Pitfalls in diagnosing colon cancer on abdominal CT

Exploring colorectal cancer patients' diagnostic pathways and general practitioners' assessment of the diagnostic processes: a Danish survey study

INTRODUCTION

Colorectal cancer (CRC) is among the most common cancers and the prognosis of CRC is highly dependent on stage at diagnosis. Although many cases are diagnosed swiftly, there is still room for improvement.

AIM

We aimed to explore CRC diagnostic pathways, encompassing (1) place of initial contact; (2) associations with symptom presentations, sex, and age with events in the diagnostic process and initial referrals and (3) the general practitioner's (GP's) evaluation of the diagnostic processes.

METHODS

All GPs in North-, Central-, and Southern Denmark were invited to fill in questionnaires for their listed patients diagnosed with cancer during the past two years.

RESULTS

Among 1,032 recorded CRC patients, 65% had their initial contact in general practice, 5% within the out-of hours service, 10% in the hospital, and 20% were diagnosed based on screening. A total of 27% of CRC patients over 40 who initially presented in general practice were treated or referred on suspicion of another disease first, and 9% were reported to have had hesitated in seeking medical attention. Some 37% presented solely non-specific symptoms, increasing the odds of the GP advising watchful waiting (OR 2.48; 95% CI 1.06-5.81), treating or referring on the suspicion of another illness first (OR 2.57; 95% CI 1.76-3.75), wait due to normal findings (OR 2.11; 95% CI 1.16-3.85), or referring to diagnostic imaging (OR 3.07; 95% CI 1.63-5.79). The GPs assessed nearly one fifth of the diagnostic processes as poor.

CONCLUSION

Most CRC patients are diagnosed with initial presentation in general practice. Having non-specific symptoms is common and challenges timely diagnosis.

Imaging and Metabolic Diagnostic Methods in the Stage Assessment of Rectal Cancer

Rectal cancer (RC) is a prevalent malignancy with significant morbidity and mortality rates. The accurate staging of RC is crucial for optimal treatment planning and patient outcomes. This review aims to summarize the current literature on imaging and metabolic diagnostic methods used in the stage assessment of RC. Various imaging modalities play a pivotal role in the initial evaluation and staging of RC. These include magnetic resonance imaging (MRI), computed tomography (CT), and endorectal ultrasound (ERUS). MRI has emerged as the gold standard for local staging due to its superior soft tissue resolution and ability to assess tumor invasion depth, lymph node involvement, and the presence of extramural vascular invasion. CT imaging provides valuable information about distant metastases and helps determine the feasibility of surgical resection. ERUS aids in assessing tumor depth, perirectal lymph nodes, and sphincter involvement. Understanding the strengths and limitations of each diagnostic modality is essential for accurate staging and treatment decisions in RC. Furthermore, the integration of multiple imaging and metabolic methods, such as PET/CT or PET/MRI, can enhance diagnostic accuracy and provide valuable prognostic information. Thus, a literature review was conducted to investigate and assess the effectiveness and accuracy of diagnostic methods, both imaging and metabolic, in the stage assessment of RC.

Deep learning for colorectal cancer detection in contrast-enhanced CT without bowel preparation: a retrospective, multicentre study

BACKGROUND

Contrast-enhanced CT scans provide a means to detect unsuspected colorectal cancer. However, colorectal cancers in contrast-enhanced CT without bowel preparation may elude detection by radiologists. We aimed to develop a deep learning (DL) model for accurate detection of colorectal cancer, and evaluate whether it could improve the detection performance of radiologists.

METHODS

We developed a DL model using a manually annotated dataset (1196 cancer vs 1034 normal). The DL model was tested using an internal test set (98 vs 115), two external test sets (202 vs 265 in 1, and 252 vs 481 in 2), and a real-world test set (53 vs 1524). We compared the detection performance of the DL model with radiologists, and evaluated its capacity to enhance radiologists' detection performance.

FINDINGS

In the four test sets, the DL model had the area under the receiver operating characteristic curves (AUCs) ranging between 0.957 and 0.994. In both the internal test set and external test set 1, the DL model yielded higher accuracy than that of radiologists (97.2% vs 86.0%, p < 0.0001; 94.9% vs 85.3%, p < 0.0001), and significantly improved the accuracy of radiologists (93.4% vs 86.0%, p < 0.0001; 93.6% vs 85.3%, p < 0.0001). In the real-world test set, the DL model delivered sensitivity comparable to that of radiologists who had been informed about clinical indications for most cancer cases (94.3% vs 96.2%, p > 0.99), and it detected 2 cases that had been missed by radiologists.

INTERPRETATION

The developed DL model can accurately detect colorectal cancer and improve radiologists' detection performance, showing its potential as an effective computer-aided detection tool.

FUNDING

This study was supported by National Science Fund for Distinguished Young Scholars of China (No. 81925023); Regional Innovation and Development Joint Fund of National Natural Science Foundation of China (No. U22A20345); National Natural Science Foundation of China (No. 82072090 and No. 82371954); Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (No. 2022B1212010011); High-level Hospital Construction Project (No. DFJHBF202105).

Pictorial essay: improving diagnostic effectiveness of colorectal cancer at CT

As the routine use for CT increases, there is an opportunity to increase the detection rate of unsuspected and asymptomatic colorectal cancers. This pictorial essay provides abundant examples of the typical morphologic appearances of colorectal cancer in the unprepared colorectum. Many examples of lesions that were missed in clinical practice are illustrated with lessons on how to avoid these errors. Atypical appearances of colorectal cancer are also illustrated. The overall aim is to increase the detection rate of colorectal cancer at routine CT.

Localization of Colorectal Cancer Lesions in Contrast-Computed Tomography Images via a Deep Learning Approach

Abdominal computed tomography (CT) is a frequently used imaging modality for evaluating gastrointestinal diseases. The detection of colorectal cancer is often realized using CT before a more invasive colonoscopy. When a CT exam is performed for indications other than colorectal evaluation, the tortuous structure of the long, tubular colon makes it difficult to analyze the colon carefully and thoroughly. In addition, the sensitivity of CT in detecting colorectal cancer is greatly dependent on the size of the tumor. Missed incidental colon cancers using CT are an emerging problem for clinicians and radiologists; consequently, the automatic localization of lesions in the CT images of unprepared bowels is needed. Therefore, this study used artificial intelligence (AI) to localize colorectal cancer in CT images. We enrolled 190 colorectal cancer patients to obtain 1558 tumor slices annotated by radiologists and colorectal surgeons. The tumor sites were double-confirmed via colonoscopy or other related examinations, including physical examination or image study, and the final tumor sites were obtained from the operation records if available. The localization and training models used were RetinaNet, YOLOv3, and YOLOv8. We achieved an F1 score of 0.97 (±0.002), a mAP of 0.984 when performing slice-wise testing, 0.83 (±0.29) sensitivity, 0.97 (±0.01) specificity, and 0.96 (±0.01) accuracy when performing patient-wise testing using our derived model YOLOv8 with hyperparameter tuning.

Strategies for improving colorectal cancer detection with routine computed tomography

PURPOSE

To report the detection rate of colorectal tumors with computed tomography (CT) performed within 1 year before diagnosis for indications other than colon abnormalities. Strategies to improve cancer detection are reported.

METHODS

Two board-certified, subspecialty-trained abdominal radiologists retrospectively reviewed patient health records and CT images with knowledge of tumor location/size. Patients were classified into 3 groups: prospective (colon abnormality suggesting neoplasm documented in radiologic report), retrospective (not documented in radiologic report but detected in our retrospective review of CT images), and undetected (neither prospectively nor retrospectively detected). Retrospective detection confidence and morphologic characteristics of each tumor were also recorded.

RESULTS

Of 209 included patients, 106 (50.7%) had prospectively detected tumors, 66 (31.6%) had retrospectively detected tumors, and 37 (17.7%) had undetected tumors. Asymmetric bowel wall thickening and polypoid masses were present more often in the retrospective group than in the prospective group (27% vs. 10.5% and 26% vs. 17.1%, respectively). Tumors in the ascending colon were more likely to be detected retrospectively than prospectively (odds ratio, 2.75; 95% CI 1.07-7.08; P = 0.04). Undetected tumors were smaller on average (2.9 cm) than prospective (6.0 cm) and retrospective (4.9 cm) tumors (P = 0.03). Detection confidence was lower for retrospectively detected tumors than for prospectively detected tumors (P = 0.03). Indications other than abdominal pain were most common for retrospectively detected tumors (P = 0.03). Use of intravenous contrast material was lowest in the undetected group (P = 0.003). The prospective group had more pericolonic abnormalities, regional/retroperitoneal lymph node involvement (P < 0.001), and distant metastases than did the retrospective group (P = 0.01).

CONCLUSION

Half of all colorectal tumors were not detected prospectively. Radiologists should perform meticulous colon tracking regardless of the indication for CT. The right colon merits additional examination. Polypoid and asymmetric morphologic characteristics were most often overlooked, but these characteristics can be learned to improve detection.

Efficacy of High-Resolution Preoperative 3D Reconstructions for Lesion Localization in Oncological Colorectal Surgery—First Pilot Study

When planning an operation, surgeons usually rely on traditional 2D imaging. Moreover, colon neoplastic lesions are not always easy to locate macroscopically, even during surgery. A 3D virtual model may allow surgeons to localize lesions with more precision and to better visualize the anatomy. In this study, we primary analyzed and discussed the clinical impact of using such 3D models in colorectal surgery. This is a monocentric prospective observational pilot study that includes 14 consecutive patients who presented colorectal lesions with indication for surgical therapy. A staging computed tomography (CT)/magnetic resonance imaging (MRI) scan and a colonoscopy were performed on each patient. The information gained from them was provided to obtain a 3D rendering. The 2D images were shown to the surgeon performing the operation, while the 3D reconstructions were shown to a second surgeon. Both of them had to locate the lesion and describe which procedure they would have performed; we then compared their answers with one another and with the intraoperative and histopathological findings. The lesion localizations based on the 3D models were accurate in 100% of cases, in contrast to conventional 2D CT scans, which could not detect the lesion in two patients (in these cases, lesion localization was based on colonoscopy). The 3D model reconstruction allowed an excellent concordance correlation between the estimated and the actual location of the lesion, allowing the surgeon to correctly plan the procedure with excellent results. Larger clinical studies are certainly required.

CT and 3 Tesla MRI in the TN Staging of Colon Cancer: A Prospective, Blind Study

(1) Background: Computer tomography (CT) scanning is currently the standard method for staging of colon cancer; however, the CT based preoperative local staging is far from optimal. The purpose of this study was to investigate the sensitivity and specificity of magnetic resonance imaging (MRI) compared to CT in the T- and N-staging of colon cancer. (2) Methods: Patients underwent a standard contrast-enhanced CT examination. For the abdominal MRI scan, a 3 Tesla unit was used, including diffusion weighted imaging (DWI). Experienced radiologists reported the CT and MRI scans blinded to each other and the endpoint of the pathological report. (3) Results: From 2018 to 2021, 134 patients received CT and MRI scans. CT identified 118 of the 134 tumors, whereas MRI identified all tumors. For discriminating between stage T3ab and T3cd, the sensitivity of CT was 51.1% and of MRI 80.0% (p = 0.02). CT and MRI showed a sensitivity of 21.4% and 46.4% in detecting pT4 tumors and a specificity of 79.0% and 85.0%, respectively. (4) Conclusion: Compared to CT, the sensitivity of MRI was statistically significantly higher in staging advanced T3cd and T4 tumors. MRI has the potential to be used in the treatment planning of colon cancer.

Quantitative Assessment of Radiologically Indeterminate Local Colonic Wall Thickening on Iodine Density Images Using Dual-Layer Spectral Detector CT

RATIONALE AND OBJECTIVES

To assess local colonic wall thickening (LCWT, thicknesses: >3 mm, lengths: <5 cm) quantitatively on iodine density images using dual-layer spectral detector computed tomography (DLSCT).

MATERIALS AND METHODS

This retrospective study included 80 patients who underwent both conventional contrast-enhanced CT and colonoscopy within one month. The region of interest was delineated on the chosen images with the iodine density image model. The iodine concentration (IC), normalized IC (NIC), and thickness of the colonic wall in the lesion area were compared between the pathological and nonpathological groups.

RESULTS

There were 50 patients whose area of LCWT discovered at CT scans displayed colon neoplasia at colonoscopy. The other 30 patients with LCWT on CT images showed normal appearances during colonoscopy. There was no significant difference in colonic wall thickness between the pathological and nonpathological (p> 0.05) LCWT groups. The IC and NIC of patients with colon neoplasms were significantly higher than those with nonpathologic LCWT (both p< 0.001). The ROC curve showed that when IC and NIC was 1.49 mg/mL and 0.33, the sensitivity and specificity for diagnosing colon neoplasm were 91.5% and 75.8%, 85.1% and 84.8%, respectively.

CONCLUSION

IC and NIC values from DLSCT could provide a satisfied diagnostic value to identify LCWT caused by colon neoplasia.

Gut wrenching: cases of missed gastrointestinal tumors and their mimics on computed tomography

Computed tomography (CT) of the abdomen and pelvis is one of the most common imaging studies ordered through the emergency department (ED). Because these studies are ordered for the detection of acute abnormalities and due to the relatively low incidence in patients presenting through the ED, gastrointestinal tumors are commonly missed. Moreover, many CT findings of malignant tumors overlap with benign entities, which can present a diagnostic challenge. This review article will describe the common CT findings of gastric, small bowel, colon, and appendiceal cancer as well as some of the common benign gastrointestinal conditions with similar imaging findings.

Computed tomography diagnosed first time diverticulitis and colorectal cancer

BACKGROUND

Computed tomography (CT) with intravenous contrast is the gold standard for diagnosing diverticulitis. Published results concerning follow-up colonoscopy after an episode of acute diverticulitis to rule out cancer are conflicting. This study aimed to evaluate the risk of underlying colonic malignancy in patients diagnosed with a first time diverticulitis with a state of the art CT investigation with intravenous contrast.

METHODS

Retrospective analysis of all patients with a first episode of diverticulitis diagnosed with CT at Danderyds Hospital, Stockholm, between January 1, 2015, and November 16, 2016. Data on modified Hinchey classification, age, sex, laboratory parameters, body mass index, and colonoscopy findings were recorded.

RESULTS

The study identified 518 patients with a CT-verified first time diverticulitis. Four hundred twenty-six (82%) of the 518 patients underwent follow-up colonoscopy and constitute our study cohort. CT showed that 402 patients had uncomplicated diverticulitis (modified Hinchey Ia), and 24 patients had complicated diverticulitis (modified Hinchey ≥Ib). Colonoscopy showed cancers in 2 (0.5%) of the 426 patients initially diagnosed as acute diverticulitis. In addition, 13 (3%) patients had advanced adenomas, and 121 (28%) patients had benign adenomas upon follow-up colonoscopy. Patients with CT-verified complicated diverticulitis (modified Hinchey ≥Ib) had a significantly higher risk for colon cancer compared with patients with an uncomplicated first time diverticulitis.

CONCLUSION

Our study supports routine follow-up colonoscopy after a first episode of CT-diagnosed complicated diverticulitis. In contrast, we do not find an increased risk for neoplasia in patients with uncomplicated diverticulitis.

Diagnostic property of direct referral from general practitioners to contrast-enhanced thoracoabdominal CT in patients with serious but non-specific symptoms or signs of cancer: a retrospective cohort study on cancer prevalence after 12 months

OBJECTIVES

To describe the diagnostic properties of thoracoabdominal contrast-enhanced CT (ceCT), when general practitioners (GPs) managed referral to ceCT through the non-specific symptoms or signs of cancer-cancer patient pathway (NSSC-CPP).

DESIGN

Retrospective cohort study including patients from a part of Denmark.

SETTING

Department of Internal Medicine at a university hospital.

PARTICIPANTS

In total, 529 patients underwent ceCT.

PRIMARY AND SECONDARY OUTCOMES

Our primary objective was to estimate the negative and positive likelihood ratios for being diagnosed with cancer within 1 year after ceCT. Our secondary outcomes were prevalence and final diagnoses of malignancy (including temporal trends since implementation of NSSC-CPP in 2012), the prevalence of revision of CT scans and referral patterns based on ceCT results.

RESULTS

In total, 529 subjects underwent ceCT and malignancy was identified in 104 (19.7%) patients; 101 (97.1%) during initial workup and 3 patients during the subsequent 12 months follow-up.Eleven patients had a false-negative ceCT, and revision classified the ceCT as 'probable/possible malignancy' in eight (73%) patients. The negative predictive value was 98% and positive predictive value 63%. Negative and positive likelihood ratios for malignancy was 0.1 and 7.9, respectively.

CONCLUSION

Our study shows that ceCT as part of GP-coordinated workup has a low negative likelihood ratio for identifying malignancy; this is important since identifying patients for further workup is vital.

Ability of DWI to characterize bowel fibrosis depends on the degree of bowel inflammation

OBJECTIVES

Although diffusion-weighted imaging (DWI) is reported to be accurate in detecting bowel inflammation in Crohn's disease (CD), its ability to assess bowel fibrosis remains unclear. This study assessed the role of DWI in the characterization of bowel fibrosis using surgical histopathology as the reference standard.

METHODS

Abdominal DWI was performed before elective surgery in 30 consecutive patients with CD. The apparent diffusion coefficients (ADCs) in pathologic bowel walls were calculated. Region-by-region correlations between DWI and the surgical specimens were performed to determine the histologic degrees of bowel fibrosis and inflammation.

RESULTS

ADCs correlated negatively with bowel inflammation (r = - 0.499, p < 0.001) and fibrosis (r = - 0.464, p < 0.001) in 90 specimens; the ADCs in regions of nonfibrosis and mild fibrosis were significantly higher than those in regions of moderate-severe fibrosis (p = 0.008). However, there was a significant correlation between the ADCs and bowel fibrosis (r = - 0.641, p = 0.001) in mildly inflamed segments but not in moderately (r = - 0.274, p = 0.255) or severely (r = - 0.225, p = 0.120) inflamed segments. In the mildly inflamed segments, the ADCs had good accuracy with an area under the receiver-operating characteristic curve of 0.867 (p = 0.004) for distinguishing nonfibrosis and mild fibrosis from moderate-severe fibrosis.

CONCLUSIONS

ADC can be used to assess bowel inflammation in patients with CD. However, it only enables the accurate detection of the degree of bowel fibrosis in mildly inflamed bowel walls. Therefore, caution is advised when using ADC to predict the degree of intestinal fibrosis.

KEY POINTS

• Diffusion-weighted imaging was used to assess bowel inflammation in patients with Crohn's disease. • The ability of diffusion-weighted imaging to evaluate bowel fibrosis decreased with increasing bowel inflammation. • Diffusion-weighted imaging enabled accurate detection of the degree of fibrosis only in mildly inflamed bowel walls.