Outcome of indeterminate liver lesions on computed tomography in patients with colorectal cancer

Circulating tumor DNA for prognosis assessment and postoperative management after curative-intent resection of colorectal liver metastases

The recurrence rate of colorectal liver metastases (CRLM) patients treated with curative intent is above 50%. Standard of care surveillance includes intensive computed tomographic (CT) imaging as well as carcinoembryonic antigen (CEA) measurements. Nonetheless, relapse detection often happens too late to resume curative treatment. This longitudinal cohort study enrolled 115 patients with plasma samples (N = 439) prospectively collected before surgery, postoperatively at day 30 and every third month for up to 3 years. Droplet digital PCR (ddPCR) was used to monitor serial plasma samples for somatic mutations. Assessment of ctDNA status either immediately after surgery, or serially during surveillance, stratified the patients into groups of high and low recurrence risk (hazard ratio [HR], 7.6; 95% CI, 3.0-19.7; P < .0001; and HR, 4.3; 95% CI, 2.3-8.1; P < .0001, respectively). The positive predictive value (PPV) of ctDNA was 100% in all postoperative analyses. In multivariable analyses, postoperative ctDNA status was the only consistently significant risk marker associated with relapse (P < .0001). Indeterminate CT findings were observed for 30.8% (21/68) of patients. All patients (9/21) that were ctDNA positive at the time of the indeterminate CT scan later relapsed, contrasting 42.6% (5/12) of those ctDNA negative (P = .0046). Recurrence diagnoses in patients with indeterminate CT findings were delayed (median 2.8 months, P < .0001). ctDNA status is strongly associated with detection of minimal residual disease and early detection of relapse. Furthermore, ctDNA status can potentially contribute to clinical decision-making in case of indeterminate CT findings, reducing time-to-intervention.

Newly detected liver nodules with a history of colorectal cancer: are they metastatic? Review of 2,632 cases in a single center

Background

The diagnosis of newly detected liver nodules in patients with colorectal cancer (CRC) is crucial for determining prognosis and treatment. Accurate identification of benign nodules can help avoid unnecessary therapy. The aim of our study was to retrospectively review patients with CRC who underwent liver resection for benign liver nodules misdiagnosed as CRC metastasis (CRLM) in our institution.

Methods

We reviewed all patients with a history of CRC who underwent liver resection from January 2012 to December 2019 in our institution. We specifically focused on nodules pathologically confirmed as benign. The pathology was rechecked by an independent pathologist. The clinicopathological characteristics of these patients were collected. Preoperative imaging examinations, including ultrasound (US), magnetic resonance imaging (MRI), and positron emission tomography-computed tomography (PET-CT) were reviewed.

Results

From 2012 to 2019, a total of 2,632 patients with CRC who were preoperatively diagnosed CRLM received liver resection, among which 2,584 (98.2%) cases were proven to be malignant, and 48 (1.8%) cases were benign. Among these 48 cases, 24 were pathologically confirmed as focal nodular hyperplasia (FNH), 9 were peliosis, 10 were inflammatory lesions, and 5 were hemangioma. At least one preoperative imaging examination indicated CRLM, with a median size of 2.0 cm (range, 0.4–8.0 cm). Before liver resection, ten patients received chemotherapy after the discovery of liver nodules.

Conclusions

It should be noted that newly detected liver nodules in patients with a history of CRC could be benign. Accurate diagnosis of liver nodules in CRC is necessary to avoid overtreatment and to identify cost-effective medication.

Indeterminate liver lesions in early stage rectal cancer patients, can they be ignored?

PURPOSE

Small hypo-attenuating indeterminate liver lesions are often encountered at staging Computed Tomography (CT) in early stage rectal cancer patients. This study aims to determine the incidence and prognostic significance of these lesions.

MATERIALS AND METHODS

A single institution's colorectal cancer (CRC) database was searched for patients with early stage rectal cancer, defined as a cT1/2N0 tumor on Magnetic Resonance Imaging (MRI). Abdominal CT scans of these patients were assessed for the presence of liver lesions and according to their morphology they were categorized. Preoperative MRI scans of the liver and abdominal follow-up imaging were assessed to determine whether the liver lesions found at staging CT appeared to be CRC metastases or not.

RESULTS

In a consecutive cohort of 1232 operated CRC patients, 84 patients with early stage rectal cancer (cT1/2N0 on MRI) were identified. Forty-five of the 84 patients (54%) had one or more liver lesions on staging CT with a total of 122 liver lesions. This consisted of 95(78%) indeterminate lesions, 25(20%) cysts and 2(2%) haemangiomas. Preoperative MRI of the liver and regular follow-up imaging revealed no synchronous or metachronous liver metastases in this cohort.

CONCLUSION

Small hypo-attenuating indeterminate lesions of the liver are common in patients diagnosed with early rectal cancer and seem have no clinical significance. Additional pre-operative imaging or follow-up imaging for indeterminate liver lesions in these patients may be unnecessary.

Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses

BACKGROUND AND AIMS

Detection and characterization of focal liver lesions (FLLs) is key for optimizing treatment for patients who may have a primary hepatic cancer or metastatic disease to the liver. This is the first study to develop an EUS-based convolutional neural network (CNN) model for the purpose of identifying and classifying FLLs.

METHODS

A prospective EUS database comprising cases of FLLs visualized and sampled via EUS was reviewed. Relevant still images and videos of liver parenchyma and FLLs were extracted. Patient data were then randomly distributed for the purpose of CNN model training and testing. Once a final model was created, occlusion heatmap analysis was performed to assess the ability of the EUS-CNN model to autonomously identify FLLs. The performance of the EUS-CNN for differentiating benign and malignant FLLs was also analyzed.

RESULTS

A total of 210,685 unique EUS images from 256 patients were used to train, validate, and test the CNN model. Occlusion heatmap analyses demonstrated that the EUS-CNN model was successful in autonomously locating FLLs in 92.0% of EUS video assets. When evaluating any random still image extracted from videos or physician-captured images, the CNN model was 90% sensitive and 71% specific (area under the receiver operating characteristic [AUROC], 0.861) for classifying malignant FLLs. When evaluating full-length video assets, the EUS-CNN model was 100% sensitive and 80% specific (AUROC, 0.904) for classifying malignant FLLs.

CONCLUSIONS

This study demonstrated the capability of an EUS-CNN model to autonomously identify FLLs and to accurately classify them as either malignant or benign lesions.

Pitfalls and value of organ specific approach in evaluating indeterminate lesions detected on CT in colorectal cancer by [F18] FDG PET/CT

Objective

The objective of this study is to evaluate the value of FDG PET/CT for different involved organs showing Indeterminate/ equivocal / suspicious lesions detected on IV contrasted CT during surveillance follow up for colorectal cancer.

Materials and methods

A total of 67 patients with colorectal cancer how are on regular surveillance follow up by IV contrasted CT scans revealing indeterminate lesions were studied. Subsequent FDG PET/CT evaluation was performed as a problem solving modality. PET/CT results were statistically characterized when compared to biopsy results or to follow/up results. Also Statistical parameters were calculated for each organ involved. The evaluation of all CT indeterminate lesions by FDG PET/CT showed overall sensitivity of 93%, Specificity of 81%, Negative predictive value of 94%, Positive predictive value 80% and accuracy of 87%. However in an organ specific approach the highest accuracy was for lymph nodes with results showing a 100% accuracy and the lowest accuracy was for local disease at a value of 80%. Probable explanations for the falsely characterized lesions resulting in the pitfalls seen and in the imperfect accuracy were provided.

Conclusion

Study shows that FDG PET/CT is an excellent tool in characterizing CT indeterminate lesions during surveillance of colorectal cancer, However different organs showed variable accuracy results with the highest accuracy for our study was for lymph node status (100%) and the lowest accuracy being for local disease at the original site of primary tumor (80%).

Recommendations for the Management of Incidental Hepatobiliary Findings in Adults: Endorsement and Adaptation of the 2017 and 2013 ACR Incidental Findings Committee White Papers by the Canadian Association of Radiologists Incidental Findings Working Group

The Canadian Association of Radiologists Incidental Findings Working Group consists of both academic subspecialty and general radiologists and is tasked with adapting and expanding upon the American College of Radiology incidental findings white papers to more closely apply to Canadian practice patterns, particularly more comprehensively dealing with the role of ultrasound and pursuing more cost-effective approaches to the workup of incidental findings without compromising patient care. Presented here are the 2020 Canadian guidelines for the management of hepatobiliary incidental findings. Topics covered include initial assessment of hepatic steatosis and cirrhosis, the workup of incidental liver masses identified on ultrasound and computed tomography (with algorithms presented), incidental gallbladder findings (wall thickening, calcification, and polyps), and management of incidental biliary dilatation.