Contrast-enhanced pelvic magnetic resonance imaging (MRI) for the prediction of treatment response in mucinous rectal cancer.

Background: In mucinous rectal cancer, it can be difficult to differentiate between cellular and acellular mucin. The purpose of this study was to evaluate, in patients with mucinous rectal cancer, the value of static enhancement (enh) and pharmacokinetic parameters of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in predicting pathologic complete response. Methods: This retrospective cross-sectional study performed at Memorial Sloan Kettering Cancer Center included 43 patients (24 males and 19 females; mean age, 57 years) with mucinous rectal cancer who underwent MRI at baseline as well as after neoadjuvant chemoradiotherapy but before surgical resection between 2008 and 2019. Two radiologists independently segmented tumors on contrast-enhanced axial 3D T1-weighted images and sagittal DCE magnetic resonance images. On contrast-enhanced axial T1-weighted images, the static parameters enh and relative enhancement (renh) were estimated. On DCE images, the pharmacokinetic parameters Ktrans, kep, relative Ktrans (rKtrans), and relative kep (rkep) were estimated. Associations between all parameters with pathologic complete response were tested using Wilcoxon signed-rank tests. Receiver operating characteristic (ROC) analysis was performed to assess the area under the curve (AUC) for each parameter. Results: Of the 43 patients who were included in the study, 42/43 (98%) had evaluable contrast-enhanced axial T1-weighted images and 35/43 (81%) had evaluable DCE images. Of the patients with evaluable contrast-enhanced axial T1-weighted images, 9/42 (21%) had pathologic complete response and 33/42 (79%) did not have pathologic complete response. For reader 1, enh(pre-neoadjuvant chemotherapy), enh(post-neoadjuvant chemotherapy), and renh were significant predictors of pathologic complete response [P=0.045 (AUC =0.73), 0.039 (AUC =0.74), and 0.0042, respectively]. For reader 2, enh(pre-neoadjuvant chemotherapy) and renh were significant predictors [P=0.021 (AUC =0.77) and 0.002, respectively]. For renh, the AUC was 0.83 for reader 1, and 0.82 for reader 2. Meanwhile, of those patients with evaluable DCE images, 9/35 (26%) had pathologic complete response and 26/35 (74%) did not have pathologic complete response. Ktrans(pre-neoadjuvant chemotherapy), kep(pre-neoadjuvant chemotherapy), and rkep were significant predictors [P=0.016 (AUC =0.73), 0.00057 (AUC =0.81), and 0.0096 (AUC =0.74), respectively]. Conclusions: Static and pharmacokinetic parameters of contrast-enhanced MRI show promise to predict neoadjuvant treatment response. Static enh parameters, which are simpler to assess, showed the strongest prediction.

Distinct CT imaging features of new liver metastases from primary genitourinary cancers.

PURPOSE: To apply natural language processing (NLP) to a large volume of structured radiology reports in the investigation of CT imaging features of new liver metastases from primary genitourinary cancers. METHODS: In this retrospective study, a previously reported NLP model was applied to consecutive structured CT reports from 2016 to 2022 to predict those patients with primary genitourinary cancer who developed liver metastasis. Pathology or imaging follow-up served as the reference standard for validating NLP predictions. Subsequently, diagnostic CTs of the identified patients were qualitatively assessed by two radiologists, whereby several imaging features of new liver metastasis were assessed. Proportions of the assessed imaging features were compared between primary genitourinary cancers using the Chi-square or Fisher's exact test. RESULTS: In 112 patients (mean age = 72 years; 83 males), the majority of new liver metastases were hypovascular (73.2%), well defined (76.6%), homogenous (66.9%), and without necrotic/cystic component (73.2%). There was a higher proportion of iso- to hyperdense liver metastases for primary kidney cancer vs other primary genitourinary cancers (42.5% in kidney cancer; 2.3% in ureter/bladder cancer, 8% in prostate cancer, and 0% in testicular cancer; p < 0.05) and a higher proportion of new liver metastases with ill-defined margin for primary prostate cancer vs other primary genitourinary cancers (44.0% in prostate cancer, 15.0% in kidney cancer, 18.6% in ureter/bladder cancer, and 25.0% in testicular cancer; p < 0.05). CONCLUSION: New liver metastases from primary genitourinary cancers tend to be hypovascular and show several distinct imaging features between different primary genitourinary cancers.

Comparison between pelvic MRI, CT, and PET/CT in baseline staging and radiation planning of anal squamous cell carcinoma.

PURPOSE: To investigate the differences in baseline staging of anal squamous cell carcinoma based on CT, MRI, and PET/CT, and the resultant impact on the radiation plan. METHODS: This retrospective study included consecutive patients with anal squamous cell carcinoma who underwent baseline pelvic MRI, CT, and PET/CT (all examinations within 3 weeks of each other) from January 2010 to April 2020. CTs, MRIs, and PET/CTs were re-interpreted by three separate radiologists. Several imaging features were assessed; tumor stage was determined based on the eight edition of the American Joint Committee on Cancer (AJCC) staging manual; and T (tumor), N (node), and M (metastasis) categories were determined based on National Comprehensive Cancer Network (NCCN) guidelines. Radiologist assessments were then randomly presented to a radiation oncologist who formulated the radiation plan in a blinded fashion. RESULTS: Across 28 patients (median age, 62 years [range, 31-78], T-category classification was significantly different on PET/CT compared to MRI and CT (p = 0.037 and 0.031, respectively). PET/CT staged a higher proportion of patients with T1/T2 disease (16/28, 57%) compared to MRI (11/28, 39%) and CT (10/28, 36%). MRI staged a higher proportion of patients with T3/T4 disease (14/28, 50%) compared to CT (12/28, 43%) and PET/CT (11/28, 39%). However, there was no significant difference between the three imaging modalities in terms of either N-category, AJCC staging, or NCCN TNM group classification, or in treatment planning. CONCLUSION: Our exploratory study showed that MRI demonstrated a higher proportion of T3/T4 tumors, while PET/CT demonstrated more T1/T2 tumors; however, MRI, CT, and PET/CT did not show any significant differences in AJCC and TNM group categories, nor was there any significant difference in treatment doses between them when assessed independently by an experienced radiation oncologist.

Preoperative CT and survival data for patients undergoing resection of colorectal liver metastases.

The liver is a common site for the development of metastases in colorectal cancer. Treatment selection for patients with colorectal liver metastases (CRLM) is difficult; although hepatic resection will cure a minority of CRLM patients, recurrence is common. Reliable preoperative prediction of recurrence could therefore be a valuable tool for physicians in selecting the best candidates for hepatic resection in the treatment of CRLM. It has been hypothesized that evidence for recurrence could be found via quantitative image analysis on preoperative CT imaging of the future liver remnant before resection. To investigate this hypothesis, we have collected preoperative hepatic CT scans, clinicopathologic data, and recurrence/survival data, from a large, single-institution series of patients (n = 197) who underwent hepatic resection of CRLM. For each patient, we also created segmentations of the liver, vessels, tumors, and future liver remnant. The largest of its kind, this dataset is a resource that may aid in the development of quantitative imaging biomarkers and machine learning models for the prediction of post-resection hepatic recurrence of CRLM.

Spine MRI Identifies Clinically Relevant Findings in Patients With Cancer Presenting With Back Pain.

STUDY DESIGN: This is a retrospective, cross-sectional study. OBJECTIVE: The primary aim was to identify the diagnostic yield of spine magnetic resonance imaging (MRI) in detecting malignant pathology in cancer patients with back pain. We also sought to evaluate the role of MRI extent ( i.e. regional vs. total) in identifying malignant pathology. SUMMARY OF BACKGROUND DATA: No prior study has systematically investigated the yield of spine MRI in a large cohort of cancer patients. METHODS: Spine MRI reports from 2017 to 2021 for back pain (acute and nonspecified chronicity) in cancer patients were reviewed to identify clinically relevant findings: malignant (1) epidural, (2) leptomeningeal, (3) intramedullary, (4) osseous disease, and (5) fracture. Logistic regression was used to evaluate the association between MRI extent and the presence of cancer-related findings. For patients with multiple MRIs, short-interval scans (≤4 mo) were evaluated to assess the yield of repeat imaging. RESULTS: At least one cancer-related finding was identified on 52% of 5989 spine MRIs ordered for back pain and 57% of 1130 spine MRIs ordered specifically for acute back pain. The most common pathology was malignant osseous disease (2545; 43%). Across all five categories, most findings (77%-89%) were new/progressive. Odds of identifying a finding were significantly higher with total versus regional spine MRIs ( P <0.001). Although only 14 patients had a positive regional MRI followed shortly by a positive total spine MRI, most of these repeat total spine MRIs (78%) identified findings outside the scope of the initial regional scan. Twenty-one patients had both computed tomography and MRI within 30 days of each other; eight (38%) had compression fractures appreciated on MRI but not on computed tomography. CONCLUSIONS: Our findings suggest imaging the total spine in cancer patients with back pain given higher odds of identifying malignant pathology and instances of capturing otherwise not visualized disease. Further work is warranted to confirm these findings.

Factors Affecting Diagnostic Yield of Lesional Bone Biopsy in Hematologic Malignancy Patients.

PURPOSE: To evaluate factors affecting the diagnostic yield (percent of biopsy samples leading to a pathologic diagnosis) of lesional bone biopsies in patients with hematologic malignancies. MATERIALS AND METHODS: This retrospective study included 206 lesional bone biopsies in 182 patients with a hematologic malignancy between January 2017 and December 2022. The parameters that were reviewed to evaluate diagnostic yield included biopsy device type (manual vs. electric-powered drill), number of biopsy cores acquired, core biopsy needle gauge, preliminary intra-procedural sample adequacy (touch preparation cytology determining if samples are adequate for final pathologic examination), lesion morphology on Computed Tomography (CT), and presence of crush artifact. RESULTS: Review of 206 lesional biopsies showed overall diagnostic yield to be 89.8% (185/206). The two statistically significant factors affecting diagnostic yield were biopsy device type and in-room adequacy. 41/42 samples obtained with the electric-powered drill and 144/164 samples obtained using a variety of manual needles were diagnostic (97.6% vs 87.8%, p = 0.03). Of the 192 samples that were assessed for sample adequacy intra-procedurally, 97/102 of the samples that were deemed adequate were diagnostic, and 77/90 of the samples where intra-procedural adequacy was not confirmed were diagnostic (95.1% vs 85.6%, p = 0.018). The remaining factors did not affect diagnostic yield. CONCLUSION: The use of an electric-powered drill bone biopsy device and intra-procedural confirmation of sample adequacy are associated with a higher diagnostic yield of lesional bone biopsies in patients with hematologic malignancies. The presence or absence of crush artifact did not significantly affect the diagnostic yield in these patients.

Evaluating residual tumor after neoadjuvant chemotherapy for muscle-invasive urothelial bladder cancer: diagnostic performance and outcomes using biparametric vs. multiparametric MRI.

BACKGROUND: Neoadjuvant chemotherapy (NAC) before radical cystectomy is standard of care in patients with muscle-invasive bladder cancer (MIBC). Response assessment after NAC is important but suboptimal using CT. We assessed MRI without vs. with intravenous contrast (biparametric [BP] vs. multiparametric [MP]) for identifying residual disease on cystectomy and explored its prognostic role. METHODS: Consecutive MIBC patients that underwent NAC, MRI, and cystectomy between January 2000-November 2022 were identified. Two radiologists reviewed BP-MRI (T2 + DWI) and MP-MRI (T2 + DWI + DCE) for residual tumor. Diagnostic performances were compared using receiver operating characteristic curve analysis. Kaplan-Meier curves and Cox proportional-hazards models were used to evaluate association with disease-free survival (DFS). RESULTS: 61 patients (36 men and 25 women; median age 65 years, interquartile range 59-72) were included. After NAC, no residual disease was detected on pathology in 19 (31.1%) patients. BP-MRI was more accurate than MP-MRI for detecting residual disease after NAC: area under the curve = 0.75 (95% confidence interval (CI), 0.62-0.85) vs. 0.58 (95% CI, 0.45-0.70; p = 0.043). Sensitivity were identical (65.1%; 95% CI, 49.1-79.0) but specificity was higher in BP-MRI compared with MP-MRI for determining residual disease: 77.8% (95% CI, 52.4-93.6) vs. 38.9% (95% CI, 17.3-64.3), respectively. Positive BP-MRI and residual disease on pathology were both associated with worse DFS: hazard ratio (HR) = 4.01 (95% CI, 1.70-9.46; p = 0.002) and HR = 5.13 (95% CI, 2.66-17.13; p = 0.008), respectively. Concordance between MRI and pathology results was significantly associated with DFS. Concordant positive (MRI+/pathology+) patients showed worse DFS than concordant negative (MRI-/pathology-) patients (HR = 8.75, 95% CI, 2.02-37.82; p = 0.004) and compared to the discordant group (MRI+/pathology- or MRI-/pathology+) with HR = 3.48 (95% CI, 1.39-8.71; p = 0.014). CONCLUSION: BP-MRI was more accurate than MP-MRI for identifying residual disease after NAC. A negative BP-MRI was associated with better outcomes, providing complementary information to pathological assessment of cystectomy specimens.

Applying Natural Language Processing to Single-Report Prediction of Metastatic Disease Response Using the OR-RADS Lexicon.

Generating Real World Evidence (RWE) on disease responses from radiological reports is important for understanding cancer treatment effectiveness and developing personalized treatment. A lack of standardization in reporting among radiologists impacts the feasibility of large-scale interpretation of disease response. This study examines the utility of applying natural language processing (NLP) to the large-scale interpretation of disease responses using a standardized oncologic response lexicon (OR-RADS) to facilitate RWE collection. Radiologists annotated 3503 retrospectively collected clinical impressions from radiological reports across several cancer types with one of seven OR-RADS categories. A Bidirectional Encoder Representations from Transformers (BERT) model was trained on this dataset with an 80-20% train/test split to perform multiclass and single-class classification tasks using the OR-RADS. Radiologists also performed the classification to compare human and model performance. The model achieved accuracies from 95 to 99% across all classification tasks, performing better in single-class tasks compared to the multiclass task and producing minimal misclassifications, which pertained mostly to overpredicting the equivocal and mixed OR-RADS labels. Human accuracy ranged from 74 to 93% across all classification tasks, performing better on single-class tasks. This study demonstrates the feasibility of the BERT NLP model in predicting disease response in cancer patients, exceeding human performance, and encourages the use of the standardized OR-RADS lexicon to improve large-scale prediction accuracy.

Extramural Venous Invasion and Tumor Deposit at Diffusion-weighted MRI in Patients after Neoadjuvant Treatment for Rectal Cancer.

Background Diffusion-weighted (DW) imaging is useful in detecting tumor in the primary tumor bed in locally advanced rectal cancer (LARC) after neoadjuvant therapy, but its value in detecting extramural venous invasion (EMVI) and tumor deposit is not well validated. Purpose To evaluate diagnostic accuracy and association with patient prognosis of viable EMVI and tumor deposit on DW images in patients with LARC after neoadjuvant therapy using whole-mount pathology specimens. Materials and Methods This retrospective study included patients who underwent neoadjuvant therapy and surgery from 2018 to 2021. Innovative five-point Likert scale was used by two radiologists to independently evaluate the likelihood of viable EMVI and tumor deposit on restaging DW MRI scans in four axial quadrants (12 to 3 o'clock, 3 to 6 o'clock, 6 to 9 o'clock, and 9 to 12 o'clock). Diagnostic accuracy was assessed at both the per-quadrant and per-patient level, with whole-mount pathology as the reference standard. Weighted κ values for interreader agreement and Cox regression models for disease-free survival and overall survival analyses were used. Results A total of 117 patients (mean age, 56 years ± 12 [SD]; 70 male, 47 female) were included. Pathologically proven viable EMVI and tumor deposit was detected in 29 of 117 patients (25%) and in 44 of 468 quadrants (9.4%). Per-quadrant analyses showed an area under the receiver operating characteristics curve of 0.75 (95% CI: 0.68, 0.83), with sensitivity and specificity of 55% and 96%, respectively. Good interreader agreement was observed between the radiologists (κ = 0.62). Per-patient analysis showed sensitivity and specificity of 62% and 93%, respectively. The presence of EMVI and tumor deposit on restaging DW MRI scans was associated with worse disease-free survival (hazard ratio [HR], 5.6; 95% CI: 2.4, 13.3) and overall survival (HR, 8.9; 95% CI: 1.6, 48.5). Conclusion DW imaging using the five-point Likert scale showed high specificity and moderate sensitivity in the detection of viable extramural venous invasion and tumor deposits in LARC after neoadjuvant therapy, and its presence on restaging DW MRI scans is associated with worse prognosis. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Méndez and Ayuso in this issue.

Synoptic Reporting for Pretreatment CT Examination in Patients With Advanced Ovarian Cancer: Impact on Documentation of Disease Sites and Physician Satisfaction.

BACKGROUND. Imaging reports that consistently document all disease sites with a potential to increase surgical complexity or morbidity can facilitate ovarian cancer treatment planning. OBJECTIVE. The aims of this study were to compare simple structured reports and synoptic reports from pretreatment CT examinations in patients with advanced ovarian cancer in terms of completeness of documenting involvement of clinically relevant anatomic sites as well as to evaluate physician satisfaction with synoptic reports. METHODS. This retrospective study included 205 patients (median age, 65 years) who underwent contrast-enhanced abdominopelvic CT before primary treatment of advanced ovarian cancer from June 1, 2018, to January 31, 2022. A total of 128 reports generated on or before March 31, 2020, used a simple structured report (free text organized into sections); 77 reports generated on or after April 1, 2020, used a synoptic report (a list of 45 anatomic sites relevant to ovarian cancer management, each of which was classified in terms of disease absence versus presence). Reports were reviewed for completeness of documentation of involvement of the 45 sites. For patients who underwent neoadjuvant chemotherapy based on diagnostic laparoscopy findings or underwent primary debulking surgery with suboptimal resection, the EMR was reviewed to identify surgically established sites of disease that were unresectable or challenging to resect. Gynecologic oncology surgeons were electronically surveyed. RESULTS. The mean report turnaround time was 29.8 minutes for simple structured reports versus 54.5 minutes for synoptic reports (p < .001). A mean of 17.6 of 45 sites (range, four to 43 sites) were mentioned by simple structured reports versus 44.5 of 45 sites (range, 39-45) for synoptic reports (p < .001). Forty-three patients had surgically established unresectable or challenging-to-resect disease; involvement of anatomic site(s) with such disease was mentioned in 37% (11/30) of simple structured reports versus 100% (13/13) of synoptic reports (p < .001). All eight surveyed gynecologic oncology surgeons completed the survey. CONCLUSION. A synoptic report improved completeness of pretreatment CT reports in patients with advanced ovarian cancer, including for established sites of unresectable or challenging-to-resect disease. CLINICAL IMPACT. The findings indicate the role of disease-specific synoptic reports in facilitating referrer communication and potentially guiding clinical decision-making.

A preoperative nomogram incorporating CT to predict the probability of ovarian clear cell carcinoma.

OBJECTIVES: To evaluate clinical, laboratory, and radiological variables from preoperative contrast-enhanced computed tomography (CECT) for their ability to distinguish ovarian clear cell carcinoma (OCCC) from non-OCCC and to develop a nomogram to preoperatively predict the probability of OCCC. METHODS: This IRB-approved, retrospective study included consecutive patients who underwent surgery for an ovarian tumor from 1/1/2000 to 12/31/2016 and CECT of the abdomen and pelvis ≤90 days before primary debulking surgery. Using a standardized form, two experienced oncologic radiologists independently analyzed imaging features and provided a subjective 5-point impression of the probability of the histological diagnosis. Nomogram models incorporating clinical, laboratory, and radiological features were created to predict histological diagnosis of OCCC over non-OCCC. RESULTS: The final analysis included 533 patients with surgically confirmed OCCC (n = 61) and non-OCCC (n = 472); history of endometriosis was more often found in patients with OCCC (20% versus 3.6%; p < 0.001), while CA-125 was significantly higher in patients with non-OCCC (351 ng/mL versus 70 ng/mL; p < 0.001). A nomogram model incorporating clinical (age, history of endometriosis and adenomyosis), laboratory (CA-125) and imaging findings (peritoneal implant distribution, morphology, laterality, and diameter of ovarian lesion and of the largest solid component) had an AUC of 0.9 (95% CI: 0.847, 0.949), which was comparable to the AUCs of the experienced radiologists' subjective impressions [0.8 (95% CI: 0.822, 0.891) and 0.9 (95% CI: 0.865, 0.936)]. CONCLUSIONS: A presurgical nomogram model incorporating readily accessible clinical, laboratory, and CECT variables was a powerful predictor of OCCC, a subtype often requiring a distinctive treatment approach.

Imaging of Anal Squamous Cell Carcinoma: Survey Results and Expert Opinion from the Rectal and Anal Cancer Disease-Focused Panel of the Society of Abdominal Radiology.

The role and method of image-based staging of anal cancer has evolved with the rapid development of newer imaging modalities and the need to address the rising incidence of this rare cancer. In 2014, the European Society of Medical Oncology mandated pelvic magnetic resonance imaging (MRI) for anal cancer and subsequently other societies such as the National Comprehensive Cancer Network followed suit with similar recommendations. Nevertheless, great variability exists from center to center and even within individual centers. Notably, this is in stark contrast to the imaging of the anatomically nearby rectal cancer. As participating team members for this malignancy, we embarked on a comprehensive literature review of anal cancer imaging to understand the relative merits of these new technologies which developed after computed tomography (CT), e.g., MRI and positron emission tomography/computed tomography (PET/CT). The results of this literature review helped to inform our next stage: questionnaire development regarding the imaging of anal cancer. Next, we distributed the questionnaire to members of the Society of Abdominal Radiology (SAR) Rectal and Anal Disease-Focused Panel, a group of abdominal radiologists with special interest, experience, and expertise in rectal and anal cancer, to provide expert radiologist opinion on the appropriate anal cancer imaging strategy. In our expert opinion survey, experts advocated the use of MRI in general (65% overall and 91-100% for primary staging clinical scenarios) and acknowledged the superiority of PET/CT for nodal assessment (52-56% agreement for using PET/CT in primary staging clinical scenarios compared to 30% for using MRI). We therefore support the use of MRI and PET and suggest further exploration of PET/MRI as an optimal combined evaluation. Our questionnaire responses emphasized the heterogeneity in imaging practice as performed at numerous academic cancer centers across the United States and underscore the need for further reconciliation and establishment of best imaging practice guidelines for optimized patient care in anal cancer.

MRI assessment of rectal cancer response to neoadjuvant therapy: a multireader study.

OBJECTIVES: A watch and wait strategy with the goal of organ preservation is an emerging treatment paradigm for rectal cancer following neoadjuvant treatment. However, the selection of appropriate patients remains a challenge. Most previous efforts to measure the accuracy of MRI in assessing rectal cancer response used a small number of radiologists and did not report variability among them. METHODS: Twelve radiologists from 8 institutions assessed baseline and restaging MRI scans of 39 patients. The participating radiologists were asked to assess MRI features and to categorize the overall response as complete or incomplete. The reference standard was pathological complete response or a sustained clinical response for > 2 years. RESULTS: We measured the accuracy and described the interobserver variability of interpretation of rectal cancer response between radiologists at different medical centers. Overall accuracy was 64%, with a sensitivity of 65% for detecting complete response and specificity of 63% for detecting residual tumor. Interpretation of the overall response was more accurate than the interpretation of any individual feature. Variability of interpretation was dependent on the patient and imaging feature investigated. In general, variability and accuracy were inversely correlated. CONCLUSIONS: MRI-based evaluation of response at restaging is insufficiently accurate and has substantial variability of interpretation. Although some patients' response to neoadjuvant treatment on MRI may be easily recognizable, as seen by high accuracy and low variability, that is not the case for most patients. KEY POINTS: • The overall accuracy of MRI-based response assessment is low and radiologists differed in their interpretation of key imaging features. • Some patients' scans were interpreted with high accuracy and low variability, suggesting that these patients' pattern of response is easier to interpret. • The most accurate assessments were those of the overall response, which took into consideration both T2W and DWI sequences and the assessment of both the primary tumor and the lymph nodes.

Sarcomatoid renal cell carcinoma: MRI features and their association with survival.

OBJECTIVE: To evaluate MRI features of sarcomatoid renal cell carcinoma (RCC) and their association with survival. METHODS: This retrospective single-center study included 59 patients with sarcomatoid RCC who underwent MRI before nephrectomy during July 2003-December 2019. Three radiologists reviewed MRI findings of tumor size, non-enhancing areas, lymphadenopathy, and volume (and percentage) of T2 low signal intensity areas (T2LIA). Clinicopathological factors of age, gender, ethnicity, baseline metastatic status, pathological details (subtype and extent of sarcomatoid differentiation), treatment type, and follow-up were extracted. Survival was estimated using Kaplan-Meier method and Cox proportional-hazards regression model was used to identify factors associated with survival. RESULTS: Forty-one males and eighteen females (median age 62 years; interquartile range 51-68) were included. T2LIAs were present in 43 (72.9%) patients. At univariate analysis, clinicopathological factors associated with shorter survival were: greater tumor size (> 10 cm; HR [hazard ratio] = 2.44, 95% CI 1.15-5.21; p = 0.02), metastatic lymph nodes (present; HR = 2.10, 95% CI 1.01-4.37; p = 0.04), extent of sarcomatoid differentiation (non-focal; HR = 3.30, 95% CI 1.55-7.01; p < 0.01), subtypes other than clear cell, papillary, or chromophobe (HR = 3.25, 95% CI 1.28-8.20; p = 0.01), and metastasis at baseline (HR = 5.04, 95% CI 2.40-10.59; p < 0.01). MRI features associated with shorter survival were: lymphadenopathy (HR = 2.24, 95% CI 1.16-4.71; p = 0.01) and volume of T2LIA (> 3.2 mL, HR = 4.22, 95% CI 1.92-9.29); p < 0.01). At multivariate analysis, metastatic disease (HR = 6.89, 95% CI 2.79-16.97; p < 0.01), other subtypes (HR = 9.50, 95% CI 2.81-32.13; p < 0.01), and greater volume of T2LIA (HR = 2.51, 95% CI 1.04-6.05; p = 0.04) remained independently associated with worse survival. CONCLUSION: T2LIAs were present in approximately two thirds of sarcomatoid RCCs. Volume of T2LIA along with clinicopathological factors were associated with survival.

Multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE) in diffusion-weighted imaging for rectal MRI: a quantitative and qualitative analysis at multiple b-values.

PURPOSE: To compare four diffusion-weighted imaging (DWI) sequences for image quality, rectal contour, and lesion conspicuity, and to assess the difference in their signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC). METHODS: In this retrospective study of 36 consecutive patients who underwent 3.0 T rectal MRI from January-June 2020, DWI was performed with single-shot echo planar imaging (ss-EPI) (b800 s/mm2), multiplexed sensitivity encoding (MUSE) (b800 s/mm2), MUSE (b1500 s/mm2), and field-of-view optimized and constrained undistorted single-shot (FOCUS) (b1500 s/mm2). Two radiologists independently scored image quality using a 5-point Likert scale. Inter-reader agreement was assessed using the weighted Cohen's к. SNR, CNR, and ADC measurements were compared using the paired t-test. RESULTS: For both readers, MUSE b800 scored significantly higher for image quality, rectal contour, and lesion conspicuity compared to ss-EPI; MUSE b800 also scored significantly higher for image quality and rectal contour compared to all other sequences. Lesion conspicuity was equally superior for MUSE b800 and MUSE b1500 compared to the other two sequences. There was good to excellent inter-reader agreement for all qualitative features (к = 0.72-0.88). MUSE b800 had the highest SNR; MUSE b1500 had the highest CNR. A significant difference in ADC was observed between ss-EPI compared to the other sequences (p < 0.001) and between MUSE b800 and FOCUS. No significant difference in ADC was found between MUSE b1500 and FOCUS b1500. CONCLUSION: MUSE b800 improved image quality over ss-EPI and both MUSE b800 and b1500 showed better tumor conspicuity compared to conventional ss-EPI.

Fat-containing adnexal masses on MRI: solid tissue volume and fat distribution as a guide for O-RADS Score assignment.

PURPOSE: To explore ways to improve O-RADS MRI scoring for fat-containing adnexal masses, by investigating methods for quantifying solid tissue volume and fat distribution and evaluating their associations with malignancy. METHODS: This retrospective, single-center study included patients with fat-containing adnexal masses on MRI during 2008-2021. Two radiologists independently reviewed overall size (Sizeoverall), size of any solid tissue (Sizeanysolid), size of solid tissue that was not Rokitansky nodule (Sizenon-Rokitansky), and fat distribution. Wilcoxon test, Fisher-exact test, and ROC curve analysis were performed. Reference standard was pathology or follow-up > 24 months. RESULTS: 188 women (median age 35 years) with 163 benign and 25 malignant lesions were included. Sizeoverall (R1, 9.9 cm vs 5.9 cm; R2, 12.4 cm vs 6.0 cm), Sizeanysolid (R1, 5.1 cm vs 1.2 cm; R2, 3.2 cm vs 0.0 cm), Sizenon-Rokitansky (R1, 5.1 cm vs 0.0 cm; R2, 3.1 cm vs 0.0 cm), and fat distribution differed significantly between malignant and benign lesions (p < 0.01). Area under ROC curve was greatest using Sizenon-Rokitansky (R1, 0.83; R2, 0.86) vs Sizeoverall (R1, 0.78; R2, 0.81) or Sizeanysolid (R1, 0.79; R2, 0.81), though differences were non-significant (p = 0.48-0.93). Cutoffs for Sizenon-Rokitansky (R1, ≥ 1.2 cm; R2, ≥ 1.0 cm) yielded sensitivity and specificity of 0.72 and 0.93 (R1) and 0.76 and 0.95 (R2). Among immature teratomas, 85.7% displayed scattered fat. CONCLUSION: Overall size, size of (any or non-Rokitansky-nodule) solid tissue, and fat distribution differed between benign and malignant fat-containing adnexal masses. Incorporating these would constitute simple and practical approaches to refining O-RADS MRI scoring.

Natural Language Processing of Computed Tomography Reports to Label Metastatic Phenotypes With Prognostic Significance in Patients With Colorectal Cancer.

PURPOSE: Natural language processing (NLP) applied to radiology reports can help identify clinically relevant M1 subcategories of patients with colorectal cancer (CRC). The primary purpose was to compare the overall survival (OS) of CRC according to American Joint Committee on Cancer TNM staging and explore an alternative classification. The secondary objective was to estimate the frequency of metastasis for each organ. METHODS: Retrospective study of CRC who underwent computed tomography (CT) chest, abdomen, and pelvis between July 1, 2009, and March 26, 2019, at a tertiary cancer center, previously labeled for the presence or absence of metastasis by an NLP prediction model. Patients were classified in M0, M1a, M1b, and M1c (American Joint Committee on Cancer), or an alternative classification on the basis of the metastasis organ number: M1, single; M2, two; M3, three or more organs. Cox regression models were used to estimate hazard ratios; Kaplan-Meier curves were used to visualize survival curves using the two M1 subclassifications. RESULTS: Nine thousand nine hundred twenty-eight patients with a total of 48,408 CT chest, abdomen, and pelvis reports were included. On the basis of NLP prediction, the median OS of M1a, M1b, and M1c was 4.47, 1.72, and 1.52 years, respectively. The median OS of M1, M2, and M3 was 4.24, 2.05, and 1.04 years, respectively. Metastases occurred most often in liver (35.8%), abdominopelvic lymph nodes (32.9%), lungs (29.3%), peritoneum (22.0%), thoracic nodes (19.9%), bones (9.2%), and pelvic organs (7.5%). Spleen and adrenal metastases occurred in < 5%. CONCLUSION: NLP applied to a large radiology report database can identify clinically relevant metastatic phenotypes and be used to investigate new M1 substaging for CRC. Patients with three or more metastatic disease organs have the worst prognosis, with an OS of 1 year.

Can 18F-FDG PET/CT Radiomics Features Predict Clinical Outcomes in Patients with Locally Advanced Esophageal Squamous Cell Carcinoma?

This study aimed to assess the usefulness of radiomics features of 18F-FDG PET/CT in patients with locally advanced esophageal cancers (ESCC) in predicting outcomes such as clinical tumor (cT) and nodal (cN) categories, PET response to induction chemotherapy (PET response), progression-free survival (PFS), and overall survival (OS). Pretreatment PET/CT images from patients who underwent concurrent chemoradiotherapy from July 2002 to February 2017 were segmented, and data were split into training and test sets. Model development was performed on the training datasets and a maximum of five features were selected. Final diagnostic accuracies were determined using the test dataset. A total of 86 PET/CTs (58 men and 28 women, mean age 65 years) were segmented. Due to small lesion size, 12 patients were excluded. The diagnostic accuracies as derived from the CT, PET, and combined PET/CT test datasets were as follows: cT category-70.4%, 70.4%, and 81.5%, respectively; cN category-69.0%, 86.2%, and 86.2%, respectively; PET response-60.0%, 66.7%, and 70.0%, respectively; PFS-60.7%, 75.0%, and 75.0%, respectively; and OS-51.7%, 55.2%, and 62.1%, respectively. A radiomics assessment of locally advanced ESCC has the potential to predict various clinical outcomes. External validation of these models would be further helpful.

Multimodal data integration using machine learning improves risk stratification of high-grade serous ovarian cancer.

Patients with high-grade serous ovarian cancer suffer poor prognosis and variable response to treatment. Known prognostic factors for this disease include homologous recombination deficiency status, age, pathological stage and residual disease status after debulking surgery. Recent work has highlighted important prognostic information captured in computed tomography and histopathological specimens, which can be exploited through machine learning. However, little is known about the capacity of combining features from these disparate sources to improve prediction of treatment response. Here, we assembled a multimodal dataset of 444 patients with primarily late-stage high-grade serous ovarian cancer and discovered quantitative features, such as tumor nuclear size on staining with hematoxylin and eosin and omental texture on contrast-enhanced computed tomography, associated with prognosis. We found that these features contributed complementary prognostic information relative to one another and clinicogenomic features. By fusing histopathological, radiologic and clinicogenomic machine-learning models, we demonstrate a promising path toward improved risk stratification of patients with cancer through multimodal data integration.