assessing bone abnormalities, particularly in orthopedic and craniofacial conditions. Articles from indexed journals such as Science Direct, Springer, Elsevier, PubMed/Medline, Wiley Online Library, and Scopus were analyzed, adhering to preferred reporting items for systematic review and meta-analysis guidelines. Ten studies met the criteria and were included in the study. The review highlights that black bone MRI outperforms computed tomography by offering superior imaging of bone and intracranial structures, leading to higher surgical accuracy and improved diagnostic precision.

Objectives: This study aimed to assess the diagnostic performance of whole-body magnetic resonance imaging (wbMRI) in comparison with gold standard ¹⁸F-fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT) for detecting metastases in patients with gynecological cancer (GCa).

Material and methods: We prospectively enrolled five histologically proven GCa patients who underwent FDG-PET/CT and were identified with metastatic disease in their lungs. We customized a wbMRI protocol including ultra-short echo time (UTE) MRI sequence with a stack-of-spiral acquisition and imaged the patients on a 3 Tesla MRI scanner. Nuclear medicine physicians and radiologists reviewed the PET/CT and MRI images respectively and compared the findings for each patient. PET/CT images were accepted gold standard. We calculated the sensitivities of wbMRI and assessed the differences in diagnostic performance between PET/CT and wbMRI using McNemar's test (P < 0.05).

Results: Three patients had cervical cancer while two had ovarian cancer. FDG-PET/CT detected a total of 44 findings (including nodules, lesions, and lymph nodes) across the five patients. WbMRI showed 39 findings with a sensitivity of 89%. McNemar's test revealed no statistically significant difference between wbMRI and PET/CT. The pre-contrast UTE sequence displayed 33 findings (33/44) and in detecting lung nodules, it displayed an accuracy of 70% (7/10).

Conclusion: This pilot study suggests that wbMRI demonstrates no statistically significant difference compared to ¹⁸FDG-PET/CT for detecting gynecological metastases. Furthermore, the UTE sequence proved valuable as part of the wbMRI protocol for detecting metastases without the need for a contrast agent.

Objectives: This study aims to evaluate the relationship between multiparametric magnetic resonance imaging (MRI) features - including T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and dynamic contrast enhancement (DCE) - and molecular subtypes of breast cancer, to enhance non-invasive diagnostic stratification.

Material and methods: This retrospective study enrolled 134 consecutive patients with pathologically confirmed breast cancer. A comparative analysis was performed to evaluate intergroup variations in clinicopathological characteristics, morphological features, and multiparametric MRI parameters (including T2WI signal intensity, ADC value, early-phase enhancement rate, and time-intensity curve pattern) across the four molecular subtypes.

Results: The cohort comprised 134 breast cancer patients stratified into molecular subtypes as follows: Luminal A (n = 22, 16.4%), Luminal B (n = 82, 61.2%), human epidermal growth factor receptor-2 (HER-2) (+) (n = 13, 9.7%), and triple-negative breast cancer (TNBC) (n = 17, 12.7%). Among the subtypes, there were statistically significant differences in terms of age, Ki-67 index, mass shape, margin, internal enhancement characteristic, T2WI signal, ADC value, early enhancement rate, and time intensity curve (TIC) pattern (P = 0.025; P < 0.001; P = 0.039; P < 0.001; P = 0.043; P = 0.014; P < 0.001; P = 0.009; and P = 0.020, respectively). Luminal subtypes predominantly exhibited irregular shapes, unclear/spiculated margins, heterogeneous enhancement, and uneven hypointense or isointense signal on T2WI. TNBC displayed regular shapes with smooth margins, ring enhancement, and uneven high signal on T2WI. The mean ADC value was significantly higher in HER-2 (+). Luminal A exhibited the highest early enhancement rate, while HER-2 (+) demonstrated the lowest. Analysis of TIC pattern revealed that type III curves were predominant across all subtypes, with a higher proportion observed in Luminal A and TNBC compared to Luminal B and HER-2 (+). Notably, no significant differences were observed between molecular subtypes in terms of menopausal status, axillary node metastasis, lesion type, number, size, and distribution, internal characteristics of non-mass enhancement lesions (P > 0.05).

Conclusion: Multiparametric MRI features, particularly ADC values, DCE kinetics, and T2WI signals, demonstrate significant associations with breast cancer molecular subtypes. These imaging biomarkers offer potential for non-invasive subtype prediction, supporting more tailored diagnostic and treatment strategies.

Objectives: The objectives of the study are to compare the prostate image quality (IQ) obtained with single-shot echo-planar diffusion-weighted imaging (ss-DWI), reduced field-of-view diffusion-weighted imaging (rf-DWI), and readout-segmented multi-shot diffusion-weighted imaging (rs-DWI), along with their diagnostic efficacy for clinically significant prostate cancer (csPCa), to optimize prostate magnetic resonance diffusion-weighted imaging sequences.

Material and methods: We have analyzed prostate images from 72 patients who underwent ss-DWI, rs-DWI, and rf-DWI magnetic resonance imaging (MRI) scans from March 2023 to September 2024. Two radiologists qualitatively evaluated the IQ of three diffusion-weighted imaging (DWI) sequences and corresponding apparent diffusion coefficient (ADC) images as well as Prostate Imaging Reporting and Data System Version 2.1 (PI-RADS v2.1) category of prostate nodules and measured the anterior-posterior diameter and right-left (RL) diameters of the prostate on both types of images and ADC values of prostate nodules. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Qualitative and quantitative differences across DWI techniques were statistically compared.

Results: The rf-DWI images demonstrated optimal clarity, minimal distortion/artifacts, and the highest CNR and lowest SNR. The RL diameter of the prostate measured on T2-weighted images was larger than those on ss-DWI images, and the RL diameter measured on ss-DWI images was smaller than those measured on rf-DWI images (P < 0.05). The rf-DWI-based PI-RADS v2.1 categorization and ADC values showed higher diagnostic accuracy for csPCa versus ss-DWI/rs-DWI, with optimal ADC cutoffs of 0.958 × 10³ mm²/s (transition zone) and 0.769 × 10³ mm²/s (peripheral zone).

Conclusion: Compared to ss-DWI and rs-DWI, the rf-DWI sequence demonstrates optimal IQ and quantitative parameters with the optimum diagnostic performance for csPCa, making it the best choice for prostate scans.

A 68-year-old female patient, diagnosed with stage Ib left upper lobe lung cancer, underwent surgery in June 2021. The patient underwent both ¹⁸F-fluorodeoxyglucose positron emission tomography (PET)/computed tomography (CT) and PET/magnetic resonance imaging (MRI) examinations on December 19. In our study, we found that PET/MRI identified more pleural and bone metastases and provided accurate total metabolic tumor volume, which might have significant value for the treatment options and prognosis assessment of certain patients, while PET/CT clearly underestimated this aspect. In conclusion, we believed that although there was no significant difference between PET/CT and PET/MRI in the clinical staging of patients with advanced lung cancer, PET/MRI provided richer and more accurate lesion information. The predictive models constructed from these parameter data held important value for changes in treatment methods, survival time, and prognosis for some patients also in the advanced stage of lung cancer.