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M.A. Heuvelmans



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    MINI 36 - Imaging and Diagnostic Workup (ID 163)

    • Event: WCLC 2015
    • Type: Mini Oral
    • Track: Screening and Early Detection
    • Presentations: 2
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      MINI36.02 - Newly Detected Solid Nodules at Incidence CT Lung Cancer Screening Rounds: Occurrence and Lung Cancer Probability (ID 1352)

      18:30 - 20:00  |  Author(s): M.A. Heuvelmans

      • Abstract
      • Slides

      Background:
      Lung cancer screening by low-dose computed tomography (LDCT) is now recommended for high-risk individuals by US guidelines. New nodules detected after initial baseline screening may complicate management. So far, reported results of new nodules have been inconsistent as different definitions were used. The purpose of this study was to determine the occurrence of new solid nodules and their respective lung cancer rate at incidence screening rounds of the Dutch-Belgian Randomized Lung Cancer Screening Trial (NELSON).

      Methods:
      The NELSON trial was approved by the Dutch Ministry of Health. All participants gave written informed consent. In total, 7,557 individuals underwent baseline LDCT screening. Incidence-screening rounds took place after 1, 3 and 5.5 years. This study included participants with solid non-calcified nodules, newly detected after baseline and also in retrospect not present on any previous screen. Lung cancer diagnosis was based on histology, and benignity was based on either histology or a stable size for at least two years. Nodule volume was generated semi-automatically by Lungcare software (Siemens, Erlangen, Germany), and the nodule detection limit was 15mm[3].

      Results:
      During the incidence screening rounds, 1,484 new solid nodules were detected in 949 participants (77% male), with a median age of 59 years (interquartile-range 55-63 years). At the second screening round (1 year after baseline), at least one new solid nodule was present in 4.7% (344/7,295) of participants, and at the third screening round (2 years after the second screening round) additional new nodules were found in 7.1% (491/6,922) of participants. Eventually, a new solid nodule was proven to be lung cancer in 7.9% (75/949) of participants with new solid nodules (77 cancers). A higher number of pack-years smoked increased the risk of a new nodule being cancer significantly (P=0.004). Age and gender distribution were comparable between participants with and without lung cancer detected in a new solid nodule (P=0.236 and P=0.157 respectively). The majority of cancers was diagnosed at stage I (48/77 [62.3%]). Most of the lung cancers were adenocarcinoma (30/77 [39.0%]), squamous cell carcinoma (20/77 [26.0%]) or small cell lung cancer (9/77 [11.7%]).

      Conclusion:
      New solid nodules are common findings in LDCT lung cancer screening and possess a comparably high risk of malignancy. Guidelines may need to consider a more stringent follow-up for new nodules. More research concerning new nodules is necessary to determine a sufficient follow-up strategy and evaluate distinguishing nodule features of benign and malignant new nodules.

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      MINI36.03 - Multi-Nodularity in Baseline CT Lung Cancer Screening and Relationship with Lung Cancer Probability (ID 1392)

      18:30 - 20:00  |  Author(s): M.A. Heuvelmans

      • Abstract
      • Slides

      Background:
      Currently, there is little known about prevalence of multi-nodularity in a high risk screening population. Radiologists often find more than one nodule per screenee. Whether the number of lung nodules plays a role in the probability of lung cancer, remains still largely unknown.

      Methods:
      In the Dutch-Belgian randomized lung cancer screening trial (NELSON), launched in 2003, participants were selected with at least one non-calcified nodule at baseline. The NELSON trial was approved by the Ministry of Health and the ethics board of each participating center. All participants gave written informed consent. The per-participant number of baseline nodules was determined. The probability of lung cancer was compared for categories based on the number of baseline nodules, using chi-square testing. Lung cancer diagnosis was confirmed by histology. Nodules were classified as benign if they did not show growth for up to six years after baseline.

      Results:
      3,392 participants (84,4% male, median age 58 years, median pack years 37,9) with 7,258 nodules at baseline CT screening were included. Of these 3,392 screenees, 1,746 (51,5%) had one nodule, 800 (23,6%) had two nodules, 354 (10,4%) had three nodules, 191 (5,6%) had four nodules, and 301 (8,9%) had five or more nodules. The probability of lung cancer was 61/354 (3.5%) in subjects with one nodule, 37/800 (4.6%) in those with two nodules, 17/354 (4.8%) for three nodules, 12/191 (6.3%) for four nodules and 10/301 (3.3%) when a participant had over four nodules (p=NS). In the baseline screening round, 62 subjects had a malignant nodule. Lung cancer diagnosis was made in the nodule with the largest volume in 60/62 (96.8%) cases. Overall, lung cancer was diagnosed in 137/3,392 subjects (4.0%) in whom nodules were found at baseline. Mean nodule count in screened subjects with only benign nodules was 2.1±1.8, compared to 2.3±2.2 in those with a malignant nodule.

      Conclusion:
      At baseline CT lung cancer screening, nearly half of screened participants with lung nodules have more than one lung nodule. Nodule count did not have predictive value in the determination of lung cancer probability in lung cancer screening participants. In the first screening round, of all detected nodules per screenee, lung cancer was detected most frequently in the nodule with the largest volume.

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    ORAL 09 - CT Screening - New Data and Risk Assessment (ID 95)

    • Event: WCLC 2015
    • Type: Oral Session
    • Track: Screening and Early Detection
    • Presentations: 1
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      ORAL09.01 - Discerning Malignant and Benign New Nodules at Incidence Rounds of CT Lung Cancer Screening: The Role of Volume and Predicted Volume Doubling Time (ID 1358)

      10:45 - 12:15  |  Author(s): M.A. Heuvelmans

      • Abstract
      • Slides

      Background:
      Newly detected nodules after baseline screen are common findings in low-dose computed tomography (LDCT) lung cancer screening, and may complicate management. So far little research focused specifically on nodules newly detected at incidence screening rounds. These nodules develop within a known time-frame and are expected to be fast-growing and potentially malignant. Even so, the majority are benign. The aim of this study was to compare volume and predicted growth rate of benign and malignant new solid nodules detected in the incidence screening rounds of the Dutch-Belgian Randomized Lung Cancer Screening Trial (NELSON).

      Methods:
      The NELSON trial was approved by the Dutch Ministry of Health. All participants gave written informed consent. In total, 7,557 individuals underwent baseline LDCT screening. After the baseline screening, incidence screening rounds took place after 1, 3 and 5.5 years. This study included participants with solid non-calcified nodules, newly detected after baseline and also in retrospect not present on any previous screening. Nodule volume was obtained semi-automatically by Lungcare software (Siemens, Erlangen, Germany). The growth rate at first detection was estimated by calculating the slowest predicted volume-doubling time (pVDT), according to the formula pVDT=[ln(2)*Δt]/[ln(V2/V1)], using the study’s detection limit of 15mm[3] (V1), the volume of the new nodule at first detection (V2), and the time interval between current and last screen (Δt [days]). The pVDT was calculated for nodules with a predicted volume increase of at least 25% (≥ 18.75mm[3]). Lung cancer diagnosis was based on histology. Benignity was based on histology or a stable size for at least two years. Mann-Whitney U testing was used to evaluate differences in volume and pVDT between malignant and benign nodules.

      Results:
      During the incidence screening rounds, 1,484 new solid nodules in 949 participants were detected of which 77 (5.2%) turned out to be malignant. At first detection, both the median volume of malignant (373mm[3], IQR 120-974mm[3]) and benign (44mm[3], interquartile-range [IQR] 22-122mm[3]) new nodules, as well as the median pVDT of malignant (144 days, IQR 116-213 days) and benign (288 days, IQR 153-566 days) new nodules differed significantly (P<0.001 for both). The calculated median pVDT of adenocarcinomas (183 days, IQR 138-299 days) and squamous-cell carcinomas (150 days, IQR 117-223 days) was similar to previously published volume doubling-times of fast-growing baseline cancers in the NELSON trial of the same histological type (196 days, IQR 135-250 days and 142 days, IQR 91-178 days, respectively).

      Conclusion:
      At incidence LDCT lung cancer screening, volume and pVDT can be used to differentiate between malignant and benign nature of newly detected solid nodules. The pVDT is a new measure that can assist in adjusting for time differences in screening intervals.

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    ORAL 24 - CT Detected Nodules - Predicting Biological Outcome (ID 122)

    • Event: WCLC 2015
    • Type: Oral Session
    • Track: Screening and Early Detection
    • Presentations: 1
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      ORAL24.02 - Quantification of Growth Patterns of Screen-Detected Lung Cancers: The NELSON Trial (ID 1455)

      10:45 - 12:15  |  Author(s): M.A. Heuvelmans

      • Abstract
      • Slides

      Background:
      A wait-and-see principle is not commonly used when lung cancer is suspected, because of the aggressiveness of the disease. In-vivo information on growth patterns of lung cancers, from small nodules barely detectable by imaging techniques to histologically proven lung cancers, is therefore scarce. In low-dose computed tomography (LDCT) lung screening, lung nodules, usually benign, are found in the majority of screenees. Follow-up CT examinations are performed to determine nodule growth, in order to differentiate between benign and malignant nodules. Growth is often defined in terms of volume-doubling time (VDT), under the assumption of exponential growth. However, this pattern has never been quantified in actual patient data. Our purpose was to evaluate and quantify growth patterns of lung cancers detected in LDCT lung cancer screening, in order to elucidate the development and progression of early lung cancer.

      Methods:
      The study was based on data of the Dutch-Belgian randomized lung cancer screening trial (NELSON trial). Solid lung cancers detected at ≥3 LDCT examinations before referral and diagnosis were included. Nodule volume was calculated by semi-automated software (LungCARE, Siemens, Erlangen). We fitted lung cancer volume (V) growth curves with a single exponential, expressed as V=V~1~exp(t/τ), with t time from baseline (days), V~1~ estimated volume at baseline (mm[3]) and τ estimated time constant. Overall VDT per lung cancer for all time points combined was calculated using τ*log(2). We used R[2] coefficient of determination as a measure for goodness of fit, where a perfect fit results in R[2]=1. A normalized growth curve for all lung cancers combined was created by plotting normalized volume (V/V~1~), on a logarithmic y-axis as a function of normalized time, t*=t/τ. Statistical analyses were performed using SPSS 20.0 and Octave (www.octave.org).

      Results:
      Forty-seven lung cancers in 46 participants were included. Seven participants were female (13.0%); mean age 61.7 ±6.2 years. Median follow-up time before lung cancer was diagnosed, was 770 days (IQR: 383-1102 days). One cancer (2.1%) was diagnosed after six LDCTs, six (12.8%) after five LDCTs, 14 (29.8%) after four LDCTs, and 26 cancers (55.3%) after three LDCTs. Most lung cancers were stage I disease (35/47, 74.5%) at diagnosis. The majority concerned adenocarcinoma (38/48, 80.9%). Median overall VDT was 348 days (IQR: 222-492). Overall VDT for adenocarcinomas versus other histological cancer types were similar (median 338 days [IQR: 225-470 days] versus 348 days [IQR: 153-558 days], respectively [p=NS]). Good fit to exponential growth was confirmed by the high R[2] coefficient of determination for the individual cancer growth curves (median 0.98; IQR: 0.94-0.99). After normalization, we found linear growth on a logarithmic scale, according to exponential growth, for almost all nodules. Not all cancers showed an exponential growth immediately from baseline; five cancers were identified with constant (low) volume for >500 days before growth expansion occurred. However, when these dormant lung cancers started growing, they followed the exponential function with excellent fit (median 1.00; IQR: 0.98-1.00).

      Conclusion:
      Screen-detected lung cancers usually evolve at an exponential growth rate. This makes VDT a powerful imaging biomarker to stratify prevalent lung nodules to growth rates.

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