Phase I trial of single-photon emission computed tomography-guided liver-directed radiotherapy for patients with low functional liver volume.

BACKGROUND: Traditional constraints specify that 700 cc of liver should be spared a hepatotoxic dose when delivering liver-directed radiotherapy to reduce the risk of inducing liver failure. We investigated the role of single-photon emission computed tomography (SPECT) to identify and preferentially avoid functional liver during liver-directed radiation treatment planning in patients with preserved liver function but limited functional liver volume after receiving prior hepatotoxic chemotherapy or surgical resection. METHODS: This phase I trial with a 3 + 3 design evaluated the safety of liver-directed radiotherapy using escalating functional liver radiation dose constraints in patients with liver metastases. Dose-limiting toxicities were assessed 6-8 weeks and 6 months after completing radiotherapy. RESULTS: All 12 patients had colorectal liver metastases and received prior hepatotoxic chemotherapy; 8 patients underwent prior liver resection. Median computed tomography anatomical nontumor liver volume was 1584 cc (range = 764-2699 cc). Median SPECT functional liver volume was 1117 cc (range = 570-1928 cc). Median nontarget computed tomography and SPECT liver volumes below the volumetric dose constraint were 997 cc (range = 544-1576 cc) and 684 cc (range = 429-1244 cc), respectively. The prescription dose was 67.5-75 Gy in 15 fractions or 75-100 Gy in 25 fractions. No dose-limiting toxicities were observed during follow-up. One-year in-field control was 57%. One-year overall survival was 73%. CONCLUSION: Liver-directed radiotherapy can be safely delivered to high doses when incorporating functional SPECT into the radiation treatment planning process, which may enable sparing of lower volumes of liver than traditionally accepted in patients with preserved liver function. TRIAL REGISTRATION: NCT02626312.

A Feasibility Study on Deep Learning Reconstruction to Improve Image Quality With PROPELLER Acquisition in the Setting of T2-Weighted Gynecologic Pelvic Magnetic Resonance Imaging.

OBJECTIVES: Evaluate deep learning (DL) to improve the image quality of the PROPELLER (Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction technique) for 3 T magnetic resonance imaging of the female pelvis. METHODS: Three radiologists prospectively and independently compared non-DL and DL PROPELLER sequences from 20 patients with a history of gynecologic malignancy. Sequences with different noise reduction factors (DL 25%, DL 50%, and DL 75%) were blindly reviewed and scored based on artifacts, noise, relative sharpness, and overall image quality. The generalized estimating equation method was used to assess the effect of methods on the Likert scales. Quantitatively, the contrast-to-noise ratio and signal-to-noise ratio (SNR) of the iliac muscle were calculated, and pairwise comparisons were performed based on a linear mixed model. P values were adjusted using the Dunnett method. Interobserver agreement was assessed using the κ statistic. P value was considered statistically significant at less than 0.05. RESULTS: Qualitatively, DL 50 and DL 75 were ranked as the best sequences in 86% of cases. Images generated by the DL method were significantly better than non-DL images ( P < 0.0001). Iliacus muscle SNR on DL 50 and DL 75 was significantly better than non-DL images ( P < 0.0001). There was no difference in contrast-to-noise ratio between the DL and non-DL techniques in the iliac muscle. There was a high percent agreement (97.1%) in terms of DL sequences' superior image quality (97.1%) and sharpness (100%) relative to non-DL images. CONCLUSION: The utilization of DL reconstruction improves the image quality of PROPELLER sequences with improved SNR quantitatively.

Multimodality annotated hepatocellular carcinoma data set including pre- and post-TACE with imaging segmentation.

Hepatocellular carcinoma (HCC) is the most common primary liver neoplasm, and its incidence has doubled over the past two decades owing to increasing risk factors. Despite surveillance, most HCC cases are diagnosed at advanced stages and can only be treated using transarterial chemo-embolization (TACE) or systemic therapy. TACE failure may occur with incidence reaching up to 60% of cases, leaving patients with a financial and emotional burden. Radiomics has emerged as a new tool capable of predicting tumor response to TACE from pre-procedural computed tomography (CT) studies. This data report defines the HCC-TACE data collection of confirmed HCC patients who underwent TACE and have pre- and post-procedure CT imaging studies and available treatment outcomes (time-to-progression and overall survival). Clinically curated segmentation of pre-procedural CT studies was done for the purpose of algorithm training for prediction and automatic liver tumor segmentation.

Diagnostic value of 3.0 T versus 1.5 T MRI in staging prostate cancer: systematic review and meta-analysis.

Purpose: To compare the diagnostic performance of 3.0 T and 1.5 T MRI in the staging of prostate cancer. Material and methods: English-language studies on the diagnostic accuracy of 3.0 T and 1.5 T MRI in prostate cancer staging published through May 2020 were searched for in relevant databases. The focus was on studies in which both 3.0 T and 1.5 T MRI were performed in the study population, to reduce interstudy heterogeneity. Pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under the receiver operating characteristic curve were determined for 3.0 T and for 1.5 T along with 95% confidence intervals (CIs). Results: Out of 8 studies identified, 4 met the inclusion criteria. 3.0 T (n = 160) had a pooled sensitivity of 69.5% (95% CI: 56.4-80.1%) and a pooled specificity of 48.8% (95% CI: 6.0-93.4%), while 1.5 T (n = 139) had a pooled sensitivity of 70.6% (95% CI: 55.0-82.5%; p = 0.91) and a pooled specificity of 41.7% (95% CI: 6.2-88.6%; p = 0.88). The pooled DOR for 3.0 T was 3 (95% CI: 0-26.0%), while the pooled DOR for 1.5 T was 2 (95% CI: 0-18.0%), which was not a significant difference (p = 0.89). Conclusions: 3.0 T has slightly better diagnostic performance than 1.5 T MRI in prostate cancer staging (3 vs. 2), although without statistical significance. Our findings suggest the need for larger, randomized trials directly comparing 3.0 T and 1.5 T MRI in prostate cancer.

Defining Diagnostic Criteria for Prostatic Ductal Adenocarcinoma at Multiparametric MRI.

Background Prostatic ductal adenocarcinoma (DAC) is an aggressive histologic variant of prostate cancer that often warrants multimodal therapy and poses a significant diagnostic challenge clinically and at imaging. Purpose To develop multiparametric MRI criteria to define DAC and to assess their diagnostic performance in differentiating DAC from prostatic acinar adenocarcinoma (PAC). Materials and Methods Men with histologically proven DAC who had multiparametric MRI before radical prostatectomy were retrospectively identified from January 2011 through November 2018. MRI features were predefined using a subset of nine DACs and then compared for men with peripheral-zone DACs 1 cm or greater in size and men with matched biopsy-confirmed International Society of Urological Pathology grade group 4-5 PAC, by four independent radiologists blinded to the pathologic diagnosis. Diagnostic performance was determined by consensus read. Patient and tumor characteristics were compared by using the Fisher test, t-tests, and Mann-Whitney U test. Agreement (Cohen κ) and sensitivity analyses were also performed. Results There were 59 men with DAC (median age, 63 years [interquartile range, 56, 67 years]) and 59 men with PAC (median age, 64 years [interquartile range, 59, 69 years]). Predefined MRI features, including intermediate T2 signal, well-defined margin, lobulation, and hypointense rim, were detected in a higher proportion of DACs than PACs (76% [45 of 59] vs 5% [three of 59]; P < .001). On consensus reading, the presence of three or more features demonstrated 76% sensitivity, 94% specificity, 94% positive predictive value [PPV], and 80% negative predictive value [NPV] for all DACs and 100% sensitivity, 95% specificity, 81% PPV, and 100% NPV for pure DACs. The DACs and PACs showed no difference in contrast enhancement (100% vs 100%; P >.99, median T2 signal intensity (254 vs 230; P = .99), or apparent diffusion coefficient (median, 677 10-6 mm2/sec vs 685 10-6 mm2/sec; P = .73). Conclusion The presence of intermediate T2 signal, well-defined margin, lobulation, and/or hypointense rim, together with restricted diffusion and contrast enhancement at multiparametric MRI of the prostate, suggests prostatic ductal adenocarcinoma rather than prostatic acinar adenocarcinoma. © RSNA, 2022 Online supplemental material is available for this article.

Errors and Misinterpretations in Imaging of Chronic Liver Diseases.

MRI is an important problem-solving tool for accurate characterization of liver lesions. Chronic liver disease alters the typical imaging characteristics and complicates liver imaging. Awareness of imaging pitfalls and technical artifacts and ways to mitigate them allows for more accurate and timely diagnosis.

What's New in Hepatic Steatosis.

Hepatic steatosis can lead to liver cancer, cirrhosis, and portal hypertension. There are two main types, non-alcoholic fatty liver disease (NAFLD) and alcoholic liver disease. The detection and quantification of hepatic steatosis with lifestyle changes can slow the evolution from NAFLD to steatohepatitis. Currently, the gold standard for the quantification of fat in the liver is biopsy, has some limitations. Hepatic steatosis is frequently detected during cross sectional imaging. Ultrasound (US), Computed Tomography (CT), and Magnetic Resonance Imaging (MRI) provide noninvasive assessment of liver parenchyma and can detect fat infiltration in the liver. However, the non-invasive quantification of hepatic steatosis by imaging has been challenging. Recent MRI techniques show great promise in the detection and quantification of liver fat. The aim of this article is to review the utilization of non-invasive imaging modalities for the detection and quantification of hepatic steatosis, to evaluate their advantages and limitations.

Novel deep learning-based noise reduction technique for prostate magnetic resonance imaging.

INTRODUCTION: Magnetic resonance imaging (MRI) has played an increasingly major role in the evaluation of patients with prostate cancer, although prostate MRI presents several technical challenges. Newer techniques, such as deep learning (DL), have been applied to medical imaging, leading to improvements in image quality. Our goal is to evaluate the performance of a new deep learning-based reconstruction method, "DLR" in improving image quality and mitigating artifacts, which is now commercially available as AIRTM Recon DL (GE Healthcare, Waukesha, WI). We hypothesize that applying DLR to the T2WI images of the prostate provides improved image quality and reduced artifacts. METHODS: This study included 31 patients with a history of prostate cancer that had a multiparametric MRI of the prostate with an endorectal coil (ERC) at 1.5 T or 3.0 T. Four series of T2-weighted images were generated in total: one set with the ERC signal turned on (ERC) and another set with the ERC signal turned off (Non-ERC). Each of these sets then reconstructed using two different reconstruction methods: conventional reconstruction (Conv) and DL Recon (DLR): ERCDLR, ERCConv, Non-ERCDLR, and Non-ERCConv. Three radiologists independently reviewed and scored the four sets of images for (i) image quality, (ii) artifacts, and (iii) visualization of anatomical landmarks and tumor. RESULTS: The Non-ERCDLR scored as the best series for (i) overall image quality (p < 0.001), (ii) reduced artifacts (p < 0.001), and (iii) visualization of anatomical landmarks and tumor. CONCLUSION: Prostate imaging without the use of an endorectal coil could benefit from deep learning reconstruction as demonstrated with T2-weighted imaging MRI evaluations of the prostate.

18F-Fluciclovine Uptake in a Ureterocele.

A 60-year-old man with prostate adenocarcinoma status post radical prostatectomy and bilateral pelvic lymph node dissection referred for restaging F-fluciclovine PET/CT due to rising serum prostate-specific antigen levels (1.1 ng/mL at that time of imaging). PET/CT images were obtained from the proximal thighs to the vertex of the skull approximately 3 to 5 minutes after the IV administration of 347.8 MBq (9.4 mCi) of F-fluciclovine. PET/CT imaging demonstrated a focus of abnormally increased F-fluciclovine uptake at the right ureterovesical junction. Subsequent MRI of the pelvis revealed that this focus corresponded to a benign ureterocele.

Value of Follow-Up Chest Computed Tomography in the Surveillance of Patients with Hepatocellular Carcinoma.

PURPOSE: To evaluate the value of follow-up chest CT in the surveillance of HCC patients. BACKGROUND: Imaging guidelines for the surveillance of hepatocellular carcinoma (HCC) patients recommend multiple follow-up computed tomography (CT) examinations of the chest, abdomen, and pelvis. Imaging studies are a major driver of rising healthcare costs. The appropriate use of imaging studies must be evaluated to provide valued health care. METHODS: We reviewed the radiology reports of baseline and follow-up chest, abdominal, and pelvic CT examinations of HCC patients. We categorized the incidence of malignancy in the chest and abdomen for the baseline and follow-up examinations. We also categorized the follow-up examinations as showing improved disease, stable disease, or disease progression. We correlated any progression of disease in the chest with progression of disease in the abdomen. We determined the extent to which disease progression in the chest occurred alongside that in the abdomen. Descriptive statistical analysis was carried out using R (version 3.5.2, R Development Core Team). RESULTS: Of the 226 patients included in our study, only 7 (3%) had disease progression in the chest without corresponding disease progression in the abdomen and pelvis on follow-up CT. Only 1.8% of patients with disease progression in the chest had a negative CT chest at baseline. CONCLUSION: Follow-up chest CT has limited benefit in the surveillance of HCC patients, especially those with negative baseline chest CT findings.

A modular phantom and software to characterize 3D geometric distortion in MRI.

Magnetic resonance imaging (MRI) offers outstanding soft tissue contrast that may reduce uncertainties in target and organ-at-risk delineation and enable online adaptive image-guided treatment. Spatial distortions resulting from non-linearities in the gradient fields and non-uniformity in the main magnetic field must be accounted for across the imaging field-of-view to prevent systematic errors during treatment delivery. This work presents a modular phantom and software application to characterize geometric distortion (GD) within the large field-of-view MRI images required for radiation therapy simulation. The modular phantom is assembled from a series of rectangular foam blocks containing high-contrast fiducial markers in a known configuration. The modular phantom design facilitates transportation of the phantom between different MR scanners and MR-guided linear accelerators and allows the phantom to be adapted to fit different sized bores or coils. The phantom was evaluated using a 1.5 T MR-guided linear accelerator (MR-Linac) and 1.5 T and 3.0 T diagnostic scanners. Performance was assessed by varying acquisition parameters to induce image distortions in a known manner. Imaging was performed using T1 and T2 weighted pulse sequences with 2D and 3D distortion correction algorithms and the receiver bandwidth (BW) varied as 250-815 Hz pixel-1. Phantom set-up reproducibility was evaluated across independent set-ups. The software was validated by comparison with a non-modular phantom. Average geometric distortion was 0.94 ± 0.58 mm for the MR-Linac, 0.90 ± 0.53 mm for the 1.5 T scanner, and 1.15 ± 0.62 mm for the 3.0 T scanner, for a 400 mm diameter volume-of-interest. GD increased, as expected, with decreasing BW, and with the 2D versus 3D correction algorithm. Differences in GD attributed to phantom set-up were 0.13 mm or less. Differences in GD for the two software applications were less than 0.07 mm. A novel modular phantom was developed to evaluate distortions in MR images for radiation therapy applications.

Quality comparison between three-dimensional T2-weighted SPACE and two-dimensional T2-weighted turbo spin echo magnetic resonance images for the brachytherapy planning evaluation of prostate and periprostatic anatomy.

PURPOSE: The purpose of this study was to compare an isotropic three-dimensional (3D) T2-weighted sequence sampling perfection with application-optimized contrasts by using flip angle evolution (SPACE) with an axial two-dimensional T2-weighted turbo spin echo (TSE) sequence with regard to overall image quality and the delineation of normal prostate and periprostatic anatomy for low-dose-rate prostate cancer brachytherapy planning evaluation. METHODS AND MATERIALS: Patients (n = 69) with prostate cancer who had pelvic magnetic resonance imaging (MRI) for low-dose-rate brachytherapy treatment planning were included. Three radiologists independently assessed the visibility of nine anatomic structures on each sequence by using a 5-point scale and overall image quality by using a 4-point scale. The significance of the differences in diagnostic performance was tested with a Wilcoxon signed rank test. RESULTS: No significant intersequence differences were found for most (7/9) anatomical structures and overall image quality. The mean scores for visibility of anatomical structures on the 3D SPACE and 2D TSE sequences, respectively, were as follows: the zonal anatomy (3.7; 3.9, p = 0.05), prostate capsule (3.9; 4.0, p = 0.08), neurovascular bundle (2.9; 2.9, p = 0.9), rectoprostatic angle (3.8; 3.8, p = 0.35), rectum (4.2; 4.3, p = 0.26), urethra (3.8; 3.9, p = 0.12), urinary bladder (4.6; 4.6, p = 0.61), and overall image quality (2.9; 2.9, p = 0.33). 3D SPACE was superior for delineation of the genitourinary diaphragm (3.8; 3.6, p = 0.003), whereas 2D TSE was superior for delineation of the seminal vesicles (3.5; 4.0, p < 0.0001). CONCLUSIONS: Anatomic delineation of the prostatic and periprostatic anatomy provided by the 3D SPACE sequence is as robust in quality as that provided by a conventional 2D TSE sequence with superior delineation of the genitourinary diaphragm. For MRI-based brachytherapy treatment planning, the 3D SPACE sequence with subcentimeter isotropic resolution can replace the 2D TSE sequence and be incorporated into standard MRI protocols.

Angiogenesis in Hepatocellular Carcinoma; Pathophysiology, Targeted Therapy, and Role of Imaging.

Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide, usually occurring on a background of liver cirrhosis. HCC is a highly vascular tumor in which angiogenesis plays a major role in tumor growth and spread. Tumor-induced angiogenesis is usually related to a complex interplay between multiple factors and pathways, with vascular endothelial growth factor being a major player in angiogenesis. In the past decade, understanding of tumor-induced angiogenesis has led to the emergence of novel anti-angiogenic therapies, which act by reducing neo-angiogenesis, and improving patient survival. Currently, Sorafenib and Lenvatinib are being used as the first-line treatment for advanced unresectable HCC. However, a disadvantage of these agents is the presence of numerous side effects. A major challenge in the management of HCC patients being treated with anti-angiogenic therapy is effective monitoring of treatment response, which decides whether to continue treatment or to seek second-line treatment. Several criteria can be used to assess response to treatment, such as quantitative perfusion on cross-sectional imaging and novel/emerging MRI techniques, including a host of known and emerging biomarkers and radiogenomics. This review addresses the pathophysiology of angiogenesis in HCC, accurate imaging assessment of angiogenesis, monitoring effects of anti-angiogenic therapy to guide future treatment and assessing prognosis.

Intrahepatic cholangiocarcinoma: pathogenesis, current staging, and radiological findings.

To this date, it is a major oncological challenge to optimally diagnose, stage, and manage intrahepatic cholangiocarcinoma (ICC). Imaging can not only diagnose and stage ICC, but it can also guide management. Hence, imaging is indispensable in the management of ICC. In this article, we review the pathology, epidemiology, genetics, clinical presentation, staging, pathology, radiology, and treatment of ICC.

Feasibility of Automated Volumetric Assessment of Large Hepatocellular Carcinomas' Responses to Transarterial Chemoembolization.

Background: Hepatocellular carcinoma (HCC) is the most common liver malignancy and the leading cause of death in patients with cirrhosis. Various treatments for HCC are available, including transarterial chemoembolization (TACE), which is the commonest intervention performed in HCC. Radiologic tumor response following TACE is an important prognostic factor for patients with HCC. We hypothesized that, for large HCC tumors, assessment of treatment response made with automated volumetric response evaluation criteria in solid tumors (RECIST) might correlate with the assessment made with the more time- and labor-intensive unidimensional modified RECIST (mRECIST) and manual volumetric RECIST (M-vRECIST) criteria. Accordingly, we undertook this retrospective study to compare automated volumetric RECIST (A-vRECIST) with M-vRECIST and mRESIST for the assessment of large HCC tumors' responses to TACE. Methods:We selected 42 pairs of contrast-enhanced computed tomography (CT) images of large HCCs. Images were taken before and after TACE, and in each of the images, the HCC was segmented using both a manual contouring tool and a convolutional neural network. Three experienced radiologists assessed tumor response to TACE using mRECIST criteria. The intra-class correlation coefficient was used to assess inter-reader reliability in the mRECIST measurements, while the Pearson correlation coefficient was used to assess correlation between the volumetric and mRECIST measurements. Results:Volumetric tumor assessment using automated and manual segmentation tools showed good correlation with mRECIST measurements. For A-vRECIST and M-vRECIST, respectively, r = 0.597 vs. 0.622 in the baseline studies; 0.648 vs. 0.748 in the follow-up studies; and 0.774 vs. 0.766 in the response assessment (P < 0.001 for all). The A-vRECIST evaluation showed high correlation with the M-vRECIST evaluation (r = 0.967, 0.937, and 0.826 in baseline studies, follow-up studies, and response assessment, respectively, P < 0.001 for all). Conclusion:Volumetric RECIST measurements are likely to provide an early marker for TACE monitoring, and automated measurements made with a convolutional neural network may be good substitutes for manual volumetric measurements.

Evaluation of feasibility and image quality of a new radial quantitative T2 weighted imaging sequence for liver MRI.

OBJECTIVES: To evaluate the clinical feasibility of a new T2 weighted sequence to calculate T2 relaxation times (T2RT) of liver lesions using two-dimensional radial turbo spin echo (2DRTSE) and to evaluate this sequence by performing image quality and relaxation time comparison of multiple liver lesions. MATERIALS AND METHODS: This prospective analysis of 2DRTSE sequences (using 22 echoes) was performed in 19 patients with 36 liver lesions. Two radiologists independently obtained T2RTs for liver lesions and scored image quality and image artifacts. Lesions were classified as cyst, hemangioma, solid, or necrotic. T2RT values were compared. Inter-reader agreement was evaluated. RESULTS: The 2DRTSE images were considered good quality with few artifacts by both radiologists. Nineteen patients were included in the study, with a total of 36 liver lesions. Two of the liver lesions were classified as cysts, 7 as hemangiomas, 4 as necrotic lesions, and 23 as solid lesions. The concordance correlation coefficient was 0.996 for the calculated T2RT of each liver lesion between the two readers, indicating good agreement. There was statically significant difference of the calculated T2RT for each lesion type. CONCLUSION: The 2DRTSE sequence can be performed and provides good T2W image quality and a quantitative T2RT map of the entire abdomen. The liver lesions can be distinguished based on the calculated T2RT using this technique. 2DRTSE could potentially supplant the current T2-weighted imaging sequence with the benefit of quantitative T2RTs.

Comparison of free breathing and respiratory triggered diffusion-weighted imaging sequences for liver imaging.

BACKGROUND: Diffusion-weighted imaging (DWI) has become a useful tool in the detection, characterization, and evaluation of response to treatment of many cancers, including malignant liver lesions. DWI offers higher image contrast between lesions and normal liver tissue than other sequences. DWI images acquired at two or more b-values can be used to derive an apparent diffusion coefficient (ADC). DWI in the body has several technical challenges. This include ghosting artifacts, mis-registration and susceptibility artifacts. New DWI sequences have been developed to overcome some of these challenges. Our goal is to evaluate 3 new DWI sequences for liver imaging. AIM: To qualitatively and quantitatively compare 3 DWI sequences for liver imaging: free-breathing (FB), simultaneous multislice (SMS), and prospective acquisition correction (PACE). METHODS: Magnetic resonance imaging (MRI) was performed in 20 patients in this prospective study. The MR study included 3 separate DWI sequences: FB-DWI, SMS-DWI, and PACE-DWI. The image quality, mean ADC, standard deviations (SD) of ADC, and ADC histogram were compared. Wilcoxon signed-rank tests were used to compare qualitative image quality. A linear mixed model was used to compare the mean ADC and the SDs of the ADC values. All tests were 2-sided and P values of < 0.05 were considered statistically significant. RESULTS: There were 56 lesions (50 malignant) evaluated in this study. The mean qualitative image quality score of PACE-DWI was 4.48. This was significantly better than that of SMS-DWI (4.22) and FB-DWI (3.15) (P < 0.05). Quantitatively, the mean ADC values from the 3 different sequences did not significantly differ for each liver lesion. FB-DWI had a markedly higher variation in the SD of the ADC values than did SMS-DWI and PACE-DWI. We found statistically significant differences in the SDs of the ADC values for FB-DWI vs PACE-DWI (P < 0.0001) and for FB-DWI vs SMS-DWI (P = 0.03). The SD of the ADC values was not statistically significant for PACE-DWI and SMS-DWI (P = 0.18). The quality of the PACE-DWI ADC histograms were considered better than the SMS-DWI and FB-DWI. CONCLUSION: Compared to FB-DWI, both PACE-DWI and SMS-DWI provide better image quality and decreased quantitative variability in the measurement of ADC values of liver lesions.

Automated Volumetric Assessment of Hepatocellular Carcinoma Response to Sorafenib: A Pilot Study.

PURPOSE: This pilot study evaluates the feasibility of automated volumetric quantification of hepatocellular carcinoma (HCC) as an imaging biomarker to assess treatment response for sorafenib. METHODS: In this institutional review board-approved, Health Insurance Portability and Accountability Act-compliant retrospective study, a training database of manually labeled background liver, enhancing and nonenhancing tumor tissue was established using pretherapy and first posttherapy multiphasic computed tomography images from a registry of 13 HCC patients. For each patient, Hounsfield density and geometry-based feature images were generated from registered multiphasic computed tomography data sets and used as the input for a random forest-based classifier of enhancing and nonenhancing tumor tissue. Leave-one-out cross-validation of the dice similarity measure was applied to quantify the classifier accuracy. A Cox regression model was used to confirm volume changes as predictors of time to progression (TTP) of target lesions for both manual and automatic methods. RESULTS: When compared with manual labels, an overall classification accuracy of dice similarity coefficient of 0.71 for pretherapy and 0.66 posttherapy enhancing tumor labels and 0.45 for pretherapy and 0.59 for posttherapy nonenhancing tumor labels was observed. Automated methods for quantifying volumetric changes in the enhancing lesion agreed with manual methods and were observed as a significant predictor of TTP. CONCLUSIONS: Automated volumetric analysis was determined to be feasible for monitoring HCC response to treatment. The information extracted using automated volumetrics is likely to reproduce labor-intensive manual data and provide a good predictor for TTP. Further work will extend these studies to additional treatment modalities and larger patient populations.

Pitfalls in liver MRI: Technical approach to avoiding misdiagnosis and improving image quality.

The following is an illustrative review of common pitfalls in liver MRI that may challenge interpretation. This article reviews common technical and diagnostic challenges encountered when interpreting dynamic multiphasic T1 -weighted imaging, hepatobiliary phase imaging, and diffusion-weighted imaging of the liver. Additionally, each section includes suggestions for avoiding diagnostic and technical errors. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:41-58.

White paper of the Society of Abdominal Radiology hepatocellular carcinoma diagnosis disease-focused panel on LI-RADS v2018 for CT and MRI.

The Liver Imaging and Reporting Data System (LI-RADS) is a comprehensive system for standardizing the terminology, technique, interpretation, reporting, and data collection of liver imaging with the overarching goal of improving communication, clinical care, education, and research relating to patients at risk for or diagnosed with hepatocellular carcinoma (HCC). In 2018, the American Association for the Study of Liver Diseases (AASLD) integrated LI-RADS into its clinical practice guidance for the imaging-based diagnosis of HCC. The harmonization between the AASLD and LI-RADS diagnostic imaging criteria required minor modifications to the recently released LI-RADS v2017 guidelines, necessitating a LI-RADS v2018 update. This article provides an overview of the key changes included in LI-RADS v2018 as well as a look at the LI-RADS v2018 diagnostic algorithm and criteria, technical recommendations, and management suggestions. Substantive changes in LI-RADS v2018 are the removal of the requirement for visibility on antecedent surveillance ultrasound for LI-RADS 5 (LR-5) categorization of 10-19 mm observations with nonrim arterial phase hyper-enhancement and nonperipheral "washout", and adoption of the Organ Procurement and Transplantation Network definition of threshold growth (≥ 50% size increase of a mass in ≤ 6 months). Nomenclatural changes in LI-RADS v2018 are the removal of -us and -g as LR-5 qualifiers.