Effects of Tetrahydrolipstatin on Glioblastoma in Mice: MRI-Based Morphologic and Texture Analysis Correlated with Histopathology and Immunochemistry Findings-A Pilot Study

BACKGROUND

This study aimed to investigate the effects of tetrahydrolipstatin (orlistat) on heterotopic glioblastoma in mice by applying MRI and correlating the results with histopathology and immunochemistry.

METHODS

Human glioblastoma cells were injected subcutaneously into the groins of immunodeficient mice. After tumor growth of >150 mm3, the animals were assigned into a treatment group (n = 6), which received daily intraperitoneal injections of orlistat, and a control group (n = 7). MRI was performed at the time of randomization and before euthanizing the animals. Tumor volumes were calculated, and signal intensities were analyzed. The internal tumor structure was evaluated visually and with texture analysis. Western blotting and protein expression analysis were performed.

RESULTS

At histology, all tumors showed high mitotic and proliferative activity (Ki67 ≥ 10%). Reduced fatty acid synthetase expression was measured in the orlistat group (p < 0.05). Based on the results of morphologic MRI-based analysis, tumor growth remained concentric in the control group and changed to eccentric in the treatment group (p < 0.05). The largest area under the receiver operating curve of the predictors derived from the texture analysis of T2w images was for wavelet transform parameters WavEnHL_s3 and WavEnLH_s4 at 0.96 and 1.00, respectively.

CONCLUSIONS

Orlistat showed effects on heterotopically implanted glioblastoma multiforme in MRI studies of mice based on morphologic and texture analysis.

Baseline parenchymal blood volume is a potential prognostic imaging biomarker in patients with malignant liver tumors treated with transarterial chemoembolization

PURPOSE

To assess the prognostic value of Parenchymal Blood Volume (PBV) in predicting survival, tumor response, and PBV response after transarterial chemoembolization (TACE).

METHODS

A total of 137 patients with malignant liver tumors who were treated with TACE between 07/2016 and 07/2018 were evaluated. Computed tomography illustrations were reworked at a dedicated workstation to create a PBV map which was overlapped with the associated magnetic resonance image to determine tumor diameter and PBV. Patients were divided into two groups according to their initial PBV value: PBV < 50 or ≥ 50 ml/l.

RESULTS

Retrospectively, for patients with at least 2 TACE and initial PBV < 50 ml/l (n = 27), the tumor volume, regardless of the primary tumor type, decreased by 13.26%, and PBV showed a decrease of 23.11%. For 84 patients with PBV ≥ 50 ml/l, the tumor volume decreased by 24.01%, and PBV showed a more substantial decrease of 44.69% (both p < 0.001). In the overall study population (n = 137), patients with an initial PBV ≥ 50 ml/l (n = 101) survived for an average of 15.05 months, while patients with an initial PBV < 50 ml/l (n = 36) survived for 10.01 months (p < 0.002). Subgroup analysis indicated that median survival in the HCC group was longer at PBV ≥ 50 ml/l. For CRC and other primary tumors, the survival time for high and low initial PBV was almost identical.

CONCLUSION

Our study reveals a noteworthy correlation between high initial PBV values and a significant reduction in both relative and absolute tumor volume. This association suggests a potential prognostic indicator, indicating that elevated PBV may signify a more favorable response to transarterial chemoembolization (TACE). Additionally, patients with high initial PBV values experienced an extended overall survival time. Notably, the subgroup analysis highlighted a prolonged survival time in the HCC group with elevated initial PBV values. These findings underscore the potential significance of assessing PBV as a predictive factor in the context of TACE, especially in specific tumor entities such as HCC. Further investigations are essential to validate and extrapolate these observations to optimize patient outcomes.

Retrospective Long-Term Evaluation of Conventional Transarterial Chemoembolization for Hepatocellular Carcinoma over 20 Years

The aim of this study was to retrospectively evaluate the effects of conventional transarterial chemoembolization (cTACE) for the treatment of hepatocellular carcinoma over 20 years regarding overall survival (OS) and prognostic factors for OS. During the period from 1996 to 2016, 836 patients with HCC were treated with cTACE. Data evaluation was performed on the basis of pre- and postinterventional MRI and CT scans. Survival analysis was performed by Kaplan-Meier estimator; prognostic factors were determined by the use of Cox regression analysis. Overall, 4084 (mean 4.89 TACE sessions/patient) procedures were assessed. Median OS was 700 days (99% CI, 632.8-767.2). Depending on the indication, patients treated with a neoadjuvant intention showed the best OS (1229 days, 99% CI 983.8-1474.2) followed by curative intention (787 days, 99% CI 696.3-877.7), and then palliative intention (360 days, 99% CI 328.4-391.6). Portal vein thrombosis (HR 2.19, CI 1.63-2.96, and p < 0.01) and Child-Pugh class B or worse (HR 1.44, CI 1.11-1.86, and p < 0.001) were significantly associated with shorter OS. Patients with HCC benefit from TACE after careful patient selection. Portal vein thrombosis and Child-Pugh class B or worse are significantly unfavorable prognostic factors for patients' survival.

Short- and Long-Term Outcomes after Radiofrequency Ablation of Osteoid Osteomas

The aim of this study was to evaluate treatment of osteoid osteomas using bipolar radiofrequency ablation (RFA) and patients' quality of life before and after therapy. We retrospectively evaluated patients who underwent bipolar RFA of osteoid osteomas between 2001 and 2016. We assessed patients' symptoms before and after treatment (four weeks after treatment and long-term) using a questionnaire including severity and quality of pain on a 10-point scale (1 = no pain, 10 = severe pain), motion restrictions, pain-related sleep disorders, and necessary pain medication. In addition, we evaluated technical success, complications, hospitalization length, and patients' satisfaction with treatment. This study included 62 patients (43 [69.4%] males, 26.2 ± 13.2 years). Average nidus size was 5.7 ± 2.6 mm. The rate of technical success was 100%. All RFAs were performed without any complications. One patient showed a recurrence, resulting in a recurrence rate of 1.6%, which was successfully treated by another session of RFA. Average hospitalization length was 1.5 ± 0.5 days. A total of 36 patients (58.1%) participated in the questionnaire, reporting an average pain severity of 8.2 ± 1.6 before RFA compared to 3.4 ± 3.0 four weeks after and an average of 2.1 ± 2.3, 6.6 years after therapy, (both p < 0.001). After therapy, 31 (86.1%) patients had no pain. The majority of patients (n = 34, 94.4%) had reduced or absent motion restriction after therapy (p < 0.001). Patient satisfaction rate was 91.7%. In conclusion, bipolar RFA is a safe and effective treatment modality for osteoid osteomas and improves quality of life by reducing pain severity and motion restrictions.

Imaging-based risk stratification of patients with pulmonary embolism based on dual-energy CT-derived radiomics

BACKGROUND

Technological progress in the acquisition of medical images and the extraction of underlying quantitative imaging data has introduced exciting prospects for the diagnostic assessment of a wide range of conditions. This study aims to investigate the diagnostic utility of a machine learning classifier based on dual-energy computed tomography (DECT) radiomics for classifying pulmonary embolism (PE) severity and assessing the risk for early death.

METHODS

Patients who underwent CT pulmonary angiogram (CTPA) between January 2015 and March 2022 were considered for inclusion in this study. Based on DECT imaging, 107 radiomic features were extracted for each patient using standardized image processing. After dividing the dataset into training and test sets, stepwise feature reduction based on reproducibility, variable importance and correlation analyses were performed to select the most relevant features; these were used to train and validate the gradient-boosted tree models.

RESULTS

The trained machine learning classifier achieved a classification accuracy of .90 for identifying high-risk PE patients with an area under the receiver operating characteristic curve of .59. This CT-based radiomics signature showed good diagnostic accuracy for risk stratification in individuals presenting with central PE, particularly within higher risk groups.

CONCLUSION

Models utilizing DECT-derived radiomics features can accurately stratify patients with pulmonary embolism into established clinical risk scores. This approach holds the potential to enhance patient management and optimize patient flow by assisting in the clinical decision-making process. It also offers the advantage of saving time and resources by leveraging existing imaging to eliminate the necessity for manual clinical scoring.

Liver metastases of neuroendocrine tumors: Conventional transarterial chemoembolization and thermal ablation

PURPOSE

 To identify prognostic factors for patients with neuroendocrine liver metastases (NELM) undergoing conventional transarterial chemoembolization (c-TACE), microwave ablation (MWA), or laser interstitial thermotherapy (LITT) and to determine the most effective therapy regarding volume reduction of NELM and survival.

MATERIALS AND METHODS

 Between 1996 and 2020, 130 patients (82 men, 48 women) were treated with c-TACE, and 40 patients were additionally treated with thermal ablation. Survival was retrospectively analyzed using the Kaplan-Meier-method. Additional analyses were performed depending on the therapeutic intention (curative, palliative, symptomatic). Prognostic factors were derived using Cox regression. To find predictive factors for volume reduction in response to c-TACE, a mixed-effects model was used.

RESULTS

 With c-TACE, an overall median volume reduction of 23.5 % was achieved. An average decrease in tumor volume was shown until the 6th c-TACE treatment, then the effect stopped. C-TACE interventions were most effective at the beginning of c-TACE therapy, and treatment breaks longer than 90 days negatively influenced the outcome. Significant prognostic factors for survival were number of liver lesions (p = 0.0001) and type of therapeutic intention (p < 0.0001). Minor complications and one major complication occurred in 20.3 % of LITT and only in 8.6 % of MWA interventions. Complete ablation was observed in 95.7 % (LITT) and 93.1 % (MWA) of interventions.

CONCLUSION

 New prognostic factors were found for survival and volume reduction. Efficacy of c-TACE decreases after the 6th intervention and treatment breaks longer than 90 days should be avoided. With thermal ablation, a high rate of complete ablation was achieved, and survival improved.

KEY POINTS

  · Number of liver lesions and therapeutic intention are prognostic factors for survival.. · Regarding volume reduction, C-TACE is most effective at the beginning of treatment and longer treatment breaks should be avoided.. · With MWA and LITT, a high rate of complete ablation was achieved. MWA trends toward fewer complications than LITT in the treatment of NELM (p = 0.07)..

Lipiodol as a Predictive Indicator for Therapy Response to Transarterial Chemoembolization of Hepatocellular Carcinoma

Background: The predictive value of Lipiodol was evaluated for response evaluation of hepatocellular carcinoma (HCC) treated with conventional transarterial chemoembolization (cTACE) by analysis of the enhancement pattern during angiography and in postinterventional computed tomography (CT). Materials and Methods: This retrospective study included 30 patients (mean age 63 years, range: 36 to 82 years, 22 males) with HCC. Patients received three Lipiodol-based cTACE sessions, each followed by an unenhanced CT within 24-h. Contrast-enhanced magnetic resonance imaging (MRI) was acquired before and after the treatment to determine tumor response. Lipiodol enhancement pattern, tumor vascularization, and density were evaluated by angiography and CT. Initial tumor size and response to cTACE were analyzed by MRI according to modified response evaluation criteria in solid tumors (mRECIST) in a 4-week follow-up. Results: Analysis of HCC lesions (68 lesions in 30 patients) during cTACE revealed clear visibility and hypervascularization in angiography as a potential independent parameter able to predict tumor response. A significant correlation was found for response measurements by volume (p = 0.012), diameter (p = 0.006), and according to mRECIST (p = 0.039). The amount of Lipiodol and enhancement pattern in postinterventional CT did not correlate with therapy response. Measurements of Hounsfield unit values after cTACE do not allow sufficient prediction of the tumor response. Conclusion: Hypervascularized HCC lesions with clear visibility after Lipiodol administration in the angiography respond significantly better to cTACE compared to hypo- or nonvascularized lesions.

Advancing Differentiation of Hepatic Metastases in Malignant Melanoma through Dual-Energy Computed Tomography Rho/Z Maps

OBJECTIVES

The aim of this study is to evaluate the diagnostic accuracy of dual-energy computed tomography (DECT)-based Rho/Z maps in differentiating between metastases and benign liver lesions in patients diagnosed with malignant melanoma compared to conventional CT value measurements.

METHODS

This retrospective study included 73 patients (mean age, 70 ± 13 years; 43 m/30 w) suffering from malignant melanoma who had undergone third-generation DECT as part of tumor staging between December 2017 and December 2021. For this study, we measured Rho (electron density) and Z (effective atomic number) values as well as Hounsfield units (HUs) in hypodense liver lesions. Values were compared, and diagnostic accuracy for differentiation was computed using receiver operating characteristic (ROC) curve analyses. Additional performed MRI or biopsies served as a standard of reference.

RESULTS

A total of 136 lesions (51 metastases, 71 cysts, and 14 hemangiomas) in contrast-enhanced DECT images were evaluated. The most notable discrepancy (p < 0.001) between measured values and the highest diagnostic accuracy for distinguishing melanoma metastases from benign cysts was observed for the Z (0.992; 95% CI, 0.956-1) parameters, followed by Rho (0.908; 95% CI, 0.842-0.953) and finally HU120kV (0.829; 95% CI, 0.751-0.891). Conversely, when discriminating between liver metastases and hemangiomas, the HU120kV parameters showed the most significant difference (p < 0.001) and yielded the highest values for diagnostic accuracy (0.859; 95% CI, 0.740-0.937), followed by the Z parameters (0.790; 95% CI, 0.681-0.876) and finally the Rho values (0.621; 95% CI, 0.501-0.730).

CONCLUSIONS

Rho and Z measurements derived from DECT allow for improved differentiation of liver metastases and benign liver cysts in patients with malignant melanoma compared to conventional CT value measurements. In contrast, in differentiation between liver hemangiomas and metastases, Rho/Z maps show inferior diagnostic accuracy. Therefore, differentiation between these two lesions remains a challenge for CT imaging.

Predictive Value of Dual-Energy CT-Derived Metrics for the Use of Bone Substitutes in Distal Radius Fracture Surgery

(1) Background: Low bone mineral density (BMD) is a significant risk factor for complicated surgery and leads to the increased use of bone substitutes in patients with distal radius fractures (DRFs). No accepted model has yet been established to predict the use of bone substitutes to facilitate preoperative planning. (2) Methods: Unenhanced dual-energy CT (DECT) images of DRFs were retrospectively acquired between March 2016 and September 2020 using the internal PACS system. Available follow-up imaging and medical health records were reviewed to determine the use of bone substitutes. DECT-based BMD, trabecular Hounsfield units (HU), cortical HU, and cortical thickness ratio were measured in non-fractured segments of the distal radius. Diagnostic accuracy parameters were calculated for all metrics using receiver-operating characteristic (ROC) curves and associations of all metrics with the use of bone substitutes were evaluated using logistic regression models. (3) The final study population comprised 262 patients (median age 55 years [IQR 43-67 years]; 159 females, 103 males). According to logistic regression analysis, DECT-based BMD was the only metric significantly associated with the use of bone substitutes (odds ratio 0.96, p = 0.003). However, no significant associations were found for cortical HU (p = 0.06), trabecular HU (p = 0.33), or cortical thickness ratio (p = 0.21). ROC-curve analysis revealed that a combined model of all four metrics had the highest diagnostic accuracy with an area under the curve (AUC) of 0.76. (4) Conclusions: DECT-based BMD measurements performed better than HU-based measurements and cortical thickness ratio. The diagnostic performance of all four metrics combined was superior to that of the individual parameters.

From pixels to prognosis: Imaging biomarkers for discrimination and outcome prediction of pulmonary embolism : Original Research Article

PURPOSE

Recent advancements in medical imaging have transformed diagnostic assessments, offering exciting possibilities for extracting biomarker-based information. This study aims to investigate the capabilities of a machine learning classifier that incorporates dual-energy computed tomography (DECT) radiomics. The primary focus is on discerning and predicting outcomes related to pulmonary embolism (PE).

METHODS

The study included 131 participants who underwent pulmonary artery DECT angiography between January 2015 and March 2022. Among them, 104 patients received the final diagnosis of PE and 27 patients served as a control group. A total of 107 radiomic features were extracted for every case based on DECT imaging. The dataset was divided into training and test sets for model development and validation. Stepwise feature reduction identified the most relevant features, which were used to train a gradient-boosted tree model. Receiver operating characteristics analysis and Cox regression tests assessed the association of texture features with overall survival.

RESULTS

The trained machine learning classifier achieved a classification accuracy of 0.94 for identifying patients with acute PE with an area under the receiver operating characteristic curve of 0.91. Radiomics features could be valuable for predicting outcomes in patients with PE, demonstrating strong prognostic capabilities in survival prediction (c-index, 0.991 [0.979-1.00], p = 0.0001) with a median follow-up of 130 days (IQR, 38-720). Notably, the inclusion of clinical or DECT parameters did not enhance predictive performance.

CONCLUSION

In conclusion, our study underscores the promising potential of leveraging radiomics on DECT imaging for the identification of patients with acute PE and predicting their outcomes. This approach has the potential to improve clinical decision-making and patient management, offering efficiencies in time and resources by utilizing existing DECT imaging without the need for an additional scoring system.

Potential of Dual-Energy CT-Based Collagen Maps for the Assessment of Disk Degeneration in the Lumbar Spine

RATIONALE AND OBJECTIVES

Lumbar disk degeneration is a common condition contributing significantly to back pain. The objective of the study was to evaluate the potential of dual-energy CT (DECT)-derived collagen maps for the assessment of lumbar disk degeneration.

PATIENTS AND METHODS

We conducted a retrospective analysis of 127 patients who underwent dual-source DECT and MRI of the lumbar spine between 07/2019 and 10/2022. The level of lumbar disk degeneration was categorized by three radiologists as follows: no/mild (Pfirrmann 1&2), moderate (Pfirrmann 3&4), and severe (Pfirrmann 5). Recall (sensitivity) and accuracy of DECT collagen maps were calculated. Intraclass correlation coefficient (ICC) was used to evaluate inter-reader reliability. Subjective evaluations were performed using 5-point Likert scales for diagnostic confidence and image quality.

RESULTS

We evaluated a total of 762 intervertebral disks from 127 patients (median age, 69.7 (range, 23.0-93.7), female, 56). MRI identified 230 non/mildly degenerated disks (30.2%), 484 moderately degenerated disks (63.5%), and 48 severely degenerated disks (6.3%). DECT collagen maps yielded an overall accuracy of 85.5% (1955/2286). Recall (sensitivity) was 79.3% (547/690) for the detection of no/mild lumbar disk degeneration, 88.7% (1288/1452) for the detection of moderate disk degeneration, and 83.3% (120/144) for the detection of severe disk degeneration (ICC=0.9). Subjective evaluations of DECT collagen maps showed high diagnostic confidence (median 4) and good image quality (median 4).

CONCLUSION

The use of DECT collagen maps to distinguish different stages of lumbar disk degeneration may have clinical significance in the early diagnosis of disk-related pathologies in patients with contraindications for MRI or in cases of unavailability of MRI.

Value of Dual-Energy CT-Derived Metrics for the Prediction of Bone Non-union in Distal Radius Fractures

RATIONALE AND OBJECTIVES

Bone non-union is a serious complication of distal radius fractures (DRF) that can result in functional limitations and persistent pain. However, no accepted method has been established to identify patients at risk of developing bone non-union yet. This study aimed to compare various CT-derived metrics for bone mineral density (BMD) assessment to identify predictive values for the development of bone non-union.

MATERIALS AND METHODS

CT images of 192 patients with DRFs who underwent unenhanced dual-energy CT (DECT) of the distal radius between 03/2016 and 12/2020 were retrospectively identified. Available follow-up imaging and medical health records were evaluated to determine the occurrence of bone non-union. DECT-based BMD, trabecular Hounsfield unit (HU), cortical HU and cortical thickness ratio were measured in normalized non-fractured segments of the distal radius.

RESULTS

Patients who developed bone non-union were significantly older (median age 72 years vs. 54 years) and had a significantly lower DECT-based BMD (median 68.1 mg/cm3 vs. 94.6 mg/cm3, p < 0.001). Other metrics (cortical thickness ratio, cortical HU, trabecular HU) showed no significant differences. ROC and PR curve analyses confirmed the highest diagnostic accuracy for DECT-based BMD with an area under the curve (AUC) of 0.83 for the ROC curve and an AUC of 0.46 for the PR curve. In logistic regression models, DECT-based BMD was the sole metric significantly associated with bone non-union.

CONCLUSION

DECT-derived metrics can accurately predict bone non-union in patients who sustained DRF. The diagnostic performance of DECT-based BMD is superior to that of HU-based metrics and cortical thickness ratio.

Does Dual-Energy Computed Tomography Material Decomposition Improve Radiomics Capability to Predict Survival in Head and Neck Squamous Cell Carcinoma Patients? A Preliminary Investigation

OBJECTIVE

Our study objective was to explore the additional value of dual-energy CT (DECT) material decomposition for squamous cell carcinoma of the head and neck (SCCHN) survival prognostication.

METHODS

A group of 50 SCCHN patients (male, 37; female, 13; mean age, 63.6 ± 10.82 years) with baseline head and neck DECT between September 2014 and August 2020 were retrospectively included. Primary tumors were segmented, radiomics features were extracted, and DECT material decomposition was performed. We used independent train and validation datasets with cross-validation and 100 independent iterations to identify prognostic signatures applying elastic net (EN) and random survival forest (RSF). Features were ranked and intercorrelated according to their prognostic importance. We benchmarked the models against clinical parameters. Intraclass correlation coefficients were used to analyze the interreader variation.

RESULTS

The exclusively radiomics-trained models achieved similar ( P = 0.947) prognostic performance of area under the curve (AUC) = 0.784 (95% confidence interval [CI], 0.775-0.812) (EN) and AUC = 0.785 (95% CI, 0.759-0.812) (RSF). The additional application of DECT material decomposition did not improve the model's performance (EN, P = 0.594; RSF, P = 0.198). In the clinical benchmark, the top averaged AUC value of 0.643 (95% CI, 0.611-0.675) was inferior to the quantitative imaging-biomarker models ( P < 0.001). A combined imaging and clinical model did not improve the imaging-based models ( P > 0.101). Shape features revealed high prognostic importance.

CONCLUSIONS

Radiomics AI applications may be used for SCCHN survival prognostication, but the spectral information of DECT material decomposition did not improve the model's performance in our preliminary investigation.

Dual-Energy CT Iodine Uptake of Head and Neck: Definition of Reference Values in a Big Data Cohort

BACKGROUND

Despite a considerable amount of literature on dual-energy CT (DECT) iodine uptake of the head and neck, the physiologic iodine uptake of this region has not been defined yet. This study aims to establish reference values for the iodine uptake of healthy organs to facilitate clinical application.

METHODS

Consecutive venous DECT scans of the head and neck were reviewed, and unremarkable exams were included (n = 617). A total of 35 region of interest measurements were performed in 16 anatomical regions. Iodine uptake was compared among different organs/tissues and subgroup analysis was performed (male (n = 403) vs. female (n = 214); young (n = 207) vs. middle-aged (n = 206) vs. old (n = 204); and normal weight (n = 314) vs. overweight (n = 196) vs. obese (n = 107)).

RESULTS

Overall mean iodine uptake values ranged between 0.5 and 9.4 mg/mL. Women showed higher iodine concentrations in the cervical vessels and higher uptake for the parotid gland, masseter muscle, submandibular glands, sublingual glands, palatine tonsils, tongue body, thyroid gland, and the sternocleidomastoid muscle than men (p ≤ 0.04). With increasing age, intravascular iodine concentrations increased as well as iodine uptake for cerebellum and thyroid gland, while values for the tongue and palatine tonsils were lower compared to younger subjects (p ≤ 0.03). Iodine concentrations for parotid glands and sternocleidomastoid muscles decreased with a higher BMI (p ≤ 0.004), while normal-weighted patients showed higher iodine values inside the jugular veins, other cervical glands, and tonsils versus patients with a higher BMI (p ≤ 0.04).

CONCLUSION

physiologic iodine uptake values of cervical organs and tissues show gender-, age-, and BMI-related differences, which should be considered in the clinical routine of head and neck DECT.

Dual-Energy CT Material Decomposition: The Value in the Detection of Lymph Node Metastasis from Breast Cancer

PURPOSE

To evaluate the diagnostic performance of a dual-energy computed tomography (DECT)-based material decomposition algorithm for iodine quantification and fat fraction analysis to detect lymph node metastases in breast cancer patients.

MATERIALS AND METHODS

30 female patients (mean age, 63.12 ± 14.2 years) diagnosed with breast cancer who underwent pre-operative chest DECT were included. To establish a reference standard, the study correlated histologic repots after lymphadenectomy or confirming metastasis in previous/follow-up examinations. Iodine concentration and fat fraction were determined through region-of-interest measurements on venous DECT iodine maps. Receiver operating characteristic curve analysis was conducted to identify the optimal threshold for differentiating between metastatic and non-metastatic lymph nodes.

RESULTS

A total of 168 lymph nodes were evaluated, divided into axillary (metastatic: 46, normal: 101) and intramammary (metastatic: 10, normal: 11). DECT-based fat fraction values exhibited significant differences between metastatic (9.56 ± 6.20%) and non-metastatic lymph nodes (41.52 ± 19.97%) (p < 0.0001). Absolute iodine concentrations showed no significant differences (2.25 ± 0.97 mg/mL vs. 2.08 ± 0.97 mg/mL) (p = 0.7999). The optimal fat fraction threshold for diagnosing metastatic lymph nodes was determined to be 17.75%, offering a sensitivity of 98% and a specificity of 94%.

CONCLUSIONS

DECT fat fraction analysis emerges as a promising method for identifying metastatic lymph nodes, overcoming the morpho-volumetric limitations of conventional CT regarding lymph node assessment. This innovative approach holds potential for improving pre-operative lymph node evaluation in breast cancer patients, offering enhanced diagnostic accuracy.

The Value of Local Therapies in Advanced Adrenocortical Carcinoma

International guidelines recommend local therapies (LTs) such as local thermal ablation (LTA; radiofrequency, microwave, cryoablation), transarterial (chemo)embolisation (TA(C)E), and transarterial radioembolisation (TARE) as therapeutic options for advanced adrenocortical carcinoma (ACC). However, the evidence for these recommendations is scarce. We retrospectively analysed patients receiving LTs for advanced ACC. Time to progression of the treated lesion (tTTP) was the primary endpoint. The secondary endpoints were best objective response, overall progression-free survival, overall survival, adverse events, and the establishment of predictive factors by multivariate Cox analyses. A total of 132 tumoural lesions in 66 patients were treated with LTA (n = 84), TA(C)E (n = 40), and TARE (n = 8). Complete response was achieved in 27 lesions (20.5%; all of them achieved by LTA), partial response in 27 (20.5%), and stable disease in 38 (28.8%). For the LTA group, the median tTTP was not reached, whereas it was reached 8.3 months after TA(C)E and 8.2 months after TARE (p < 0.001). The median time interval from primary diagnosis to LT was >47 months. Fewer than four prior therapies and mitotane plasma levels of >14 mg/L positively influenced the tTTP. In summary, this is one of the largest studies on LTs in advanced ACC, and it demonstrates a very high local disease control rate. Thus, it clearly supports the guideline recommendations for LTs in these patients.

Incident fractures of the distal radius: Dual-energy CT-derived metrics for opportunistic risk stratification

BACKGROUND

Dual-energy CT (DECT)-derived bone mineral density (BMD) of the distal radius and other CT-derived metrics related to bone health have been suggested for opportunistic osteoporosis screening and risk evaluation for sustaining distal radius fractures (DRFs).

METHODS

The distal radius of patients who underwent DECT between 01/2016 and 08/2021 was retrospectively analyzed. Cortical Hounsfield Unit (HU), trabecular HU, cortical thickness, and DECT-based BMD were acquired from a non-fractured, metaphyseal area in all examinations. Receiver-operating characteristic (ROC) analysis was conducted to determine the area under the curve (AUC) values for predicting DRFs based on DECT-derived BMD, HU values, and cortical thickness. Logistic regression models were then employed to assess the associations of these parameters with the occurrence of DRFs.

RESULTS

In this study, 263 patients (median age: 52 years; interquartile range: 36-64; 132 women; 192 fractures) were included. ROC curve analysis revealed a higher area under the curve (AUC) value for DECT-derived BMD compared to cortical HU, trabecular HU, and cortical thickness (0.91 vs. 0.61, 0.64, and 0.69, respectively; p <.001). Logistic regression models confirmed the association between lower DECT-derived BMD and the occurrence of DRFs (Odds Ratio, 0.83; p <.001); however, no influence was observed for cortical HU, trabecular HU, or cortical thickness.

CONCLUSIONS

DECT can be used to assess the BMD of the distal radius without dedicated equipment such as calibration phantoms to increase the detection rates of osteoporosis and stratify the individual risk to sustain DRFs. In contrast, assessing HU-based values and cortical thickness does not provide clinical benefit.

AdaRes: A deep learning-based model for ultrasound image denoising: Results of image quality metrics, radiomics, artificial intelligence, and clinical studies

PURPOSE

The quality of ultrasound images is degraded by speckle and Gaussian noises. This study aims to develop a deep-learning (DL)-based filter for ultrasound image denoising.

METHODS

A novel DL-based filter using adaptive residual (AdaRes) learning was proposed. Five image quality metrics (IQMs) and 27 radiomics features were used to evaluate denoising results. The effect of our proposed filter, AdaRes, on four pre-trained convolutional neural network (CNN) classification models and three radiologists was assessed.

RESULTS

AdaRes filter was tested on both natural and ultrasound image databases. IQMs results indicate that AdaRes could remove noises in three different noise levels with the highest performances. In addition, a radiomics study proved that AdaRes did not distort tissue textures and it could preserve most radiomics features. AdaRes could also improve the performance classification using CNNs in different settings. Finally, AdaRes also improved the mean overall performance (AUC) of three radiologists from 0.494 to 0.702 in the classification of benign and malignant lesions.

CONCLUSIONS

AdaRes filtered out noises on ultrasound images more effectively and can be used as an auxiliary preprocessing step in computer-aided diagnosis systems. Radiologists may use it to remove unwanted noises and improve the ultrasound image quality before the interpretation.

Locoregional Therapies for Primary and Metastatic Breast Cancer: AJR Expert Panel Narrative Review

Minimally invasive locoregional therapies have a growing role in the multidisciplinary treatment of primary and metastatic breast cancer. Factors contributing to the expanding role of ablation for primary breast cancer include earlier diagnosis, when tumors are small, and increased longevity of patients whose condition precludes surgery. Cryoablation has emerged as the leading ablative modality for primary breast cancer owing to its wide availability, the lack of need for sedation, and the ability to monitor the ablation zone. Emerging evidence suggests that in patients with oligometastatic breast cancer, use of locoregional therapies to eradicate all disease sites may confer a survival advantage. Evidence also suggests that transarterial therapies-including chemoembolization, chemoperfusion, and radioembolization-may be helpful to some patients with advanced liver metastases from breast cancer, such as those with hepatic oligoprogression or those who cannot tolerate systemic therapy. However, the optimal modalities for treatment of oligometastatic and advanced metastatic disease remain unknown. Finally, locoregional therapies may produce tumor antigens that in combination with immunotherapy drive anti-tumor immunity. Although key trials are ongoing, additional prospective studies are needed to establish the inclusion of interventional oncology in societal breast cancer guidelines to support further clinical adoption and improved patient outcomes.

Indicators for Hospitalization in Acute Pulmonary Embolism: Uncover the Association Between D-dimer Levels, Thrombus Volume and Radiomics

BACKGROUND

The advent of advanced computed tomography (CT) technology and the field of radiomics has opened up new avenues in diagnostic assessments. Increasingly, there is substantial evidence advocating for the incorporation of quantitative imaging biomarkers in the clinical decision-making process. This study aimed to examine the correlation between D-dimer levels and thrombus size in acute pulmonary embolism (PE) combining dual-energy CT (DECT) and radiomics and to investigate the diagnostic utility of a machine learning classifier based on dual-energy computed tomography (DECT) radiomics for identifying patients with a complicated course, defined as at least hospitalization at IMC.

METHODS

The study was conducted including 136 participants who underwent pulmonary artery CT angiography from January 2015 to March 2022. Based on DECT imaging, 107 radiomic features were extracted for each patient using standardized image processing. After dividing the dataset into training and test sets, stepwise feature reduction based on reproducibility, variable importance and correlation analyses were performed to select the most relevant features; these were used to train and validate the gradient-boosted tree models.Receiver operating characteristics (ROC) analysis was utilized to evaluate the association between volumetric, laboratory data and adverse outcomes.

RESULTS

In the central PE group, we observed a significant correlation between thrombus volumetrics and D-dimer levels (p = 0.0037), as well as between thrombus volumetrics and hospitalization at the Intermediate Care Unit (IMC) (p = 0.0001). In contrast, no statistically significant differences were identified in thrombus sizes between patients who experienced complications and those who had a favorable course (p = 0.3162). The trained machine learning classifier achieved an accuracy of 61% and 55% in identifying patients with a complicated course, as indicated by an area under the ROC curve of 0.63 and 0.58.

CONCLUSION

In conclusion, our findings indicate a positive correlation between D-dimer levels and central PE's pulmonary embolic burden. Thrombus volumetrics may serve as an indicator for complications and outcomes in acute PE patients. Thus, thrombus volumetrics, as opposed to D-dimers, could be an additional marker for evaluating embolic disease severity. Moreover, DECT-derived radiomic feature models show promise in identifying patients with a complicated course, such as hospitalization at IMC.

Diagnostic performance of modern computed tomography in cruciate ligament injury detection: A comprehensive study

BACKGROUND

This study aimed to evaluate the clinical utility of modern single and dual-energy computed tomography (CT) for assessing the integrity of the cruciate ligaments in patients that sustained acute trauma.

METHODS

Patients who underwent single- or dual-energy CT followed by 3 Tesla magnetic resonance imaging (MRI) or knee joint arthroscopy between 01/2016 and 12/2022 were included in this retrospective, monocentric study. Three radiologists specialized in musculoskeletal imaging independently evaluated all CT images for the presence of injury to the cruciate ligaments. An MRI consensus reading of two experienced readers and arthroscopy provided the reference standard. Diagnostic accuracy parameters and area under the receiver operator characteristic curve (AUC) were the primary metrics for diagnostic performance.

RESULTS

CT images of 204 patients (median age, 49 years; IQR 36 - 64; 113 males) were evaluated. Dual-energy CT yielded significantly higher diagnostic accuracy and AUC for the detection of injury to the anterior (94% [240/255] vs 75% [266/357] and 0.89 vs 0.66) and posterior cruciate ligaments (95% [243/255] vs 87% [311/357] and 0.90 vs 0.61) compared to single-energy CT (all parameters, p <.005). Diagnostic confidence and image quality were significantly higher in dual-energy CT compared to single-energy CT (all parameters, p <.005).

CONCLUSIONS

Modern dual-energy CT is readily available and can serve as a screening tool for detecting or excluding cruciate ligament injuries in patients with acute trauma. Accurate diagnosis of cruciate ligament injuries is crucial to prevent adverse outcomes, including delayed treatment, chronic instability, or long-term functional limitations.

Lightweight Techniques to Improve Generalization and Robustness of U-Net Based Networks for Pulmonary Lobe Segmentation

Lung lobe segmentation in chest CT is relevant to a wide range of clinical applications. However, existing segmentation pipelines often exhibit vulnerabilities and performance degradations when applied to external datasets. This is usually attributed to the size of the available dataset or model. We show that it is possible to enhance generalizability without huge resources by carefully curating the dataset and combining machine learning with medical expertise. Multiple machine learning techniques (self-supervision (SSL), attention (A), and data augmentation (DA)) are used to train a fast and fully-automated lung lobe segmentation model based on 2D U-Net. Our study involved evaluating these techniques on a diverse dataset collected under the RACOON project, encompassing 100 CT chest scans from patients with bacterial, viral, or SARS-CoV2 infections. We compare our model to a baseline U-Net trained on the same dataset. Our approach significantly improved segmentation accuracy (Dice score of 92.8% vs. 82.3%, p < 0.001). Moreover, our model achieved state-of-the-art performance (Dice score of 92.8% vs. 90.8% for the literature's state-of-the-art, p = 0.102) with reduced training examples (69 vs. 231 CT Scans). Among the techniques, data augmentation with expert knowledge displayed the most significant impact, enhancing the Dice score by +0.056. Notably, these enhancements are not limited to lobe segmentation but can be seamlessly integrated into various medical imaging segmentation tasks, demonstrating their versatility and potential for broader applications.

Machine-Learning-Aided Prediction of Brain Metastases Development in Non-Small-Cell Lung Cancers

PURPOSE

Non-small-cell lung cancer (NSCLC) shows a high incidence of brain metastases (BM). Early detection is crucial to improve clinical prospects. We trained and validated classifier models to identify patients with a high risk of developing BM, as they could potentially benefit from surveillance brain MRI.

METHODS

Consecutive patients with an initial diagnosis of NSCLC from January 2011 to April 2019 and an in-house chest-CT scan (staging) were retrospectively recruited at a German lung cancer center. Brain imaging was performed at initial diagnosis and in case of neurological symptoms (follow-up). Subjects lost to follow-up or still alive without BM at the data cut-off point (12/2020) were excluded. Covariates included clinical and/or 3D-radiomics-features of the primary tumor from staging chest-CT. Four machine learning models for prediction (80/20 training) were compared. Gini Importance and SHAP were used as measures of importance; sensitivity, specificity, area under the precision-recall curve, and Matthew's Correlation Coefficient as evaluation metrics.

RESULTS

Three hundred and ninety-five patients compromised the clinical cohort. Predictive models based on clinical features offered the best performance (tuned to maximize recall: sensitivity∼70%, specificity∼60%). Radiomics features failed to provide sufficient information, likely due to the heterogeneity of imaging data. Adenocarcinoma histology, lymph node invasion, and histological tumor grade were positively correlated with the prediction of BM, age, and squamous cell carcinoma histology were negatively correlated. A subgroup discovery analysis identified 2 candidate patient subpopulations appearing to present a higher risk of BM (female patients + adenocarcinoma histology, adenocarcinoma patients + no other distant metastases).

CONCLUSION

Analysis of the importance of input features suggests that the models are learning the relevant relationships between clinical features/development of BM. A higher number of samples is to be prioritized to improve performance. Employed prospectively at initial diagnosis, such models can help select high-risk subgroups for surveillance brain MRI.

Multiparametric Evaluation of Radiomics Features and Dual-Energy CT Iodine Maps for Discrimination and Outcome Prediction of Thymic Masses

RATIONALE AND OBJECTIVES

To investigate the diagnostic value of radiomics features and dual-source dual-energy CT (DECT) based material decomposition in differentiating low-risk thymomas, high-risk thymomas, and thymic carcinomas.

MATERIALS AND METHODS

This retrospective study included 32 patients (16 males, mean age 66 ± 14 years) with pathologically confirmed thymic masses who underwent contrast-enhanced DECT between 10/2014 and 01/2023. Two experienced readers evaluated all patients regarding conventional radiomics features, as well as DECT-based features, including attenuation (HU), iodine density (mg/mL), and fat fraction (%). Data comparisons were performed using analysis of variance and chi-square statistic tests. Receiver operating characteristic curve analysis and Cox-regression tests were used to discriminate between low-risk/high-risk thymomas and thymic carcinomas.

RESULTS

Of the 32 thymic tumors, 12 (38%) were low-risk thymomas, 11 (34%) were high-risk thymomas, and 9 (28%) were thymic carcinomas. Values differed significantly between low-risk thymoma, high-risk thymoma, and thymic carcinoma regarding DECT-based features (p ≤ 0.023) and 30 radiomics features (p ≤ 0.037). The area under the curve to differentiate between low-risk/high-risk thymomas and thymic cancer was 0.998 (95% CI, 0.915-1.000; p < 0.001) for the combination of DECT imaging parameters and radiomics features, yielding a sensitivity of 100% and specificity of 96%. During a follow-up of 60 months (IQR, 35-60 months), the multiparametric approach including radiomics features, DECT parameters, and clinical parameters showed an excellent prognostic power to predict all-cause mortality (c-index = 0.978 [95% CI, 0.958-0.998], p = 0.003).

CONCLUSION

A multiparametric approach including conventional radiomics features and DECT-based features facilitates accurate, non-invasive discrimination between low-risk/high-risk thymomas and thymic carcinomas.

Advanced biomedical imaging for accurate discrimination and prognostication of mediastinal masses

BACKGROUND

To investigate the potential of radiomic features and dual-source dual-energy CT (DECT) parameters in differentiating between benign and malignant mediastinal masses and predicting patient outcomes.

METHODS

In this retrospective study, we analysed data from 90 patients (38 females, mean age 51 ± 25 years) with confirmed mediastinal masses who underwent contrast-enhanced DECT. Attenuation, radiomic features and DECT-derived imaging parameters were evaluated by two experienced readers. We performed analysis of variance (ANOVA) and Chi-square statistic tests for data comparison. Receiver operating characteristic curve analysis and Cox regression tests were used to differentiate between mediastinal masses.

RESULTS

Of the 90 mediastinal masses, 49 (54%) were benign, including cases of thymic hyperplasia/thymic rebound (n = 10), mediastinitis (n = 16) and thymoma (n = 23). The remaining 41 (46%) lesions were classified as malignant, consisting of lymphoma (n = 28), mediastinal tumour (n = 4) and thymic carcinoma (n = 9). Significant differences were observed between benign and malignant mediastinal masses in all DECT-derived parameters (p ≤ .001) and 38 radiomic features (p ≤ .044) obtained from contrast-enhanced DECT. The combination of these methods achieved an area under the curve of .98 (95% CI, .893-1.000; p < .001) to differentiate between benign and malignant masses, with 100% sensitivity and 91% specificity. Throughout a follow-up of 1800 days, a multiparametric model incorporating radiomic features, DECT parameters and gender showed promising prognostic power in predicting all-cause mortality (c-index = .8 [95% CI, .702-.890], p < .001).

CONCLUSIONS

A multiparametric approach combining radiomic features and DECT-derived imaging biomarkers allows for accurate and noninvasive differentiation between benign and malignant masses in the anterior mediastinum.

NTRK fusion events and targeted treatment of advanced radioiodine refractory thyroid cancer

PURPOSE

Pathogenic fusion events involving neurotrophic receptor tyrosine kinase (NTRK) have been described in ~ 2% of differentiated thyroid cancer (DTC). The selective tropomyosin receptor kinase (TRK) inhibitors entrectinib and larotrectinib have been approved in a tumor agnostic manner based on phase 1/2 clinical trials. In a real-world setting at five referral centers, we aimed to describe the prevalence of NTRK gene fusions and the efficacy and safety of TRK inhibitor treatment for non-medullary, advanced thyroid cancer (TC).

METHODS

A total of 184 TC patients with testing for NTRK gene fusions were included. Progression-free survival (PFS) and overall survival (OS) probabilities were estimated using the Kaplan-Meier method in six patients with NTRK fusion-positive TC who underwent TRK inhibitor therapy.

RESULTS

8/184 (4%) patients harbored NTRK gene fusions. Six patients with radioiodine (RAI)-refractory TC harboring NTRK1 (n = 4) and NTRK3 (n = 2) gene fusions were treated with larotrectinib. Five patients (83%) had received ≥ 1 prior systemic therapy and one patient did not receive prior systemic therapy. All patients had morphologically progressive disease before treatment initiation. Objective response rate was 83%, including two complete remissions. Median PFS from start of TRK inhibitor treatment was 23 months (95% confidence interval [CI], 0-57.4) and median OS was not reached (NR) (95% CI, NR). Adverse events were of grade 1-3.

CONCLUSION

The prevalence of NTRK gene fusions in our cohort of RAI-refractory TC is slightly higher than reported for all TC patients. Larotrectinib is an effective treatment option in the majority of NTRK gene fusion-positive advanced TC patients after prior systemic treatment and has a favorable safety profile.

Degradable Starch Microspheres Transarterial Chemoembolization with or without Lipiodol for Liver Metastases from Pancreatic Cancer: A Prospective Randomized Trial

To evaluate and compare the outcome of patients with liver metastases from pancreatic cancer treated by transarterial chemoembolization (TACE) using two different protocols. In this prospective, randomized, single-center trial, patients were randomly assigned to receive TACE therapy either with degradable starch microspheres (DSM) alone or a combination of Lipiodol and DSM. From the initial 58 patients, 26 patients (13 DSM-TACE, 13 Lipiodol + DSM-TACE) who completed 3 TACE treatments at an interval of four weeks were considered for evaluation of tumor responses. Initial and final MRIs were used to evaluate local therapy response by RECIST 1.1; changes in diameter, volume, ADC value, and survival rate were statistically evaluated. The differences between the DSM-TACE and Lipiodol + DSM-TACE were identified for partial response (PR) as 15.4% versus 53.8%, stable disease (SD) as 69.2% versus 46.2%, progressive disease (PD) as 15.4% versus 0%, respectively (p = 0.068). Median overall survival times for DSM-TACE and Lipiodol + DSM-TACE were 20 months (95% CI, 18.1-21.9) and 23 months (95% CI, 13.8-32.2), respectively (p = 0.565). The one-year survival rates for DSM-TACE and Lipiodol + DSM-TACE were 85.4% and 60.4%, the two-year survival rates were 35.9% and 47.7%, and the three-year survival rates were 12% and 30.9%, respectively. The evaluated local therapy response by RECIST 1. was not significantly different between the two studied groups. A longer overall survival time was observed after Lipiodol + DSM-TACE therapy; however, it was not significantly different.

Combination Therapy of Bland Transarterial Embolization and Microwave Ablation for Hepatocellular Carcinoma within the Milan Criteria Leads to Significantly Higher Overall Survival

A comparison of the combination therapy consisting of microwave ablation (MWA) after bland lipiodol-based transarterial embolization (TAE) with MWA alone in the treatment of hepatocellular carcinoma (HCC) within the Milan criteria. Forty-nine patients in the TAE-MWA group (12 women and 37 men; mean age: 63.3 ± 9.6 years) with 55 tumors and 63 patients in the MWA group (18 women and 45 men; mean age: 65.9 ± 10.5 years) with 67 tumors were retrospectively enrolled in this study. For the investigation of treatment protocols based upon both safety and efficacy, patients' cases were analyzed with regard to complications, local tumor progression (LTP), intrahepatic distant recurrence (IDR), overall survival (OS), and progression-free survival (PFS). There were no cases of major complications in either group. The LTP rate was 5.5% in the MWA-TAE group and 7.5% in the MWA group (p = 0.73). The rate of IDR was 42.9% in the MWA-TAE group and 52.4% in the MWA group (p = 0.42). The 12-, 24-, and 36-month OS rates starting at the date of tumor diagnosis were 97.7%, 85.1%, and 78.8% in the TAE-MWA group, and 91.9%, 71.4%, and 59.8% in the MWA group, respectively (p = 0.004). The 6-, 12-, and 24-month PFS rates were 76.5%, 55%, and 44.6% in the TAE-MWA group, and 74.6%, 49.2%, and 29.6% in the MWA group, respectively (p = 0.18). The combination therapy of TAE-MWA was significantly superior to MWA monotherapy according to OS in treating HCC within the Milan criteria.

Unveiling the diagnostic enigma of D-dimer testing in cancer patients: Current evidence and areas of application

BACKGROUND

Cancer is a well-known risk factor for venous thromboembolism (VTE). A combined strategy of D-dimer testing and clinical pre-test probability is usually used to exclude VTE. However, its effectiveness is diminished in cancer patients due to reduced specificity, ultimately leading to a decreased clinical utility. This review article seeks to provide a comprehensive summary of how to interpret D-dimer testing in cancer patients.

METHODS

In accordance with PRISMA standards, literature pertaining to the diagnostic and prognostic significance of D-dimer testing in cancer patients was carefully chosen from reputable sources such as PubMed and the Cochrane databases.

RESULTS

D-dimers have not only a diagnostic value in ruling out VTE but can also serve as an aid for rule-in if their values exceed 10-times the upper limit of normal. This threshold allows a diagnosis of VTE in cancer patients with a positive predictive value of more than 80%. Moreover, elevated D-dimers carry important prognostic information and are associated with VTE reoccurrence. A gradual increase in risk for all-cause death suggests that VTE is also an indicator of biologically more aggressive cancer types and advanced cancer stages. Considering the lack of standardization for D-dimer assays, it is essential for clinicians to carefully consider the variations in assay performance and the specific test characteristics of their institution.

CONCLUSIONS

Standardizing D-dimer assays and developing modified pretest probability models specifically for cancer patients, along with adjusted cut-off values for D-dimer testing, could significantly enhance the accuracy and effectiveness of VTE diagnosis in this population.

Comparison of radiomics models and dual-energy material decomposition to decipher abdominal lymphoma in contrast-enhanced CT

PURPOSE

The radiologists' workload is increasing, and computational imaging techniques may have the potential to identify visually unequivocal lesions, so that the radiologist can focus on equivocal and critical cases. The purpose of this study was to assess radiomics versus dual-energy CT (DECT) material decomposition to objectively distinguish visually unequivocal abdominal lymphoma and benign lymph nodes.

METHODS

Retrospectively, 72 patients [m, 47; age, 63.5 (27-87) years] with nodal lymphoma (n = 27) or benign abdominal lymph nodes (n = 45) who had contrast-enhanced abdominal DECT between 06/2015 and 07/2019 were included. Three lymph nodes per patient were manually segmented to extract radiomics features and DECT material decomposition values. We used intra-class correlation analysis, Pearson correlation and LASSO to stratify a robust and non-redundant feature subset. Independent train and test data were applied on a pool of four machine learning models. Performance and permutation-based feature importance was assessed to increase the interpretability and allow for comparison of the models. Top performing models were compared by the DeLong test.

RESULTS

About 38% (19/50) and 36% (8/22) of the train and test set patients had abdominal lymphoma. Clearer entity clusters were seen in t-SNE plots using a combination of DECT and radiomics features compared to DECT features only. Top model performances of AUC = 0.763 (CI = 0.435-0.923) were achieved for the DECT cohort and AUC = 1.000 (CI = 1.000-1.000) for the radiomics feature cohort to stratify visually unequivocal lymphomatous lymph nodes. The performance of the radiomics model was significantly (p = 0.011, DeLong) superior to the DECT model.

CONCLUSIONS

Radiomics may have the potential to objectively stratify visually unequivocal nodal lymphoma versus benign lymph nodes. Radiomics seems superior to spectral DECT material decomposition in this use case. Therefore, artificial intelligence methodologies may not be restricted to centers with DECT equipment.

Association of Phantomless Dual-Energy CT-based Volumetric Bone Mineral Density with the Prevalence of Acute Insufficiency Fractures of the Spine

RATIONALE AND OBJECTIVES

To evaluate the bone mineral density (BMD) of the lumbar spine derived from dual-energy CT (DECT)-based volumetric material decomposition and its association with acute insufficiency fractures of the thoracolumbar spine.

MATERIALS AND METHODS

L1 of 160 patients (77 men, 83 women; mean age 64.3 years, range, 22-94 years) who underwent third-generation dual-source DECT between January 2016 and December 2021 due to suspected insufficiency fractures was retrospectively analyzed. All depicted vertebrae were examined for signs of recent fractures. A dedicated DECT postprocessing software using material decomposition was applied for phantomless BMD assessment. Receiver-operating characteristic (ROC) analysis identified optimal BMD thresholds. Associations of BMD, sex, and age with the occurrence of insufficiency fractures were examined with logistic regression models.

RESULTS

A DECT-derived BMD threshold of 120.40 mg/cm³ yielded 90.1% specificity and 59.32% sensitivity to differentiate patients with at least one insufficiency fracture from patients without fracture. No patient without fracture had a DECT-derived BMD below 85 mg/cm3. Lower DECT-derived bone mineral density was associated with an increased risk of insufficiency fractures (Odds ratio of 0.93, 95% CI, 0.91-0.96, p < 0.001). Overall ROC-derived AUC was 0.82 (p < 0.0001) for the differentiation of patients that sustained an insufficiency fracture from the control group.

CONCLUSION

Dual-Energy CT-based BMD assessment can accurately differentiate patients with acute insufficiency fractures of the thoracolumbar spine from patients without fracture. This algorithm can be used for phantomless risk stratification of patients undergoing routine CT to sustain insufficiency fractures of the thoracolumbar spine The identified cut-off value of 120.4 mg/cm³ is in line with current American College of Radiology (ACR) recommendations to differentiate healthy individuals from those with reduced bone mineral density.

Diagnostic value of DECT-based colored collagen maps for the assessment of cruciate ligaments in patients with acute trauma

OBJECTIVES

The purpose of this study was to evaluate the diagnostic accuracy of third-generation dual-source dual-energy CT (DECT) color-coded collagen reconstructions for the assessment of the cruciate ligaments compared to standard grayscale image reconstruction.

METHODS

Patients who underwent third-generation dual-source DECT followed by either 3-T MRI or arthroscopy of the knee joint within 14 days between January 2016 and December 2021 were included in this retrospective study. Five radiologists independently evaluated conventional grayscale DECT for the presence of injury to the cruciate ligaments; after 4 weeks, readers re-evaluated the examinations using grayscale images and color-coded collagen reconstructions. A reference standard for MRI was provided by a consensus reading of two experienced readers and arthroscopy. Sensitivity and specificity were the primary metrics of diagnostic performance.

RESULTS

Eighty-five patients (mean age, 44 years ± 16; 50 male) with injury to the ACL or PCL (n = 31) were ultimately included. Color-coded collagen reconstructions significantly increased overall sensitivity (94/105 [90%] vs. 67/105 [64%]), specificity (248/320 [78%] vs. 215/320 [67%]), PPV (94/166 [57%] vs. 67/162 [39%]), NPV (248/259 [96%] vs. 215/253 [85%]), and accuracy (342/425 [81%] vs. 282/425 [66%]) for the detection of injury to the anterior cruciate ligament (all parameters, p < .001). For injury to the posterior cruciate ligament, diagnostic accuracy increased for complete tears (p < .001). Color-coded collagen reconstructions achieved superior diagnostic confidence, image quality, and noise scores compared to grayscale CT (all parameters, p < .001) and showed good agreement with MRI examinations.

CONCLUSIONS

DECT-derived color-coded collagen reconstructions yield substantially higher diagnostic accuracy and confidence for assessing the integrity of the cruciate ligaments compared to standard grayscale CT in patients with acute trauma.

KEY POINTS

• Color-coded collagen reconstructions derived from dual-energy CT yield substantially higher diagnostic accuracy and confidence for the assessment of the cruciate ligaments compared to standard grayscale CT in patients with acute trauma. • Color-coded collagen reconstructions demonstrate good agreement with MRI for the assessment cruciate ligament injury. • Dual-energy CT may serve as a readily available screening approach for patients with acute trauma to the knee when injury to the cruciate ligaments is suspected.

Coil embolization of a fistula from the right inferior phrenic artery to the right pulmonary artery with involvement of further arteries: A rare case report

A 51-year-old female patient was presenting dyspnea for more than a year with no previous lung infections or surgery. Initially, a diagnostic computed tomography was made, showing a rare arterio-arterial malformation between the right inferior phrenic and right pulmonary artery leading into a vascular bundle in the middle lung lobe. Due to the patients' dyspnea and massive extent of malformation, the indication for transcatheter arterial embolization was made. The first transcatheter arterial embolization procedure involved the inferior phrenic and a selective branch of the internal thoracic artery. Interventional angiography as well as computed tomography revealed further extend of the malformation showing a connection of right lateral thoracic, hepatic, and inferior epigastric artery to the fistula. After one month, a second transcatheter arterial embolization of these arteries as well as a second approach of the proximal internal thoracic artery was performed. In the follow-up the patient described a substantial improvement of her dyspnea and showed no signs of infections. A phrenic artery to pulmonary artery fistula is an extremely rare case occurring congenital or acquired. Patients may be asymptomatic or present, among others, dyspnea, hemoptysis, pulmonary infections and congestive heart failure. Symptomatic patients require treatment using transcatheter arterial embolization or surgical resection. The patient had dyspnea and a substantial extent of malformation with possibly complicated clinical course. The recommended less invasive treatment using transcatheter arterial embolization was successfully performed. In conclusion, our patient represented a rare congenital case of systemic and pulmonary artery communication, which we were able to treat sufficiently with coil embolization.

Ankle Joint MRI-Comparison of Image Quality and Effect of Sports-Related Stress

OBJECTIVES

The main aims of the study were the evaluation of stress-related effects (strenuous vs. non-strenuous sport vs. nonathletes) in stimulating or reducing influences on cartilage volume in the ankle joint and the evaluation of the image quality of a magnetic resonance imaging (MRI) device with a field strength of 3.0 Tesla compared to one of 1.5 Tesla.

METHODS

A total of 15 subjects (6 male, 9 female) aged 19-33 years participated voluntarily in this prospective study. The subjects were divided into three groups: high-performance athletes of the German Football Association (DFB) (football/soccer = strenuous sport), high-performance athletes of the German Swimming Association (DSV) (swimming = non-strenuous sport), and nonathletes. MRI was performed on both ankle joints of all subjects in the 1.5 T and 3.0 T MRI scanners using survey sequences, proton density sequences in the coronal and sagittal planes, and VIBE sequences. Using the images of both feet produced by VIBE sequences, the cartilages of the talus and tibia were manually circumscribed using a computer mouse in every third layer, and the volume was calculated. For qualitative assessment, blinded images were submitted to three radiologists with defined standards. The images were scored using a scale from 1 to 5.

RESULTS

Cartilage volume: The investigation and examination of the individual cartilage volumes by analysis of variance (ANOVA) showed no significant differences among the three groups. The effect intensities, as calculated by Cohen's d, were right tibia (Tiri) = 2.5, left tibia (Tile) = 2.2, right talus (Tari) = 1.9, and left talus (Tale) = 1.6 in the strenuous sport versus nonstrenuous sport groups; Tiri = 0.8, Tile = 1.2, Tari = 0.4, and Tale = 0.5 in the strenuous sport versus nonathlete groups; and Tiri = 0.3, Tile = 0.2, Tari = 0.7, and Tale = 0.5 in the nonstrenuous sport versus nonathlete groups. Device comparison: In the investigation of each evaluated area on the 1.5 T and 3.0 T MR images by the Wilcoxon matched-pair test, significant differences were found for the cartilage-bone border (KKG = 0.002), cancellous bone (Sp = 0.001), medial ligamentous apparatus (mBa = 0.001), lateral ligamentous apparatus (lBa = 0.001), and adipose tissue (Fg = 0.002). Thus, there were significant differences in the assessment of the 1.5 T MRI and the 3.0 T MRI in all five evaluated areas.

CONCLUSION

The study showed no significant difference in the volume of hyaline articular cartilage in the upper ankle joint among the high-performance strenuous DFB athlete, high-performance non-strenuous DSV athlete, and nonathlete groups. The 3.0 Tesla device offers significant advantages in image quality compared to the 1.5 Tesla device.

Improved Coronary Artery Visualization Using Virtual Monoenergetic Imaging from Dual-Layer Spectral Detector CT Angiography

Background: To evaluate if coronary CT angiography (CCTA) monoenergetic reconstructions, obtained with a dual-layer spectral detector computed tomography (DLCT) system, offer improved image quality compared with 120 kVp conventional images without affecting the quantitative assessment of coronary stenoses. Methods: Fifty CCTA datasets (30 men; mean age: 61.6 ± 12.3 years) acquired with a DLCT system were reconstructed using virtual monoenergetic images (VMI) from 40 to 100 keV with 10 keV increment and compared with conventional images. An analysis of objective image quality was performed, evaluating the signal- and contrast-to-noise ratio. For the subjective assessment, two readers used a 5-point Likert scoring system to evaluate sharpness, noise, demarcation of coronary plaques, vascular contrast, and an overall score. Furthermore, coronary stenoses were analyzed for each vessel to describe the diagnostic agreement between monoenergetic images and conventional images. Results: The objective image analysis showed that all reconstructions from 70 keV to 40 keV show higher SNR (from 61.33 ± 12.46 to 154.22 ± 42.91, respectively) and CNR (from 51.45 ± 11.19 to 135.63 ± 39.38, respectively) compared with conventional images (all p < 0.001). The 40 keV monoenergetic images obtained the best average score for sharpness, vascular contrast, and for the overall impression (all with p < 0.001). The detection and grading of stenoses of the coronary arteries with conventional and monoenergetic images at 70 keV and 40 keV showed an overall excellent interobserver agreement (k= 0.81 [0.72-0.91]). Conclusions: The 40 keV virtual monoenergetic images obtained with a DLCT system allow the objective and subjective image quality of coronary CT angiography to be improved.

Dual-Energy CT-based Opportunistic Volumetric Bone Mineral Density Assessment of the Distal Radius

Background In patients with distal radius fractures (DRFs), low bone mineral density (BMD) is associated with bone substitute use during surgery and bone nonunion, but BMD information is not regularly available. Purpose To evaluate the feasibility of dual-energy CT (DECT)-based BMD assessment from routine examinations in the distal radius and the relationship between the obtained BMD values, the occurrence of DRFs, bone nonunion, and use of surgical bone substitute. Materials and Methods Scans in patients who underwent routine dual-source DECT in the distal radius between January 2016 and December 2021 were retrospectively acquired. Phantomless BMD assessment was performed using the delineated trabecular bone of a nonfractured segment of the distal radius and both DECT image series. CT images and health records were examined to determine fracture severity, surgical management, and the occurrence of bone nonunion. Associations of BMD with the occurrence of DRFs, bone nonunion, and bone substitute use at surgical treatment were examined with generalized additive models and receiver operating characteristic analysis. Results This study included 263 patients (median age, 52 years; IQR, 36-64 years; 132 female patients), of whom 192 were diagnosed with fractures. Mean volumetric BMD was lower in patients who sustained a DRF (93.9 mg/cm3 vs 135.4 mg/cm3; P < .001), required bone substitutes (79.6 mg/cm3 vs 95.5 mg/cm3; P < .001), and developed bone nonunion (71.1 mg/cm3 vs 96.5 mg/cm3; P < .001). Receiver operating characteristic curve analysis identified these patients with an area under the curve of 0.71-0.91 (P < .001). Lower BMD increased the risk to sustain DRFs, develop bone nonunion, and receive bone substitutes at surgery (P < .001). Conclusion DECT-based BMD assessment at routine examinations is feasible and could help predict surgical bone substitute use and the occurrence of bone nonunion in patients with DRFs. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Carrino in this issue.

Virtual Non-Contrast Spectral CT in Renal Masses: Is It Time to Discard Conventional Unenhanced Phase?

Dual-layer Dual-Energy CT (dl-DECT) allows one to create virtual non-contrast (VNC) reconstructions from contrast-enhanced CT scans, with a consequent decrease of the radiation dose. This study aims to assess the reliability of VNC for the diagnostic evaluation of renal masses in comparison with true non-contrast (TNC) images. The study cohort included 100 renal masses in 40 patients who underwent dl-DECT between June and December 2021. Attenuation values and standard deviations were assessed through the drawing of regions of interest on TNC and VNC images reconstructed from corticomedullary and nephrographic phases. A Wilcoxon signed-rank test was performed in order to assess equivalence of data and Spearman's Rho correlation coefficient to evaluate correlations between each parameter. The diagnostic accuracy of VNC was estimated through the performance of receiver operating characteristic (ROC) curve analysis. Differences between attenuation values were, respectively, 74%, 18%, 5% and 3% (TNC-VNC_cort), and 74%, 15%, 9% and 2% (TNC-VNC_neph). The Wilcoxon signed-rank test demonstrated the equivalence of attenuation values between the TNC and VNC images. The diagnostic performance of VNC images in the depiction of kidney simple cysts remains high compared to TNC (VNC_cort-AUC: 0.896; VNC_neph-AUC: 0.901, TNC-AUC: 0.903). In conclusion, quantitative analysis of attenuation values showed a strong agreement between VNC and TNC images in the evaluation of renal masses.

Intravascular Treatment Techniques for Locoregional Therapies of Lung Tumors

BACKGROUND

Lung cancer incidence has greatly increased over the past century. Moreover, the lung is the most common site of metastatic involvement. Despite improvements in the diagnosis and treatment of lung malignancies, patient prognosis is still unsatisfactory. Locoregional chemotherapeutic techniques for the treatment of lung malignancies are the current focus of research. The aim of this review article is to present different locoregional intravascular techniques and their treatment principles and to assess the pros and cons of each of them as a palliative and neoadjuvant treatment method in the treatment of lung malignancy.

METHOD

The different methods for the treatment of malignant lung lesions such as isolated lung perfusion (ILP), selective pulmonary artery perfusion (SPAP), transpulmonary chemoembolization (TPCE), bronchial artery infusion (BAI), bronchioarterial chemoembolization (BACE), and intraarteriel chemoperfusion (IACP) are evaluated comparatively.

RESULTS

Locoregional intravascular chemotherapy procedures are proving to be promising treatment options in the management of malignant lung tumors. In order to achieve optimal results, the locoregional technique should be used to achieve the highest possible uptake of the chemotherapeutic agent into the target tissue with rapid systemic clearance.

CONCLUSION

Among the various treatment options for lung malignancies, TPCE is the best evaluated treatment concept. However, further studies are necessary to define the optimal treatment concept with the best clinical outcomes.

KEY POINTS

· There are various intravascular chemotherapy methods for the treatment of lung malignancies.. · Transpulmonary chemoembolization (TPCE) is currently the most extensively evaluated treatment method for lung malignancies.. · Thermoablation after neoadjuvant chemoperfusion is a promising therapy for treating lung malignancies..

CITATION FORMAT

· Vogl TJ, Mekkawy A, Thabet DB. Intravascular Treatment Techniques for Locoregional Therapies of Lung Tumors. Fortschr Röntgenstr 2023; 195: 579 - 585.

Dual-Energy CT in Cardiothoracic Imaging: Current Developments

This article describes the technical principles and clinical applications of dual-energy computed tomography (DECT) in the context of cardiothoracic imaging with a focus on current developments and techniques. Since the introduction of DECT, different vendors developed distinct hard and software approaches for generating multi-energy datasets and multiple DECT applications that were developed and clinically investigated for different fields of interest. Benefits for various clinical settings, such as oncology, trauma and emergency radiology, as well as musculoskeletal and cardiovascular imaging, were recently reported in the literature. State-of-the-art applications, such as virtual monoenergetic imaging (VMI), material decomposition, perfused blood volume imaging, virtual non-contrast imaging (VNC), plaque removal, and virtual non-calcium (VNCa) imaging, can significantly improve cardiothoracic CT image workflows and have a high potential for improvement of diagnostic accuracy and patient safety.

Virtual monoenergetic dual-layer dual-energy CT images in colorectal cancer: CT diagnosis could be improved?

PURPOSE

To compare conventional CT images and virtual monoenergetic images (VMI) at dual-layer dual-energy CT (dlDECT) in patients with colorectal cancer (CRC) through quantitative analysis and to investigate the added value of VMI.

MATERIAL AND METHODS

Sixty-six consecutive patients with histologically documented CRC and available VMI reconstructions were retrospectively investigated. Subsequently, forty-two patients, without any colonic disease at colonoscopy, were selected as control group. Conventional CT images and VMI reconstructions at energy levels ranging from 40 (VMI₄₀) to 100 keV (VMI₁₀₀) in 10 keV increments, were obtained from the late arterial phase. First, signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were obtained to select the best VMI reconstruction. Finally, the diagnostic accuracy of conventional CT and VMI₄₀ in late arterial phase was evaluated.

RESULTS

On quantitative analysis, SNR and CNR were higher for VMI₄₀ (19.5 ± 7.7 and 11.8 ± 6.2, respectively) with statistically significant differences compared to conventional CT (P < 0.05) and all the other VMI reconstructions (P < 0.05), except for VMI₅₀ (P > 0.05). The addition of VMI₄₀ to conventional CT images significantly improved the area under the curve (AUC) for the diagnosis of CRC, increasing it from 0.875 to 0.943 for reader 1 (P < 0.05) and from 0.916 to 0.954 for reader 2 (P < 0.05). The improvement was greater in the less experienced radiologist (0.068) compared to the more experienced one (0.037).

CONCLUSION

VMI₄₀ has showed the highest quantitative image parameters. Furthermore, the use of VMI₄₀ can lead to a significant improvement in the diagnostic performance for detecting CRC.

Correlation of background parenchymal enhancement on breast MRI with breast cancer

AIM

To evaluate the prognostic value of background parenchymal enhancement (BPE) in breast magnetic resonance imaging (MRI) in women referred to radiological department as a high risk for breast cancer.

MATERIALS AND METHODS

A retrospective, cross-sectional study included 327 consecutive patients (mean age: 60 years, age range: 30-90 years) who underwent breast MRI and tissue biopsy between 2007 and 2016. All MRI images (T1, T2, and subtraction images) were evaluated visually. The relationship of BPE with patient age, fibroglandular tissue (FGT), Breast Imaging Reporting and Data System (BIRADS) categories, presence of breast cancer, and expression of human epidermal growth factor receptor 2 (HER2), progesterone receptor (PR), oestrogen receptor (ER), and Ki67 were analysed. Furthermore, all variables were correlated with pre- and postmenopausal status.

RESULTS

BPE of bilateral breast showed a weak correlation with FGT (right BPE: r=-0.14, p=0.004; left BPE: r=0.16, p=0.003), a weak negative correlation with patient age (right BPE: r=-0.14, p=0.007; left BPE: r=-0.15, p=0.006), and significant correlation with HER2 (right BPE, p=0.02), left BPE with HER2 was not significant. Among the correlations between BPE and BIRADS, only between right BPE and right BIRADS was significant (p=0.031). No clear evidence of an association between breast MRI BPE and breast cancer in premenopausal and postmenopausal status was observed, and no difference was found between the right and left breasts.

CONCLUSIONS

The results of the present study showed no significant correlations between BPE and breast cancer. In addition, there was no significant difference between the right and left breast. Hence, BPE of MRI may not be a reliable biomarker of breast cancer development.

Radiomics for therapy-specific head and neck squamous cell carcinoma survival prognostication (part I)

BACKGROUND

Treatment plans for squamous cell carcinoma of the head and neck (SCCHN) are individually decided in tumor board meetings but some treatment decision-steps lack objective prognostic estimates. Our purpose was to explore the potential of radiomics for SCCHN therapy-specific survival prognostication and to increase the models' interpretability by ranking the features based on their predictive importance.

METHODS

We included 157 SCCHN patients (male, 119; female, 38; mean age, 64.39 ± 10.71 years) with baseline head and neck CT between 09/2014 and 08/2020 in this retrospective study. Patients were stratified according to their treatment. Using independent training and test datasets with cross-validation and 100 iterations, we identified, ranked and inter-correlated prognostic signatures using elastic net (EN) and random survival forest (RSF). We benchmarked the models against clinical parameters. Inter-reader variation was analyzed using intraclass-correlation coefficients (ICC).

RESULTS

EN and RSF achieved top prognostication performances of AUC = 0.795 (95% CI 0.767-0.822) and AUC = 0.811 (95% CI 0.782-0.839). RSF prognostication slightly outperformed the EN for the complete (ΔAUC 0.035, p = 0.002) and radiochemotherapy (ΔAUC 0.092, p < 0.001) cohort. RSF was superior to most clinical benchmarking (p ≤ 0.006). The inter-reader correlation was moderate or high for all features classes (ICC ≥ 0.77 (± 0.19)). Shape features had the highest prognostic importance, followed by texture features.

CONCLUSIONS

EN and RSF built on radiomics features may be used for survival prognostication. The prognostically leading features may vary between treatment subgroups. This warrants further validation to potentially aid clinical treatment decision making in the future.

Diagnosis of Metastatic Lymph Nodes in Patients With Papillary Thyroid Cancer: A Comparative Multi-Center Study of Semantic Features and Deep Learning-Based Models

OBJECTIVES

Deep learning algorithms have shown potential in streamlining difficult clinical decisions. In the present study, we report the diagnostic profile of a deep learning model in differentiating malignant and benign lymph nodes in patients with papillary thyroid cancer.

METHODS

An in-house deep learning-based model called "ClymphNet" was developed and tested using two datasets containing ultrasound images of 195 malignant and 178 benign lymph nodes. An expert radiologist also viewed these ultrasound images and extracted qualitative imaging features used in routine clinical practice. These signs were used to train three different machine learning algorithms. Then the deep learning model was compared with the machine learning models on internal and external validation datasets containing 22 and 82 malignant and 20 and 76 benign lymph nodes, respectively.

RESULTS

Among the three machine learning algorithms, the support vector machine model (SVM) outperformed the best, reaching a sensitivity of 91.35%, specificity of 88.54%, accuracy of 90.00%, and an area under the curve (AUC) of 0.925 in all cohorts. The ClymphNet performed better than the SVM protocol in internal and external validation, achieving a sensitivity of 93.27%, specificity of 92.71%, and an accuracy of 93.00%, and an AUC of 0.948 in all cohorts.

CONCLUSION

A deep learning model trained with ultrasound images outperformed three conventional machine learning algorithms fed with qualitative imaging features interpreted by radiologists. Our study provides evidence regarding the utility of ClymphNet in the early and accurate differentiation of benign and malignant lymphadenopathy.

Correlation of mean apparent diffusion coefficient (ADC) and maximal standard uptake value (SUVmax) evaluated by diffusion-weighted MRI and 18F-FDG-PET/CT in children with Hodgkin lymphoma: a feasibility study

BACKGROUND

The objective was to analyse if magnetic resonance imaging (MRI) can act as a non-radiation exposure surrogate for (18)F-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in children with histologically confirmed Hodgkin lymphoma (HL) before treatment. This was done by analysing a potential correlation between apparent diffusion coefficient (ADC) in MRI and the maximum standardized uptake value (SUVmax) in FDG-PET/CT.

PATIENTS AND METHODS

Seventeen patients (six female, eleven male, median age: 16 years, range: 12-20 years) with histologically confirmed HL were retrospectively analysed. The patients underwent both MRI and (18)F-FDG PET/CT before the start of treatment. (18)F-FDG PET/CT data and correlating ADC maps in MRI were collected. For each HL-lesion two readers independently evaluated the SUVmax and correlating meanADC.

RESULTS

The seventeen patients had a total of 72 evaluable lesions of HL and there was no significant difference in the number of lesions between male and female patients (median male: 15, range: 12-19 years, median female: 17 range: 12-18 years, p = 0.021). The mean duration between MRI and PET/CT was 5.9 ± 5.3 days. The inter-reader agreement as assessed by the intraclass correlation coefficient (ICC) was excellent (ICC = 0.98, 95% CI: 0.97-0.99). The correlated SUVmax and meanADC of all 17 patients (ROIs n = 72) showed a strong negative correlation of -0.75 (95% CI: -0.84, - -0.63, p = 0.001). Analysis revealed a difference in the correlations of the examination fields. The correlated SUVmax and meanADC showed a strong correlation at neck and thoracal examinations (neck: -0.83, 95% CI: -0.93, - -0.63, p < 0.0001, thoracal: -0.82, 95% CI: -0.91, - -0.64, p < 0.0001) and a fair correlation at abdominal examinations of -0.62 (95% CI: -0.83, - -0.28, p = 0.001).

CONCLUSIONS

SUVmax and meanADC showed a strong negative correlation in paediatric HL lesions. The assessment seemed robust according to inter-reader agreements. Our results suggest that ADC maps and meanADC have the potential to replace PET/CT in the analysis of disease activity in paediatric Hodgkin lymphoma patients. This may help reduce the number of PET/CT examinations and decrease radiation exposure to children.

Injury patterns of the spine following blunt trauma: A per-segment analysis of spinal structures and their detection rates in CT and MRI

Rationale and objectives

To provide a detailed analysis of injury patterns of the spine following blunt trauma and establish the role of supplementary MRI by evaluating discrepancies in the detection rates of damaged structures in CT and MRI.

Method

216 patients with blunt trauma to the spine who underwent CT followed by supplementary MRI were included in this study. Two board-certified radiologists blinded to clinical symptoms and injury mechanisms independently interpreted all acquired CT and MRI images. The interpretation was performed using a dedicated catalogue of typical findings associated with spinal trauma and assessed for spinal stability using the AO classification systems.

Results

Lesions to structures associated with spinal instability were present in 31.0% in the cervical spine, 12.3% in the thoracic spine, and 29.9% in the lumbar spine. In all spinal segments, MRI provided additional information regarding potentially unstable injuries. Novel information derived from supplementary MRI changed clinical management in 3.6% of patients with injury to the cervical spine. No change in clinical management resulted from novel information on the thoracolumbar spine. Patients with injuries to the vertebral body, intervertebral disc, or spinous process were significantly more likely to benefit from supplementary MRI.

Conclusion

In patients that sustained blunt spinal trauma, supplementary MRI of the cervical spine should routinely be performed to detect injuries that require surgical treatment, whereas CT is the superior imaging modality for the detection of unstable injuries in the thoracolumbar spine.